Applied System on Biomedical Engineering, Healthcare and Sustainability

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Bioengineering bioengineering	4.6	4.2	2014	17.7 Days	CHF 2700
Electronics electronics	2.9	4.7	2012	15.6 Days	CHF 2400
Healthcare healthcare	2.8	2.7	2013	19.5 Days	CHF 2700
Journal of Clinical Medicine jcm	3.9	5.4	2012	17.9 Days	CHF 2600
Sustainability sustainability	3.9	5.8	2009	18.8 Days	CHF 2400

11 pages, 1542 KiB

Open AccessArticle

Assessment of the Efficiency of Measuring Foot and Ankle Edema with a 3D Portable Scanner

by Julien Beldame, Riccardo Sacco, Marie-Aude Munoz, Marion Masse and Matthieu Lalevée

Bioengineering 2023, 10(5), 549; https://doi.org/10.3390/bioengineering10050549 - 03 May 2023

Cited by 2 | Viewed by 1410

Background: To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle and to compare the acquisition time associated with these two methods. Methods: Foot volume was measured in 29 [...] Read more.

Background: To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle and to compare the acquisition time associated with these two methods. Methods: Foot volume was measured in 29 healthy volunteers (58 feet, 24 females and 5 males) by a 3D scanner (UPOD-S 3D Laser Full-Foot Scanner®) and by water displacement volumetry. Measurements were performed on both feet, up to a height of 10 cm above the ground. The acquisition time for each method was evaluated. The Kolmogorov-Smirnov test, Lin’s Concordance Correlation Coefficient, and a Student’s t-test were performed. Results: Mean foot volume was 869.7 +/− 165.1 cm³ (3D scanner) versus 867.9 +/− 155.4 cm³ (water-displacement volumetry) (p < 10⁻⁵). The concordance of measurements was 0.93, indicative of a high correlation between the two techniques. Volumes were 47.8 cm³ lower when using the 3D scanner versus water volumetry. After statistically correcting this underestimation, the concordance was improved (0.98, residual bias = −0.03 +/− 35.1 cm³). The mean examination time was 4.2 +/− 1.7 min (3D optical scanner) versus 11.1 +/− 2.9 min (water volumeter) (p < 10⁻⁴). Conclusions: Ankle/foot volumetric measurements performed using this portable 3D scanner are reliable and fast and can be used in clinical practice and research. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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11 pages, 2936 KiB

Open AccessArticle

Effects of Background Music on Mental Fatigue in Steady-State Visually Evoked Potential-Based BCIs

by Shouwei Gao, Kang Zhou, Jun Zhang, Yi Cheng and Shujun Mao

Healthcare 2023, 11(7), 1014; https://doi.org/10.3390/healthcare11071014 - 02 Apr 2023

Viewed by 1613

Abstract

As a widely used brain–computer interface (BCI) paradigm, steady-state visually evoked potential (SSVEP)-based BCIs have the advantages of high information transfer rates, high tolerance for artifacts, and robust performance across diverse users. However, the incidence of mental fatigue from prolonged, repetitive stimulation is [...] Read more.

As a widely used brain–computer interface (BCI) paradigm, steady-state visually evoked potential (SSVEP)-based BCIs have the advantages of high information transfer rates, high tolerance for artifacts, and robust performance across diverse users. However, the incidence of mental fatigue from prolonged, repetitive stimulation is a critical issue for SSVEP-based BCIs. Music is often used as a convenient, non-invasive means of relieving mental fatigue. This study investigates the compensatory effect of music on mental fatigue through the introduction of different modes of background music in long-duration, SSVEP-BCI tasks. Changes in electroencephalography power index, SSVEP amplitude, and signal-to-noise ratio were used to assess participants’ mental fatigue. The study’s results show that the introduction of exciting background music to the SSVEP-BCI task was effective in relieving participants’ mental fatigue. In addition, for continuous SSVEP-BCI tasks, a combination of musical modes that used soothing background music during the rest interval phase proved more effective in reducing users’ mental fatigue. This suggests that background music can provide a practical solution for long-duration SSVEP-based BCI implementation. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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17 pages, 1725 KiB

Open AccessArticle

Automated Diagnosis of Diabetic Retinopathy Using Deep Learning: On the Search of Segmented Retinal Blood Vessel Images for Better Performance

by Mohammad B. Khan, Mohiuddin Ahmad, Shamshul B. Yaakob, Rahat Shahrior, Mohd A. Rashid and Hiroki Higa

Bioengineering 2023, 10(4), 413; https://doi.org/10.3390/bioengineering10040413 - 26 Mar 2023

Cited by 4 | Viewed by 1966

Abstract

Diabetic retinopathy is one of the most significant retinal diseases that can lead to blindness. As a result, it is critical to receive a prompt diagnosis of the disease. Manual screening can result in misdiagnosis due to human error and limited human capability. [...] Read more.

Diabetic retinopathy is one of the most significant retinal diseases that can lead to blindness. As a result, it is critical to receive a prompt diagnosis of the disease. Manual screening can result in misdiagnosis due to human error and limited human capability. In such cases, using a deep learning-based automated diagnosis of the disease could aid in early detection and treatment. In deep learning-based analysis, the original and segmented blood vessels are typically used for diagnosis. However, it is still unclear which approach is superior. In this study, a comparison of two deep learning approaches (Inception v3 and DenseNet-121) was performed on two different datasets of colored images and segmented images. The study’s findings revealed that the accuracy for original images on both Inception v3 and DenseNet-121 equaled 0.8 or higher, whereas the segmented retinal blood vessels under both approaches provided an accuracy of just greater than 0.6, demonstrating that the segmented vessels do not add much utility to the deep learning-based analysis. The study’s findings show that the original-colored images are more significant in diagnosing retinopathy than the extracted retinal blood vessels. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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15 pages, 3496 KiB

Open AccessArticle

Mathematical Channel Modeling of Electromagnetic Waves in Biological Tissues for Wireless Body Communication

by Intissar Krimi, Sofiane Ben Mbarek, Selma Amara, Fethi Choubani and Yehia Massoud

Electronics 2023, 12(6), 1282; https://doi.org/10.3390/electronics12061282 - 07 Mar 2023

Cited by 4 | Viewed by 1987

Abstract

In the wireless body area network (WBAN), radio propagations from devices that communicate with the human body are very complex and distinctive compared to other environments. As we know, the human body is a lossy channel that significantly attenuates the propagation of electromagnetic [...] Read more.

In the wireless body area network (WBAN), radio propagations from devices that communicate with the human body are very complex and distinctive compared to other environments. As we know, the human body is a lossy channel that significantly attenuates the propagation of electromagnetic waves (EMW). Therefore, channel models are critical in evaluating the communication link. One of the most predominant models is the path loss channel model, which is used to cover a wide range of communication channels and frequency bands in WBAN. This paper investigates the EMW in a human model irradiated by an incident electromagnetic plane wave. A planar multilayer structure is used for modeling human tissue. Moreover, the steady-state electromagnetic distribution is calculated by solving the differential and integral equations (DIE) by using the method of moments (MoM). The obtained results demonstrate the great use of performing a theoretical analysis for path loss (PL) and power loss density (PLD) estimation. The magnitude of the electric field inside muscle tissue at various depths, and with the most important frequencies in medical applications, is evaluated. This investigation provides evidence that the penetration of EMW in biological tissue strongly depends on the frequency and thickness of the tissue involved. Thus, for different examined conditions, an excellent agreement between recent results that were obtained by an analytical method, finite element (FEM), and the proposed MoM method is verified to be valid in this investigation, and it is found that the distribution of the field, PL, and PLD for different communication scenarios is very promising to determine the quality of communication for WBAN technology. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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14 pages, 3207 KiB

Open AccessArticle

Research on sEMG Feature Generation and Classification Performance Based on EBGAN

by Xia Zhang and Mingyu Ma

Electronics 2023, 12(4), 1040; https://doi.org/10.3390/electronics12041040 - 20 Feb 2023

Cited by 2 | Viewed by 1351

Abstract

Surface electromyography signal (sEMG) recognition technology requires a large number of samples to ensure the accuracy of the training results. However, sEMG signals generally have the problems of a small amount of data, complicated acquisition process and large environmental influence, which hinders the [...] Read more.

Surface electromyography signal (sEMG) recognition technology requires a large number of samples to ensure the accuracy of the training results. However, sEMG signals generally have the problems of a small amount of data, complicated acquisition process and large environmental influence, which hinders the improvement of the accuracy of sEMG classification. In order to improve the accuracy of sEMG classification, an sEMG feature generation method based on an energy generative adversarial network (EBGAN) is proposed in this paper for the first time. The energy concept is introduced into the discriminant network instead of the traditional binary judgment, and the distribution of the real EMG dataset is learned and captured by multiple fully connected layers, with similar sEMG data being generated. The experimental results show that, compared with other types of GAN networks, this method achieves a small maximum mean discrepancy in comparison with that of the original data. The experimental results using different typical classification models show that the data augmentation method proposed can effectively improve the classification accuracy of typical classification models, and the accuracy increase range is 1~5%. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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17 pages, 3489 KiB

Open AccessArticle

Complete, Fully Automatic Detection and Classification of Benign and Malignant Breast Tumors Based on CT Images Using Artificial Intelligent and Image Processing

by Chung-Feng Jeffrey Kuo, Hsuan-Yu Chen, Jagadish Barman, Kai-Hsiung Ko and Hsian-He Hsu

J. Clin. Med. 2023, 12(4), 1582; https://doi.org/10.3390/jcm12041582 - 16 Feb 2023

Viewed by 1509

Abstract

Breast cancer is the most common type of cancer in women, and early detection is important to significantly reduce its mortality rate. This study introduces a detection and diagnosis system that automatically detects and classifies breast tumors in CT scan images. First, the [...] Read more.

Breast cancer is the most common type of cancer in women, and early detection is important to significantly reduce its mortality rate. This study introduces a detection and diagnosis system that automatically detects and classifies breast tumors in CT scan images. First, the contours of the chest wall are extracted from computed chest tomography images, and two-dimensional image characteristics and three-dimensional image features, together with the application of active contours without edge and geodesic active contours methods, are used to detect, locate, and circle the tumor. Then, the computer-assisted diagnostic system extracts features, quantifying and classifying benign and malignant breast tumors using a greedy algorithm and a support vector machine. The study used 174 breast tumors for experiment and training and performed cross-validation 10 times (k-fold cross-validation) to evaluate performance of the system. The accuracy, sensitivity, specificity, and positive and negative predictive values of the system were 99.43%, 98.82%, 100%, 100%, and 98.89% respectively. This system supports the rapid extraction and classification of breast tumors as either benign or malignant, helping physicians to improve clinical diagnosis. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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21 pages, 9999 KiB

Open AccessArticle

A Novel Bidirectional-Switched-Capacitor-Based Interlaced DC-DC Converter

by Kuo-Kai Shyu, Yi-Chang Yu, Xin-Lan Lin, Lung-Hao Lee and Po-Lei Lee

Electronics 2023, 12(4), 792; https://doi.org/10.3390/electronics12040792 - 05 Feb 2023

Cited by 1 | Viewed by 1344

Abstract

This study proposes a novel bidirectional-switched-capacitor-based interleaved converter. In view of the shortcomings of the two well-known unidirectional-switched-capacitor-based interleaved converters, this study improves such converters through combining the novel structure of a switched capacitor circuit. The first effort was to overcome the drawback [...] Read more.

This study proposes a novel bidirectional-switched-capacitor-based interleaved converter. In view of the shortcomings of the two well-known unidirectional-switched-capacitor-based interleaved converters, this study improves such converters through combining the novel structure of a switched capacitor circuit. The first effort was to overcome the drawback of the Cockcroft–Walton-based interleaved converter, whose circuit impedance and ripple cause a serious output voltage drop. The second was to solve the Dickson-based interleaved converter with its capacitors subjected to high-voltage stress. The third was to relax the unidirectional boost function of the Cockcroft–Walton- or Dickson-based interleaved converter. This study avoided not only high-circuit impedance and ripple, as in the case of the Cockcroft–Walton converter, but also it had lower component stress than the Dickson converter. In addition, this study redesigned the unidirectional boost function of the Cockcroft–Walton- or Dickson-based interleaved converter, such that the switch-capacitor-based interleaved converters became bidirectional DC-DC converters. Finally, the experimental results are provided to verify the feasibility of the proposed method. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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14 pages, 2975 KiB

Open AccessArticle

The Threat of Adversarial Attack on a COVID-19 CT Image-Based Deep Learning System

by Yang Li and Shaoying Liu

Bioengineering 2023, 10(2), 194; https://doi.org/10.3390/bioengineering10020194 - 02 Feb 2023

Cited by 5 | Viewed by 1696

Abstract

The coronavirus disease 2019 (COVID-19) rapidly spread around the world, and resulted in a global pandemic. Applying artificial intelligence to COVID-19 research can produce very exciting results. However, most research has focused on applying AI techniques in the study of COVID-19, but has [...] Read more.

The coronavirus disease 2019 (COVID-19) rapidly spread around the world, and resulted in a global pandemic. Applying artificial intelligence to COVID-19 research can produce very exciting results. However, most research has focused on applying AI techniques in the study of COVID-19, but has ignored the security and reliability of AI systems. In this paper, we explore adversarial attacks on a deep learning system based on COVID-19 CT images with the aim of helping to address this problem. Firstly, we built a deep learning system that could identify COVID-19 CT images and non-COVID-19 CT images with an average accuracy of 76.27%. Secondly, we attacked the pretrained model with an adversarial attack algorithm, i.e., FGSM, to cause the COVID-19 deep learning system to misclassify the CT images, and the classification accuracy of non-COVID-19 CT images dropped from 80% to 0%. Finally, in response to this attack, we proposed how a more secure and reliable deep learning model based on COVID-19 medical images could be built. This research is based on a COVID-19 CT image recognition system, which studies the security of a COVID-19 CT image-based deep learning system. We hope to draw more researchers’ attention to the security and reliability of medical deep learning systems. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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20 pages, 6037 KiB

Open AccessArticle

Continual Learning of a Transformer-Based Deep Learning Classifier Using an Initial Model from Action Observation EEG Data to Online Motor Imagery Classification

by Po-Lei Lee, Sheng-Hao Chen, Tzu-Chien Chang, Wei-Kung Lee, Hao-Teng Hsu and Hsiao-Huang Chang

Bioengineering 2023, 10(2), 186; https://doi.org/10.3390/bioengineering10020186 - 01 Feb 2023

Cited by 5 | Viewed by 2914

Abstract

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that enables users to communicate with external environments through their minds. However, current MI-BCI systems ask naïve subjects to perform unfamiliar MI tasks with simple textual instruction or a visual/auditory cue. [...] Read more.

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that enables users to communicate with external environments through their minds. However, current MI-BCI systems ask naïve subjects to perform unfamiliar MI tasks with simple textual instruction or a visual/auditory cue. The unclear instruction for MI execution not only results in large inter-subject variability in the measured EEG patterns but also causes the difficulty of grouping cross-subject data for big-data training. In this study, we designed an BCI training method in a virtual reality (VR) environment. Subjects wore a head-mounted device (HMD) and executed action observation (AO) concurrently with MI (i.e., AO + MI) in VR environments. EEG signals recorded in AO + MI task were used to train an initial model, and the initial model was continually improved by the provision of EEG data in the following BCI training sessions. We recruited five healthy subjects, and each subject was requested to participate in three kinds of tasks, including an AO + MI task, an MI task, and the task of MI with visual feedback (MI-FB) three times. This study adopted a transformer- based spatial-temporal network (TSTN) to decode the user’s MI intentions. In contrast to other convolutional neural network (CNN) or recurrent neural network (RNN) approaches, the TSTN extracts spatial and temporal features, and applies attention mechanisms along spatial and temporal dimensions to perceive the global dependencies. The mean detection accuracies of TSTN were 0.63, 0.68, 0.75, and 0.77 in the MI, first MI-FB, second MI-FB, and third MI-FB sessions, respectively. This study demonstrated the AO + MI gave an easier way for subjects to conform their imagery actions, and the BCI performance was improved with the continual learning of the MI-FB training process. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 7286 KiB

Open AccessArticle

Emotional State Classification from MUSIC-Based Features of Multichannel EEG Signals

by Sakib Abrar Hossain, Md. Asadur Rahman, Amitabha Chakrabarty, Mohd Abdur Rashid, Anna Kuwana and Haruo Kobayashi

Bioengineering 2023, 10(1), 99; https://doi.org/10.3390/bioengineering10010099 - 11 Jan 2023

Cited by 7 | Viewed by 2185

Abstract

Electroencephalogram (EEG)-based emotion recognition is a computationally challenging issue in the field of medical data science that has interesting applications in cognitive state disclosure. Generally, EEG signals are classified from frequency-based features that are often extracted using non-parametric models such as Welch’s power [...] Read more.

Electroencephalogram (EEG)-based emotion recognition is a computationally challenging issue in the field of medical data science that has interesting applications in cognitive state disclosure. Generally, EEG signals are classified from frequency-based features that are often extracted using non-parametric models such as Welch’s power spectral density (PSD). These non-parametric methods are not computationally sound due to having complexity and extended run time. The main purpose of this work is to apply the multiple signal classification (MUSIC) model, a parametric-based frequency-spectrum-estimation technique to extract features from multichannel EEG signals for emotional state classification from the SEED dataset. The main challenge of using MUSIC in EEG feature extraction is to tune its parameters for getting the discriminative features from different classes, which is a significant contribution of this work. Another contribution is to show some flaws of this dataset for the first time that contributed to achieving high classification accuracy in previous research works. This work used MUSIC features to classify three emotional states and achieve 97% accuracy on average using an artificial neural network. The proposed MUSIC model optimizes a 95–96% run time compared with the conventional classical non-parametric technique (Welch’s PSD) for feature extraction. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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22 pages, 4424 KiB

Open AccessArticle

Long-Term Care Services and Insurance System in China: An Evolutionary Game Analysis

by Han Hu and Zhao Zhang

Sustainability 2023, 15(1), 610; https://doi.org/10.3390/su15010610 - 29 Dec 2022

Cited by 1 | Viewed by 1671

Abstract

The study creates a simplified game model to propose a suitable policy to foster a win-win scenario between care institutions and families of the disabled elderly, and to give a reference basis for enhancing the welfare level of the disabled elderly as well [...] Read more.

The study creates a simplified game model to propose a suitable policy to foster a win-win scenario between care institutions and families of the disabled elderly, and to give a reference basis for enhancing the welfare level of the disabled elderly as well as the commercial performance of care institutions. First, we study and synthesise the experiences of contemporary Chinese long-term care pilot cities to offer data for subsequent numerical analysis; second, we create an evolutionary game model to depict the conflicts and evolving patterns of conflicts between the disabled elderly and care facilities in China; and third, we use numerical analysis to investigate the effects of internal factors (cost of care, price of care) and policy assistance (government subsidies). Finally, we utilise numerical analysis to investigate how internal factors (cost of care, price of care) and policy assistance (government subsidy) affect the combination of solutions. The study reveals that (1) the two-sided strategic choices of care institutions and disabled families make the game unstable. (2) The government can influence the choice of care institutions and disabled families by tax rates and subsidies, implying a stability policy. (3) The presence of an evolutionary stabilization strategy implies that government control may have a desirable limit. When government engagement in this market is limited, “professional care, home care” finally becomes the evolutionary stability method. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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14 pages, 4601 KiB

Open AccessArticle

Open-Source Culture Platform for Multi-Cell Type Study with Integrated Pneumatic Stimulation

by Nicolò Cacocciola, Simone Luigi Marasso, Giancarlo Canavese, Matteo Cocuzza, Candido Fabrizio Pirri and Francesca Frascella

Electronics 2023, 12(1), 73; https://doi.org/10.3390/electronics12010073 - 25 Dec 2022

Viewed by 1318

Abstract

Mechanical forces can influence the structure and development of healthy and cancerous cells and tissue microenvironments, acting on their physical shape and promoting non-genetic alterations during growth. For this reason, it is interesting to investigate the role of dynamic hydrostatic compression on such [...] Read more.

Mechanical forces can influence the structure and development of healthy and cancerous cells and tissue microenvironments, acting on their physical shape and promoting non-genetic alterations during growth. For this reason, it is interesting to investigate the role of dynamic hydrostatic compression on such cultures, to assess the role of such stimuli on key parameters, such as cell differentiation, cell stiffness and cytoskeleton rearrangements. In this work, we present a versatile Arduino-based pneumatic system for the stimulation of a cell culture performed in a standard multi-well plate, designed to work inside a CO₂ incubator. The system is capable of modifying the hydrostatic pressure inside a dedicated culture chamber following the desired pattern, and, thus, providing a mechanical hydrostatic stimulus to a cell culture growing inside it. In the present work, a human respiration-like compression pattern was used, to mimic the mechanical stress conditions inside the human lung alveoli, and make the platform compatible with the development of lung tissues and organoids. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 3568 KiB

Open AccessArticle

Classification of Pulmonary Damage Stages Caused by COVID-19 Disease from CT Scans via Transfer Learning

by Irina Andra Tache, Dimitrios Glotsos and Silviu Marcel Stanciu

Bioengineering 2023, 10(1), 6; https://doi.org/10.3390/bioengineering10010006 - 20 Dec 2022

Viewed by 2090

Abstract

The COVID-19 pandemic has produced social and economic changes that are still affecting our lives. The coronavirus is proinflammatory, it is replicating, and it is quickly spreading. The most affected organ is the lung, and the evolution of the disease can degenerate very [...] Read more.

The COVID-19 pandemic has produced social and economic changes that are still affecting our lives. The coronavirus is proinflammatory, it is replicating, and it is quickly spreading. The most affected organ is the lung, and the evolution of the disease can degenerate very rapidly from the early phase, also known as mild to moderate and even severe stages, where the percentage of recovered patients is very low. Therefore, a fast and automatic method to detect the disease stages for patients who underwent a computer tomography investigation can improve the clinical protocol. Transfer learning is used do tackle this issue, mainly by decreasing the computational time. The dataset is composed of images from public databases from 118 patients and new data from 55 patients collected during the COVID-19 spread in Romania in the spring of 2020. Even if the disease detection by the computerized tomography scans was studied using deep learning algorithms, to our knowledge, there are no studies related to the multiclass classification of the images into pulmonary damage stages. This could be helpful for physicians to automatically establish the disease severity and decide on the proper treatment for patients and any special surveillance, if needed. An evaluation study was completed by considering six different pre-trained CNNs. The results are encouraging, assuring an accuracy of around 87%. The clinical impact is still huge, even if the disease spread and severity are currently diminished. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 1077 KiB

Open AccessArticle

Eight-Element Communication Model for Internet Health Rumors: A New Exploration of Lasswell’s “5W Communication Model”

by Haibin Wei, Jianyang Chen, Xinyan Gan and Zhenyi Liang

Healthcare 2022, 10(12), 2507; https://doi.org/10.3390/healthcare10122507 - 11 Dec 2022

Cited by 2 | Viewed by 2827

Abstract

(1) Background: Rumors are a special type of information. Based on the classic theory of the communication of information, the “5W” communication model, this article aims to build a new model and thus explains the generation and communication of Internet health rumors. (2) [...] Read more.

(1) Background: Rumors are a special type of information. Based on the classic theory of the communication of information, the “5W” communication model, this article aims to build a new model and thus explains the generation and communication of Internet health rumors. (2) Methods: The authors selected 50 Internet health rumors, which were widely spread in widely used websites and social media in China, then grounded theory is used to perform the qualitative analysis of the Internet health rumors. (3) Results: Three Core Concepts are abstracted after qualitative analysis. An internal dynamic mutual assistance mechanism of the communication of rumors is built and illustrated. Based on Lasswell’s “5W” communication model, the authors develop an eight-element communication model for Internet health rumors to illustrate the generation and communication of Internet health rumors. (4) Conclusions: By removing one or several elements of this new model, the chain of the communication of Internet health rumors could be cut off, which is valuable information for the government or websites to manage communication of Internet health rumors. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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16 pages, 1921 KiB

Open AccessArticle

A Deep Learning Approach for Detecting Stroke from Brain CT Images Using OzNet

by Oznur Ozaltin, Orhan Coskun, Ozgur Yeniay and Abdulhamit Subasi

Bioengineering 2022, 9(12), 783; https://doi.org/10.3390/bioengineering9120783 - 08 Dec 2022

Cited by 7 | Viewed by 2780

Abstract

A brain stroke is a life-threatening medical disorder caused by the inadequate blood supply to the brain. After the stroke, the damaged area of the brain will not operate normally. As a result, early detection is crucial for more effective therapy. Computed tomography [...] Read more.

A brain stroke is a life-threatening medical disorder caused by the inadequate blood supply to the brain. After the stroke, the damaged area of the brain will not operate normally. As a result, early detection is crucial for more effective therapy. Computed tomography (CT) images supply a rapid diagnosis of brain stroke. However, while doctors are analyzing each brain CT image, time is running fast. This circumstance may lead to result in a delay in treatment and making errors. Therefore, we targeted the utilization of an efficient artificial intelligence algorithm in stroke detection. In this paper, we designed hybrid algorithms that include a new convolution neural networks (CNN) architecture called OzNet and various machine learning algorithms for binary classification of real brain stroke CT images. When we classified the dataset with OzNet, we acquired successful performance. However, for this target, we combined it with a minimum Redundancy Maximum Relevance (mRMR) method and Decision Tree (DT), k-Nearest Neighbors (kNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), and Support Vector Machines (SVM). In addition, 4096 significant features were obtained from the fully connected layer of OzNet, and we reduced the dimension of features from 4096 to 250 using the mRMR method. Finally, we utilized these machine learning algorithms to classify important features. As a result, OzNet-mRMR-NB was an excellent hybrid algorithm and achieved an accuracy of 98.42% and AUC of 0.99 to detect stroke from brain CT images. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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15 pages, 6812 KiB

Open AccessArticle

An Optimization-Based Technology Applied for Face Skin Symptom Detection

by Yuan-Hsun Liao, Po-Chun Chang, Chun-Cheng Wang and Hsiao-Hui Li

Healthcare 2022, 10(12), 2396; https://doi.org/10.3390/healthcare10122396 - 29 Nov 2022

Cited by 5 | Viewed by 1689

Abstract

Face recognition segmentation is very important for symptom detection, especially in the case of complex image backgrounds or noise. The complexity of the photo background, the clarity of the facial expressions, or the interference of other people’s faces can increase the difficulty of [...] Read more.

Face recognition segmentation is very important for symptom detection, especially in the case of complex image backgrounds or noise. The complexity of the photo background, the clarity of the facial expressions, or the interference of other people’s faces can increase the difficulty of detection. Therefore, in this paper, we have proposed a method to combine mask region-based convolutional neural networks (Mask R-CNN) with you only look once version 4 (YOLOv4) to identify facial symptoms by this new method. We use the face image dataset from the public image databases DermNet and Freepic as the training source for the model. Face segmentation was first applied with Mask R-CNN. Then the images were imported into ResNet-101, and the facial features were fused with region of interest (RoI) in the feature pyramid networks (FPN) structures. After removing the non-face features and noise, the face region has been accurately obtained. Next, the recognized face area and RoI data were used to identify facial symptoms (acne, freckle, and wrinkles) with YOLOv4. Finally, we use Mask R-CNN, and you only look once version 3 (YOLOv3) and YOLOv4 are matched to perform the performance analysis. Although, the facial images with symptoms are relatively few. We still use a limited amount of data to train the model. The experimental results show that our proposed method still achieves 57.73%, 60.38%, and 59.75% of mean average precision (mAP) for different amounts of data. Compared with other methods, the mAP was more than about 3%. Consequently, using the method proposed in this paper, facial symptoms can be effectively and accurately identified. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 4563 KiB

Open AccessArticle

Health Information System and Health Care Applications Performance in the Healthcare Arena: A Bibliometric Analysis

by Ayogeboh Epizitone, Smangele Pretty Moyane and Israel Edem Agbehadji

Healthcare 2022, 10(11), 2273; https://doi.org/10.3390/healthcare10112273 - 12 Nov 2022

Cited by 6 | Viewed by 4222

Abstract

There have been several studies centred on health information systems with many insights provided to enhance health care applications globally. These studies have provided theoretical schemes for fortifying the enactment and utilisation of the Health Information System (HIS). In addition, these research studies [...] Read more.

There have been several studies centred on health information systems with many insights provided to enhance health care applications globally. These studies have provided theoretical schemes for fortifying the enactment and utilisation of the Health Information System (HIS). In addition, these research studies contribute greatly to the development of HIS in alignment with major stakeholders such as health practitioners and recipients of health care. Conversely, there has been trepidation about HIS’ sustainability and resilience for healthcare applications in the era of digitalization and globalization. Hence, this paper investigates research on HIS with a primary focus on health care applications to ascertain its sustainability and resilience amidst the transformation of the global healthcare space. Therefore, using a bibliometric approach, this paper measures the performance of health information systems and healthcare for health care applications using bibliometric data from the web of science database. The findings reveal solid evidence of the constructive transformation of health information systems and health care applications in the healthcare arena, providing ample evidence of the adaptation of HIS and health care applications within the healthcare arena to the fourth industrial revolution and, additionally, revealing the resilient alignment of health care applications and health information systems. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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11 pages, 3776 KiB

Open AccessArticle

Artificial Neural Network-Based Abnormal Gait Pattern Classification Using Smart Shoes with a Gyro Sensor

by Kimin Jeong and Kyung-Chang Lee

Electronics 2022, 11(21), 3614; https://doi.org/10.3390/electronics11213614 - 05 Nov 2022

Cited by 2 | Viewed by 2625

Abstract

Recently, as a wearable-sensor-based approach, a smart insole device has been used to analyze gait patterns. By adding a small low-power sensor and an IoT device to the smart insole, it is possible to monitor human activity, gait pattern, and plantar pressure in [...] Read more.

Recently, as a wearable-sensor-based approach, a smart insole device has been used to analyze gait patterns. By adding a small low-power sensor and an IoT device to the smart insole, it is possible to monitor human activity, gait pattern, and plantar pressure in real time and evaluate exercise function in an uncontrolled environment. The sensor-embedded smart soles prevent any feeling of heterogeneity, and WiFi technology allows acquisition of data even when the user is not in a laboratory environment. In this study, we designed a sensor data-collection module that uses a miniaturized low-power accelerometer and gyro sensor, and then embedded it in a shoe to collect gait data. The gait data are sent to the gait-pattern classification module via a Wi-Fi network, and the ANN model classifies the gait into gait patterns such as in-toeing gait, normal gait, or out-toeing gait. Finally, the feasibility of our model was confirmed through several experiments. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 2736 KiB

Open AccessArticle

Efficient and Economic Heparin Recovery from Porcine Intestinal Mucosa Using Quaternary Ammonium-Functionalized Silica Gel

by Mahmood Karimi Abdolmaleki, Anushree Das, Devang P. Khambhati, Ali Shafiee, Kayli Dimas, Carlo Alberto Velazquez, Seyed Mohammad Davachi and Sima Choubtarash Abardeh

Bioengineering 2022, 9(11), 606; https://doi.org/10.3390/bioengineering9110606 - 23 Oct 2022

Cited by 2 | Viewed by 2465

Abstract

Heparin, usually isolated from porcine intestinal mucosa, is an active pharmaceutical ingredient of great material value. Traditionally, diverse types of commercial resins were employed as an adsorbent for heparin retrieval from biological samples. However, more recent years have encouraged the advent of new [...] Read more.

Heparin, usually isolated from porcine intestinal mucosa, is an active pharmaceutical ingredient of great material value. Traditionally, diverse types of commercial resins were employed as an adsorbent for heparin retrieval from biological samples. However, more recent years have encouraged the advent of new cost-effective adsorbents to achieve enhanced heparin retrieval. Inexpensive cationic ammonium-functionalized silica gels, monodispersed with larger surface area, porosity, and higher thermal stability, were chosen to evaluate the heparin recovery yield from porcine intestinal mucosa. We demonstrated that higher positively charged and less bulky quaternary modified silica gel (e.g., QDASi) could adsorb ~28% (14.7 mg g⁻¹) heparin from the real samples. In addition, we also determined suitable surface conditions for the heparin molecule adsorption by mechanistic studies and optimized different variables, such as pH, temperature, etc., to improve the heparin adsorption. This is going to be the first reported study on the usage of quaternary amine-functionalized silica gel for HEP uptake. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 2038 KiB

Open AccessArticle

Ultrafast PCR Detection of COVID-19 by Using a Microfluidic Chip-Based System

by Xiaojing Chen, Yiteng Liu, Xuan Zhan, Yibo Gao, Zhongyi Sun, Weijia Wen and Weidong Zheng

Bioengineering 2022, 9(10), 548; https://doi.org/10.3390/bioengineering9100548 - 13 Oct 2022

Cited by 8 | Viewed by 2734

Abstract

With the evolution of the pandemic caused by the Coronavirus disease of 2019 (COVID-19), reverse transcriptase-polymerase chain reactions (RT-PCR) have invariably been a golden standard in clinical diagnosis. Nevertheless, the traditional polymerase chain reaction (PCR) is not feasible for field application due to [...] Read more.

With the evolution of the pandemic caused by the Coronavirus disease of 2019 (COVID-19), reverse transcriptase-polymerase chain reactions (RT-PCR) have invariably been a golden standard in clinical diagnosis. Nevertheless, the traditional polymerase chain reaction (PCR) is not feasible for field application due to its drawbacks, such as time-consuming and laboratory-based dependence. To overcome these challenges, a microchip-based ultrafast PCR system called SWM-02 was proposed to make PCR assay in a rapid, portable, and low-cost strategy. This novel platform can perform 6-sample detection per run using multiple fluorescent channels and complete an ultrafast COVID-19 RT-PCR test within 40 min. Here, we evaluated the performance of the microdevice using the gradient-diluted COVID-19 reference samples and commercial PCR kit and determined its limit-of-detection (LoD) as 500 copies/mL, whose variation coefficients for the nucleocapsid (N) gene and open reading frame 1 ab region (ORF1ab) gene are 1.427% and 0.7872%, respectively. The system also revealed an excellent linear correlation between cycle threshold (Ct) values and dilution factors (R² > 0.99). Additionally, we successfully detected the target RNAs and internal gene in the clinical samples by fast PCR, which shows strong consistency with conventional PCR protocol. Hence, with compact dimension, user-friendly design, and fast processing time, SWM-02 has the capability of offering timely and sensitive on-site molecular diagnosis for prevention and control of pathogen transmission. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 5678 KiB

Open AccessArticle

Augmented Reality Surgical Navigation System for External Ventricular Drain

by Shin-Yan Chiou, Zhi-Yue Zhang, Hao-Li Liu, Jiun-Lin Yan, Kuo-Chen Wei and Pin-Yuan Chen

Healthcare 2022, 10(10), 1815; https://doi.org/10.3390/healthcare10101815 - 21 Sep 2022

Cited by 7 | Viewed by 2086

Abstract

Augmented reality surgery systems are playing an increasing role in the operating room, but applying such systems to neurosurgery presents particular challenges. In addition to using augmented reality technology to display the position of the surgical target position in 3D in real time, [...] Read more.

Augmented reality surgery systems are playing an increasing role in the operating room, but applying such systems to neurosurgery presents particular challenges. In addition to using augmented reality technology to display the position of the surgical target position in 3D in real time, the application must also display the scalpel entry point and scalpel orientation, with accurate superposition on the patient. To improve the intuitiveness, efficiency, and accuracy of extra-ventricular drain surgery, this paper proposes an augmented reality surgical navigation system which accurately superimposes the surgical target position, scalpel entry point, and scalpel direction on a patient’s head and displays this data on a tablet. The accuracy of the optical measurement system (NDI Polaris Vicra) was first independently tested, and then complemented by the design of functions to help the surgeon quickly identify the surgical target position and determine the preferred entry point. A tablet PC was used to display the superimposed images of the surgical target, entry point, and scalpel on top of the patient, allowing for correct scalpel orientation. Digital imaging and communications in medicine (DICOM) results for the patient’s computed tomography were used to create a phantom and its associated AR model. This model was then imported into the application, which was then executed on the tablet. In the preoperative phase, the technician first spent 5–7 min to superimpose the virtual image of the head and the scalpel. The surgeon then took 2 min to identify the intended target position and entry point position on the tablet, which then dynamically displayed the superimposed image of the head, target position, entry point position, and scalpel (including the scalpel tip and scalpel orientation). Multiple experiments were successfully conducted on the phantom, along with six practical trials of clinical neurosurgical EVD. In the 2D-plane-superposition model, the optical measurement system (NDI Polaris Vicra) provided highly accurate visualization (2.01 ± 1.12 mm). In hospital-based clinical trials, the average technician preparation time was 6 min, while the surgeon required an average of 3.5 min to set the target and entry-point positions and accurately overlay the orientation with an NDI surgical stick. In the preparation phase, the average time required for the DICOM-formatted image processing and program import was 120 ± 30 min. The accuracy of the designed augmented reality optical surgical navigation system met clinical requirements, and can provide a visual and intuitive guide for neurosurgeons. The surgeon can use the tablet application to obtain real-time DICOM-formatted images of the patient, change the position of the surgical entry point, and instantly obtain an updated surgical path and surgical angle. The proposed design can be used as the basis for various augmented reality brain surgery navigation systems in the future. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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17 pages, 786 KiB

Open AccessArticle

The Determinants of ESG for Community LOHASism Sustainable Development Strategy

by Chih-Cheng Huang, Yung-Kuan Chan and Ming Yuan Hsieh

Sustainability 2022, 14(18), 11429; https://doi.org/10.3390/su141811429 - 12 Sep 2022

Cited by 14 | Viewed by 2810

Abstract

Owing to the increasing trends of the LOHAS lifestyle (LOHASism) adopted by a majority of Taiwanese communities, most community development associations have begun to explore the most effective LOHASism sustainable development strategies for advancing a high-quality lifestyle for these extensive community residents. Hence, [...] Read more.

Owing to the increasing trends of the LOHAS lifestyle (LOHASism) adopted by a majority of Taiwanese communities, most community development associations have begun to explore the most effective LOHASism sustainable development strategies for advancing a high-quality lifestyle for these extensive community residents. Hence, this research cross-employed the three core principles in LOHASism, three analytical dimensions (environment, society and governance) of Environment Society and Governance (ESG) and 17 evaluated sustainable indexes of the Sustainable Development Goals (SDGs) in order to effectively induce the determinants of ESG for a community LOHASism sustainable development strategy. Significantly, the three most valuable conclusions and contributive findings are: (1) the main research question has been comprehensively solved through interdisciplinary analyses of the consolidation among the three principles (Dogood, Feelgood, Lookgood) of LOHASism, three dimensions of ESG and 17 evaluated sustainable indexes of the SDGs; (2) the highest scale of standardized comparative weights was located in the Positively Promoting Community Development Sustainability (PPCDS) of 0.7194, which means LOHASism, ESG and SDGs did positively promote community sustainable development in order and empirically achieved the brief research goal; and (3) industry, innovation and infrastructure (III), reduced inequality and responsible consumption and production in the governance of the EGS into LOHASism were the highest three weighted scales in the Positively Promoting Community Development Sustainability (PPCDS). This means that most community’s residents expect the advancement of innovation and infrastructure (III), the improvement of reduced inequality and the increment of responsible consumption and production to be the top three critical sustainable development strategies in their community development governance in order to advance the most residents to be good-looking and have body health. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 3317 KiB

Open AccessArticle

A Device Designed to Improve Care and Wayfinding Assistance for Elders with Dementia

by Winger Seiwo Tseng and Jonny Fang

Sustainability 2022, 14(17), 11076; https://doi.org/10.3390/su141711076 - 05 Sep 2022

Cited by 2 | Viewed by 1798

Abstract

With an aging population and the rapid increase in the rate of dementia, the care of patients is a significant problem for caregivers and family members at home. Patients’ spatial and environmental cognitive impairments require caregivers to pay attention to their walking routes, [...] Read more.

With an aging population and the rapid increase in the rate of dementia, the care of patients is a significant problem for caregivers and family members at home. Patients’ spatial and environmental cognitive impairments require caregivers to pay attention to their walking routes, walking safety, and avoiding dangerous areas. With this in mind, this study developed the Dementia Care Management and Mentoring Guarantee System (DECMGSS) to examine the accuracy and efficiency of patient wayfinding, and to reduce the stress on institutional caregivers through a wayfinding task and a caregiver stress scale (CSS). The results showed that the mean time spent with the DECMGSS on 10 subjects with mild to moderate dementia was significantly less than that without the device (t = −2.930, p = 0.017), and the number of errors was also less but not significantly different. In addition, the DECMGSS did significantly reduce the caregiver stress load. Twenty institutional caregivers were divided into experimental and control groups. There was no significant difference in the stress load scores of the control group before and after the test. However, a significant mean difference was found between the pre-test and post-test scores of the experimental group (t = 3.315, p < 0.009). DECMGSS’s intervention significantly reduced the caregiver’s personal anxiety and stress in caregiving and the patient’s time dependence on the caregiver. Although this product is primarily used for patients in the Care Center, it can also be used in other home care settings. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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8 pages, 222 KiB

Open AccessArticle

Enforcement of the Use of Digital Contact-Tracing Apps in a Common Law Jurisdiction

by Tsz Ho Kwan

Healthcare 2022, 10(9), 1613; https://doi.org/10.3390/healthcare10091613 - 25 Aug 2022

Cited by 2 | Viewed by 1734

Abstract

Digital contact-tracing systems have been widely implemented worldwide with different system designs and implementation policies for the purpose of tracking potentially exposed individuals. The use of a digital contact-tracing app in Hong Kong has been mandated for visiting certain premises by legislations. This [...] Read more.

Digital contact-tracing systems have been widely implemented worldwide with different system designs and implementation policies for the purpose of tracking potentially exposed individuals. The use of a digital contact-tracing app in Hong Kong has been mandated for visiting certain premises by legislations. This paper reviewed the regulations promulgated specifically for the prevention and control of COVID-19 and identified those associated with the digital contact-tracing system. A comprehensive search in newspaper databases was performed to explore the enforcement of the mandated use of the digital contact-tracing app. The three facets of regulations in relation to digital contact tracing were examined: duty to disclose information, requirements and directions to businesses, and compulsory testing. The use of digital contact-tracing data for non-public health purposes was also reported. Our analyses showed that prosecution of non-use or the use of fraudulent digital contact-tracing apps was not limited to COVID-19-specific legislations. The flexible approach ensured the enforcement of the use of the digital contact-tracing app, but the judiciary’s test must be passed in future cases. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

10 pages, 1753 KiB

Open AccessCommunication

Robot-Assisted Radiofrequency Ablation Combined with Thermodynamic Simulation for Epilepsy Reoperations

by Yu-Chi Wang, Mei-Yun Cheng, Po-Cheng Hung, Cheng-Yen Kuo, Hsiang-Yao Hsieh, Kuang-Lin Lin, Po-Hsun Tu, Chieh-Tsai Wu, Peng-Wei Hsu, Kuo-Chen Wei and Chi-Cheng Chuang

J. Clin. Med. 2022, 11(16), 4804; https://doi.org/10.3390/jcm11164804 - 17 Aug 2022

Cited by 3 | Viewed by 1752

Abstract

Repeat craniotomies to treat recurrent seizures may be difficult, and minimally invasive radiofrequency ablation is an alternative therapy. On the basis of this procedure, we aimed to develop a more reliable methodology which is helpful for institutions where real-time image monitoring or electrophysiologic [...] Read more.

Repeat craniotomies to treat recurrent seizures may be difficult, and minimally invasive radiofrequency ablation is an alternative therapy. On the basis of this procedure, we aimed to develop a more reliable methodology which is helpful for institutions where real-time image monitoring or electrophysiologic guidance during ablation are not available. We used simulation combined with a robot-assisted radiofrequency ablation (S-RARFA) protocol to plan and execute brain epileptic tissue lesioning. Trajectories of electrodes were planned on the robot system, and time-dependent thermodynamics was simulated with radiofrequency parameters. Thermal gradient and margin were displayed on a computer to calculate ablation volume with a mathematic equation. Actual volume was measured on images after the ablation. This small series included one pediatric and two adult patients. The remnant hippocampus, corpus callosum, and irritative zone around arteriovenous malformation nidus were all treated with S-RARFA. The mean error percentage of the volume ablated between preoperative simulation and postoperative measurement was 2.4 ± 0.7%. No complications or newly developed neurologic deficits presented postoperatively, and the patients had little postoperative pain and short hospital stays. In this pilot study, we preliminarily verified the feasibility and safety of this novel protocol. As an alternative to traditional surgeries or real-time monitoring, S-RARFA served as successful seizure reoperation with high accuracy, minimal collateral damage, and good seizure control. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 2375 KiB

Open AccessArticle

Inherent Safety Analysis and Sustainability Evaluation of a Vaccine Production Topology in North-East Colombia

by Ángel Darío González-Delgado, Janet B. García-Martínez and Andrés F. Barajas-Solano

Sustainability 2022, 14(16), 9985; https://doi.org/10.3390/su14169985 - 12 Aug 2022

Cited by 3 | Viewed by 1465

Abstract

Influenza is a respiratory disease that may cause severe consequences to human health. Influenza caused between 99,000 and 200,000 deaths worldwide in 2019. Studies have reported the presence of this virus in Santander, Colombia, a region with a high humanitarian flow. An influenza [...] Read more.

Influenza is a respiratory disease that may cause severe consequences to human health. Influenza caused between 99,000 and 200,000 deaths worldwide in 2019. Studies have reported the presence of this virus in Santander, Colombia, a region with a high humanitarian flow. An influenza vaccine production plant topology has been proposed previously. Nevertheless, the inherent safety and sustainably behavior of this topology is unknown. Process safety plays a crucial role in the evaluation of emerging technologies since it allows the identification of potential risks. Moreover, the current sustainability policies enforce the assessment of processes considering economic, social, and environmental aspects. For this reason, a safety and sustainability evaluation of a vaccine production topology is performed in this work. The inherent safety index (ISI) methodology was implemented to analyze the process. The sustainability evaluation was performed using the sustainability weighted return on investment metric (SWROIM), in which return on investment (ROI), output potential environmental impact (PEI output), total safety inherent index (ITI), and exergy efficiency were considered. The results showed that influenza vaccine production is inherently safe since the total inherent safety index was 11. The destroyed exergy was 378.69 MJ/h, the return on investment was 86%, and the SWROIM was estimated at 81%, which means slightly negative impacts on sustainability. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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22 pages, 1503 KiB

Open AccessArticle

An Investigation into the Perspectives of Elementary Pre-Service Teachers on Sustainable Development

by Lam-Huu-Phuoc Nguyen, Nguyen-Bich-Thy Bui, Thi-Ngoc-Cam Nguyen and Chin-Fei Huang

Sustainability 2022, 14(16), 9943; https://doi.org/10.3390/su14169943 - 11 Aug 2022

Cited by 5 | Viewed by 2203

Abstract

Teachers in elementary schools play a crucial role in educating children about sustainable development. Therefore, the concept of sustainable development is essential for elementary pre-service teachers to be ready for their future careers. This study used the sequential mixed methods design to investigate [...] Read more.

Teachers in elementary schools play a crucial role in educating children about sustainable development. Therefore, the concept of sustainable development is essential for elementary pre-service teachers to be ready for their future careers. This study used the sequential mixed methods design to investigate the relationship between the sustainable development perspectives of elementary pre-service teachers in Southern Vietnam and the current teacher training curriculum. The EDINSOST sustainability questionnaire was distributed to 392 participants in order to measure four dimensions of sustainable development: critical contextualization of knowledge, sustainable use of resources, participation in community processes, and ethics. A set of six interview questions was conducted with eight participants, focused on their understandings of sustainable development and the evaluation of the curriculum on sustainable development. Quantitative findings revealed that elementary pre-service teachers rate moderately on all dimensions; however, the knowledge is slightly higher than the behavior. Moreover, there were variations in perspectives based on pre-service teachers’ grade level and gender. Qualitative findings suggested the lack of sustainable development perspectives amongst pre-service teachers and the gaps in the teacher training curriculums regarding sustainable development. Finally, detailed discussions regarding the implementation of sustainable development in the training curriculum were provided. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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15 pages, 2174 KiB

Open AccessArticle

Design and Implementation of a Comprehensive AI Dashboard for Real-Time Prediction of Adverse Prognosis of ED Patients

by Wei-Chun Tsai, Chung-Feng Liu, Hung-Jung Lin, Chien-Chin Hsu, Yu-Shan Ma, Chia-Jung Chen, Chien-Cheng Huang and Chia-Chun Chen

Healthcare 2022, 10(8), 1498; https://doi.org/10.3390/healthcare10081498 - 09 Aug 2022

Cited by 7 | Viewed by 2641

Abstract

The emergency department (ED) is at the forefront of medical care, and the medical team needs to make outright judgments and treatment decisions under time constraints. Thus, knowing how to make personalized and precise predictions is a very challenging task. With the advancement [...] Read more.

The emergency department (ED) is at the forefront of medical care, and the medical team needs to make outright judgments and treatment decisions under time constraints. Thus, knowing how to make personalized and precise predictions is a very challenging task. With the advancement of artificial intelligence (AI) technology, Chi Mei Medical Center (CMMC) adopted AI, the Internet of Things (IoT), and interaction technologies to establish diverse prognosis prediction models for eight diseases based on the ED electronic medical records of three branch hospitals. CMMC integrated these predictive models to form a digital AI dashboard, showing the risk status of all ED patients diagnosed with any of these eight diseases. This study first explored the methodology of CMMC’s AI development and proposed a four-tier AI dashboard architecture for ED implementation. The AI dashboard’s ease of use, usefulness, and acceptance was also strongly affirmed by the ED medical staff. The ED AI dashboard is an effective tool in the implementation of real-time risk monitoring of patients in the ED and could improve the quality of care as a part of best practice. Based on the results of this study, it is suggested that healthcare institutions thoughtfully consider tailoring their ED dashboard designs to adapt to their unique workflows and environments. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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21 pages, 1192 KiB

Open AccessArticle

Making Hospitals Sustainable: Towards Greener, Fairer and More Prosperous Services

by Karine Borges de Oliveira and Otávio José de Oliveira

Sustainability 2022, 14(15), 9730; https://doi.org/10.3390/su14159730 - 08 Aug 2022

Cited by 7 | Viewed by 4312

Abstract

The growing demand for hospital services and the pressure to incorporate sustainable strategies into hospital management have led hospitals to rethink their business model and seek new ways to manage their operations. Corporate sustainability is an important way to make hospitals more sustainable [...] Read more.

The growing demand for hospital services and the pressure to incorporate sustainable strategies into hospital management have led hospitals to rethink their business model and seek new ways to manage their operations. Corporate sustainability is an important way to make hospitals more sustainable and competitive. Therefore, this paper proposes a framework that contains the drivers for the management of sustainability in hospitals (SH), developed through the content analysis method. As a result, this study proposes five drivers: toward the circular economy; making sustainable buildings; adopting knowledge management and organizational culture; employing management systems, tools, and methods; and applying technological innovations. This framework contributes in a managerial way to helping managers of hospitals in managing sustainability; making their businesses fairer, greener, and more prosperous; and fulfilling their commitments to the well-being of their employees and society, providing a basis for moving toward the premises of the United Nation’s 2030 Agenda. This study also scientifically contributes to the academic maturation of the topic by systematizing elements and adding insights to the state of the art on SH. It is recommended that future studies add new elements to the drivers or even propose new drivers for the continuous scientific advancement of this topic. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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19 pages, 6639 KiB

Open AccessArticle

Simultaneous Maturation of Single Chain Antibody Stability and Affinity by CHO Cell Display

by Ruiqi Luo, Baole Qu, Lili An, Yun Zhao, Yang Cao, Peng Ren and Haiying Hang

Bioengineering 2022, 9(8), 360; https://doi.org/10.3390/bioengineering9080360 - 02 Aug 2022

Cited by 2 | Viewed by 2089

Abstract

Antibody stability and affinity are two important features of its applications in therapy and diagnosis. Antibody display technologies such as yeast and bacterial displays have been successfully used for improving both affinity and stability. Although mammalian cell display has also been utilized for [...] Read more.

Antibody stability and affinity are two important features of its applications in therapy and diagnosis. Antibody display technologies such as yeast and bacterial displays have been successfully used for improving both affinity and stability. Although mammalian cell display has also been utilized for maturing antibody affinity, it has not been applied for improving antibody stability. Previously, we developed a Chinese hamster ovary (CHO) cell display platform in which activation-induced cytidine deaminase (AID) was used to induce antibody mutation, and antibody affinity was successfully matured using the platform. In the current study, we developed thermo-resistant (TR) CHO cells for the purpose of maturing both antibody stability and affinity. We cultured TR CHO cells displaying an antibody mutant library and labeled them at temperatures above 41 °C, enriching cells that displayed antibody mutants with both the highest affinities and the highest display levels. To evaluate our system, we chose three antibodies to improve their affinities and stabilities. We succeeded in simultaneously improving both affinities and stabilities of all three antibodies. Of note, we obtained an anti-TNFα antibody mutant with a Tm (dissolution temperature) value 12 °C higher and affinity 160-fold greater than the parent antibody after two rounds of cell proliferation and flow cytometric sorting. By using CHO cells with its advantages in protein folding, post-translational modifications, and code usage, this procedure is likely to be widely used in maturing antibodies and other proteins in the future. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 5359 KiB

Open AccessArticle

Lung Field Segmentation in Chest X-ray Images Using Superpixel Resizing and Encoder–Decoder Segmentation Networks

by Chien-Cheng Lee, Edmund Cheung So, Lamin Saidy and Min-Ju Wang

Bioengineering 2022, 9(8), 351; https://doi.org/10.3390/bioengineering9080351 - 29 Jul 2022

Cited by 4 | Viewed by 1802

Abstract

Lung segmentation of chest X-ray (CXR) images is a fundamental step in many diagnostic applications. Most lung field segmentation methods reduce the image size to speed up the subsequent processing time. Then, the low-resolution result is upsampled to the original high-resolution image. Nevertheless, [...] Read more.

Lung segmentation of chest X-ray (CXR) images is a fundamental step in many diagnostic applications. Most lung field segmentation methods reduce the image size to speed up the subsequent processing time. Then, the low-resolution result is upsampled to the original high-resolution image. Nevertheless, the image boundaries become blurred after the downsampling and upsampling steps. It is necessary to alleviate blurred boundaries during downsampling and upsampling. In this paper, we incorporate the lung field segmentation with the superpixel resizing framework to achieve the goal. The superpixel resizing framework upsamples the segmentation results based on the superpixel boundary information obtained from the downsampling process. Using this method, not only can the computation time of high-resolution medical image segmentation be reduced, but also the quality of the segmentation results can be preserved. We evaluate the proposed method on JSRT, LIDC-IDRI, and ANH datasets. The experimental results show that the proposed superpixel resizing framework outperforms other traditional image resizing methods. Furthermore, combining the segmentation network and the superpixel resizing framework, the proposed method achieves better results with an average time score of 4.6 s on CPU and 0.02 s on GPU. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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9 pages, 1602 KiB

Open AccessCommunication

Intracranial Monitoring to Verify Novel Transcranial Electric Stimulation in an Epileptic Swine Model

by Yu-Chi Wang, Po-Fang Wang, Han-Chi Pan, Chuan-Yi Lin, Hao-Teng Hsu, Zhuo-Hao Liu and Po-Lei Lee

Electronics 2022, 11(14), 2195; https://doi.org/10.3390/electronics11142195 - 13 Jul 2022

Viewed by 1596

Abstract

Invasive deep brain stimulation has proven to be clinically therapeutic for patients with drug-refractory epilepsy. The aim of this study was to develop a novel transcranial electrical device as a noninvasive stimulation modality for seizure treatment. We fabricated a novel transcranial electrical device [...] Read more.

Invasive deep brain stimulation has proven to be clinically therapeutic for patients with drug-refractory epilepsy. The aim of this study was to develop a novel transcranial electrical device as a noninvasive stimulation modality for seizure treatment. We fabricated a novel transcranial electrical device and tested it in four swine brains with depth electrodes surgically implanted under neuro-navigation. Stimulation with two high-frequency alternating currents was used to cause an interference envelope. Acute focal epilepsy was induced by a subcortical injection of penicillin and specific anesthesia protocol. The frequency and electric field of the stimulation in the hippocampus were investigated. The two frequencies (2 k and 2.14 kHz) of stimulation successfully caused an envelope of 140 Hz. With 1 mA stimulation, the electric field degraded gradually and induced an in situ electric field of 0.68 mV/mm in the hippocampi. The interference mode transcranial electric stimulation attenuated the originally induced epileptic form discharges. No neuronal or axonal injuries were noted histopathologically after the stimulation. The feasibility and biosafety of our proposed device were preliminarily verified. Future translational research should focus on the electrode deposition and stimulation parameters for a quantitative therapeutic effect. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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20 pages, 5535 KiB

Open AccessArticle

The Effect of Lower Limb Exoskeleton Alignment on Knee Rehabilitation Efficacy

by AmirHossein MajidiRad, Yimesker Yihun, Nils Hakansson and Allyson Mitchell

Healthcare 2022, 10(7), 1291; https://doi.org/10.3390/healthcare10071291 - 12 Jul 2022

Cited by 2 | Viewed by 2030

Abstract

This study focuses on a musculoskeletal analysis of human lower extremity and associated muscle forces during different rehabilitative tasks and exoskeleton alignment models. By changing the size and orientation of the impairment levels that could be caused by the misalignment of the exoskeleton [...] Read more.

This study focuses on a musculoskeletal analysis of human lower extremity and associated muscle forces during different rehabilitative tasks and exoskeleton alignment models. By changing the size and orientation of the impairment levels that could be caused by the misalignment of the exoskeleton and biological knee joint, muscle stress variations were observed. This indicates an increase in force such as that generated by the Vastus lateralis muscle up to 4.3% due to a 5 mm lateral offset from an anatomically healthy knee joint location. In another setting, while a subject moved the shank through a circular trajectory using an exoskeleton support, muscle strain due to misalignment was reflected at the rectus femoris with a variation of 44%, the biceps femoris large head with 32% and the gastrocnemius muscles with 31–33% variation. These results suggest that misalignment should be taken into account while using exoskeletons with certain trajectories for knee rehabilitation purposes. Based on the shortcomings of conventional physiotherapeutic tasks, the outcome of this study can be helpful in prescribing an impactful yet convenient configuration toward a safe and promising rehabilitation process. Assessment of exoskeleton alignment during rehabilitation is important to ensure user safety with a better therapy efficacy. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 3566 KiB

Open AccessArticle

Incorporating Fuzzy Cognitive Inference for Vaccine Hesitancy Measuring

by Kun Sun, Tian-Fang Zhao, Xiao-Kun Wu, Kai-Sheng Lai, Wei-Neng Chen and Jin-Sheng Zhang

Sustainability 2022, 14(14), 8434; https://doi.org/10.3390/su14148434 - 10 Jul 2022

Viewed by 1544

Abstract

Vaccine hesitancy plays a key role in vaccine delay and refusal, but its measurement is still a challenge due to multiple intricacies and uncertainties in factors. This paper attempts to tackle this problem through fuzzy cognitive inference techniques. Firstly, we formulate a vaccine [...] Read more.

Vaccine hesitancy plays a key role in vaccine delay and refusal, but its measurement is still a challenge due to multiple intricacies and uncertainties in factors. This paper attempts to tackle this problem through fuzzy cognitive inference techniques. Firstly, we formulate a vaccine hesitancy determinants matrix containing multi-level factors. Relations between factors are formulated through group decision-making of domain experts, which results in a fuzzy cognitive map. The subjective uncertainty of linguistic variables is expressed by fuzzy numbers. A double-weighted method is designed to integrate the distinguished decisions, in which the subjective hesitancy is considered for each decision. Next, three typical scenarios are constructed to identify key and sensitive factors under different experimental conditions. The experimental results are further discussed, which enrich the approaches of vaccine hesitancy estimation for the post-pandemic global recovery. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 881 KiB

Open AccessArticle

Implementation and Acceptance of Information and Communication Technology Incorporated into Long-Term Care

by Yi-Cheng Chiang, Yin-Chia Hsieh and Fan Wu

Healthcare 2022, 10(7), 1253; https://doi.org/10.3390/healthcare10071253 - 05 Jul 2022

Cited by 1 | Viewed by 1910

Abstract

Every country in the world is facing serious demographic aging, since the average life expectancy is consistently increasing. Agencies involved in the implementation of caregiving through long-term care institutions can develop more convenient approaches using information and communication technology to enhance overall efficiency. [...] Read more.

Every country in the world is facing serious demographic aging, since the average life expectancy is consistently increasing. Agencies involved in the implementation of caregiving through long-term care institutions can develop more convenient approaches using information and communication technology to enhance overall efficiency. Communication technology has enabled the strengthening of physiological instruments, improving the efficiency and quality of services, while integrating management systems for optimum efficiency. This work conducted empirical studies, collecting responses to questionnaires from residents and caregivers in five institutions located in the south of Taiwan. The PZB model, proposed by Parasuraman, Zeithaml, and Berry, was used to construct the questionnaire to analyze the service quality following the incorporation of information and communication technology. The results of the empirical study show that 34% and 63% of the relatives of the residents agreed and strongly agreed that the system was practical and convenient, respectively. As for the caregivers, 77% of them agreed or strongly agreed that the system was mobile, practical, and convenient, and they agreed that the system could significantly increase working efficiency, reduce waiting time, and improve administration for chronic diseases among care-home residents. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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17 pages, 5192 KiB

Open AccessArticle

The Full Informational Spectral Analysis for Auditory Steady-State Responses in Human Brain Using the Combination of Canonical Correlation Analysis and Holo-Hilbert Spectral Analysis

by Po-Lei Lee, Te-Min Lee, Wei-Keung Lee, Narisa Nan Chu, Yuri E. Shelepin, Hao-Teng Hsu and Hsiao-Huang Chang

J. Clin. Med. 2022, 11(13), 3868; https://doi.org/10.3390/jcm11133868 - 04 Jul 2022

Cited by 3 | Viewed by 2302

Abstract

Auditory steady-state response (ASSR) is a translational biomarker for several neurological and psychiatric disorders, such as hearing loss, schizophrenia, bipolar disorder, autism, etc. The ASSR is sinusoidal electroencephalography (EEG)/magnetoencephalography (MEG) responses induced by periodically presented auditory stimuli. Traditional frequency analysis assumes ASSR is [...] Read more.

Auditory steady-state response (ASSR) is a translational biomarker for several neurological and psychiatric disorders, such as hearing loss, schizophrenia, bipolar disorder, autism, etc. The ASSR is sinusoidal electroencephalography (EEG)/magnetoencephalography (MEG) responses induced by periodically presented auditory stimuli. Traditional frequency analysis assumes ASSR is a stationary response, which can be analyzed using linear analysis approaches, such as Fourier analysis or Wavelet. However, recent studies have reported that the human steady-state responses are dynamic and can be modulated by the subject’s attention, wakefulness state, mental load, and mental fatigue. The amplitude modulations on the measured oscillatory responses can result in the spectral broadening or frequency splitting on the Fourier spectrum, owing to the trigonometric product-to-sum formula. Accordingly, in this study, we analyzed the human ASSR by the combination of canonical correlation analysis (CCA) and Holo-Hilbert spectral analysis (HHSA). The CCA was used to extract ASSR-related signal features, and the HHSA was used to decompose the extracted ASSR responses into amplitude modulation (AM) components and frequency modulation (FM) components, in which the FM frequency represents the fast-changing intra-mode frequency and the AM frequency represents the slow-changing inter-mode frequency. In this paper, we aimed to study the AM and FM spectra of ASSR responses in a 37 Hz steady-state auditory stimulation. Twenty-five healthy subjects were recruited for this study, and each subject was requested to participate in two auditory stimulation sessions, including one right-ear and one left-ear monaural steady-state auditory stimulation. With the HHSA, both the 37 Hz (fundamental frequency) and the 74 Hz (first harmonic frequency) auditory responses were successfully extracted. Examining the AM spectra, the 37 Hz and the 74 Hz auditory responses were modulated by distinct AM spectra, each with at least three composite frequencies. In contrast to the results of traditional Fourier spectra, frequency splitting was seen at 37 Hz, and a spectral peak was obscured at 74 Hz in Fourier spectra. The proposed method effectively corrects the frequency splitting problem resulting from time-varying amplitude changes. Our results have validated the HHSA as a useful tool for steady-state response (SSR) studies so that the misleading or wrong interpretation caused by amplitude modulation in the traditional Fourier spectrum can be avoided. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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9 pages, 1438 KiB

Open AccessArticle

Effect of the Application of Virtual Reality on Pain Reduction and Cerebral Blood Flow in Robot-Assisted Gait Training in Burn Patients

by Seung Yeol Lee, Jeong Yeon Cha, Ji Won Yoo, Matheu Nazareno, Yoon Soo Cho, So Young Joo and Cheong Hoon Seo

J. Clin. Med. 2022, 11(13), 3762; https://doi.org/10.3390/jcm11133762 - 29 Jun 2022

Cited by 7 | Viewed by 2435

Abstract

Burn injuries and their treatment are extremely painful. This study aimed to determine whether virtual reality (VR) could reduce pain during robot-assisted gait training (RAGT) in burn patients by analyzing the cerebral blood flow (CBF) in the prefrontal cortex over time using functional [...] Read more.

Burn injuries and their treatment are extremely painful. This study aimed to determine whether virtual reality (VR) could reduce pain during robot-assisted gait training (RAGT) in burn patients by analyzing the cerebral blood flow (CBF) in the prefrontal cortex over time using functional near-infrared spectroscopy (fNIRS). The patients included in this study complained of a pain score ≥5 on a visual analog scale (VAS) during RAGT, which was performed 10 times for 2 weeks. Each session consisted of 15 min of VR application, with a 2-min break, and 15 min without VR. The average values of oxyhemoglobin and deoxyhemoglobin concentrations in the prefrontal cortex on fNIRS were calculated at four stages: temporal delay time with only RAGT, RAGT without VR, temporal delay time with RAGT and VR, and RAGT with VR. The pain scores and CBF were evaluated in sessions 1, 5, and 10 of the RAGT. The mean VAS pain scores were significantly lower (p < 0.05) in the experimental condition than in the control condition. Oxyhemoglobin in the prefrontal lobe significantly increased when RAGT was performed with VR. In conclusion, VR may be a strong nonpharmacological pain reduction technique for burn patients during physical therapy. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 1692 KiB

Open AccessArticle

Mechatronic Design of a Prototype Orthosis to Support Elbow Joint Rehabilitation

by Jhoan Danilo Arcos Rosero, Daniel Camilo Bolaños Rosero, Luis Fernando Alape Realpe, Andrés Felipe Solis Pino and Elizabeth Roldán González

Bioengineering 2022, 9(7), 287; https://doi.org/10.3390/bioengineering9070287 - 29 Jun 2022

Cited by 2 | Viewed by 2069

Abstract

Injuries in the elbow area, such as lateral and medial epicondylitis, are the leading causes of consultation with health specialists. Therefore, this research proposes the mechatronic design of an orthosis with a graphic interface that supports professionals in the rehabilitation of the elbow [...] Read more.

Injuries in the elbow area, such as lateral and medial epicondylitis, are the leading causes of consultation with health specialists. Therefore, this research proposes the mechatronic design of an orthosis with a graphic interface that supports professionals in the rehabilitation of the elbow joint through the execution of flexion–extension and pronation–supination movements. For the development of the rehabilitation prototype, mechatronic design, co-design, and IDEF0 methodologies are used, performing activities such as actuator characterization, simulations, and modeling, among others. Through the execution of a case study in a real environment, the device was validated, where the results suggest a functional and workable prototype that supports the treatment of pathologies in the elbow area through the execution of the mentioned movements, supposing that this is a low-cost alternative with elements to improve, such as the industrial design and new functionalities. The developed proposal shows potential as an economical product that health professionals can use. However, some limitations related to the design and functionalities in the application domain were identified. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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20 pages, 898 KiB

Open AccessArticle

Sustaining the Well-Being of Wearable Technology Users: Leveraging SEM-Based IPMA and VIKOR Analyses to Gain Deeper Insights

by Huan-Ming Chuang and Chien-I Chen

Sustainability 2022, 14(13), 7799; https://doi.org/10.3390/su14137799 - 27 Jun 2022

Cited by 4 | Viewed by 1774

Abstract

Wearable technology is a self-contained computer system that can record muscular activity data. Wearable technologies are rapidly evolving that have the potential to enhance the well-being of healthier lives. However, wearable technologies are finding slow adoption rates relative to mainstream technologies such as [...] Read more.

Wearable technology is a self-contained computer system that can record muscular activity data. Wearable technologies are rapidly evolving that have the potential to enhance the well-being of healthier lives. However, wearable technologies are finding slow adoption rates relative to mainstream technologies such as smartphones. Consequently, both designers and manufacturers are increasingly interested in key decision factors that influence the acceptance of these technologies. As discussions relating to wearable technologies are often approached from different perspectives, a general framework featuring not only a synthesis of general acceptance issues but also with consideration of contingent factors would be a useful research undertaking. Furthermore, wearable technology acceptance studies are insufficient to supplement practical implementation and promotion issues. In this regard, methods for further analysis of results from structural equation modeling (SEM), such as importance-performance map analysis (IPMA) and VIKOR for multi-criteria optimization and compromise solution, can be used to derive greater insights. The primary research findings are extensively discussed, and practical promotion strategies for wearable technologies for health care are suggested. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 444 KiB

Open AccessArticle

Development and Validation of a New Questionnaire to Measure Knowledge Level of Street Food Hawkers to Support the Single-Use Plastics Reduction Program in Kelantan, Malaysia

by Nur Baizura Aini Abdullah, Nor Azwany Yaacob and Ahmad Filza Ismail

Sustainability 2022, 14(13), 7552; https://doi.org/10.3390/su14137552 - 21 Jun 2022

Cited by 1 | Viewed by 2961

Abstract

Food hawkers’ knowledge about single-use plastic food containers must be assessed using a valid and reliable tool to improve assessment and evidence collection credibility and to promote environmental sustainability practice. This study aims to develop and validate a new questionnaire to assess the [...] Read more.

Food hawkers’ knowledge about single-use plastic food containers must be assessed using a valid and reliable tool to improve assessment and evidence collection credibility and to promote environmental sustainability practice. This study aims to develop and validate a new questionnaire to assess the knowledge level of street food hawkers to support the single-use plastics reduction program. Seven experts were involved in the questionnaire process. In the validation process, a cross-sectional study employed the purposive sampling of 660 night-market street food hawkers in a north-eastern state in Peninsular Malaysia, utilising a Google Forms questionnaire with 22 self-administered items. The Content Validity Index (CVI) and Face Validity index (FVI) were used for the construct analysis. The dichotomous response scale was analysed using a two-parameter logistic model of item response theory (2-PL IRT), while marginal reliability used to determine the internal consistency. The I-CVI were calculated for all items with the value ≥ 0.83, except for nine items with I-CVI < 0.83. I-FVI with values of 0.83 or more were acceptable. The 2-PL IRT analyses indicated good psychometric properties considering the discrimination and difficulty index. The marginal reliability value was 0.77. The newly developed questionnaire is a valid and reliable tool to assess the knowledge level of street-food hawkers to support the single-use plastics reduction program. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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9 pages, 2854 KiB

Open AccessArticle

Physiological Ventricular Simulator for Valve Surgery Training

by Kasparas Zilinskas, Jennie H. Kwon, Katherine Bishara, Kaila Hayden, Ritchelli Quintao and Taufiek Konrad Rajab

Bioengineering 2022, 9(6), 264; https://doi.org/10.3390/bioengineering9060264 - 20 Jun 2022

Cited by 1 | Viewed by 1585

Abstract

Surgical simulation is becoming increasingly important in training cardiac surgeons. However, there are currently no training simulators capable of testing the quality of simulated heart valve procedures under dynamic physiologic conditions. Here we describe a dynamic ventricular simulator, consisting of a 3D printed [...] Read more.

Surgical simulation is becoming increasingly important in training cardiac surgeons. However, there are currently no training simulators capable of testing the quality of simulated heart valve procedures under dynamic physiologic conditions. Here we describe a dynamic ventricular simulator, consisting of a 3D printed valve suspension chamber and a model 1423 Harvard apparatus pulsatile pump, which can provide close to physiologic hemodynamic perfusion of porcine aortic roots attached to the valve chamber for education and training in cardiac surgery. The simulator was validated by using it to test aortic valve leaflet repairs (n = 6) and aortic valve replacements (n = 3) that were performed by two trainees. Procedural success could be evaluated by direct visualization of the opening and closing valve, hemodynamic measurements and echocardiography. We conclude that, unlike other methods of simulation, this novel ventricular simulator is able to test the functional efficacy of aortic procedures under dynamic physiologic conditions using clinically relevant echocardiographic and hemodynamic outcomes. While validated for valve surgery, other potential applications include ascending aortic interventions, coronary re-implantation or catheter-based valve replacements. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 698 KiB

Open AccessSystematic Review

Utility of Teleorthodontics in Orthodontic Emergencies during the COVID-19 Pandemic: A Systematic Review

by Sabina Saccomanno, Vincenzo Quinzi, Arianna Albani, Nicola D’Andrea, Giuseppe Marzo and Guido Macchiarelli

Healthcare 2022, 10(6), 1108; https://doi.org/10.3390/healthcare10061108 - 14 Jun 2022

Cited by 8 | Viewed by 2066

Abstract

Background. Coronavirus disease has subjected the whole of humanity to two years of social isolation and a series of restrictions. These circumstances have led to the use of information technology in an increasingly widespread manner. Even in the dental field, telematic means have [...] Read more.

Background. Coronavirus disease has subjected the whole of humanity to two years of social isolation and a series of restrictions. These circumstances have led to the use of information technology in an increasingly widespread manner. Even in the dental field, telematic means have been used to respond to emergencies. The aim of this systematic review of the literature is to evaluate the types of orthodontic emergency that occurred most often and how they were managed by teleorthodontics during the COVID-19 pandemic. The secondary aim is that clinicians will use teleorthodontics not only during pandemics but as an additional tool to manage orthodontics. Materials and Methods. Out of 1695 articles available on PubMed, Science Direct, Cochrane and SciELO, eight articles were selected for this systematic literature review. Google Scholar was used as a secondary source to confirm that there were no additional articles. The screened papers comprised editorials, clinical studies, cross-sectional studies and retrospective studies in Italian, English or Spanish language. Results. The articles showed that the means by which patients most often communicated with their orthodontists were voice calls and smartphone applications such as WhatsApp^® Messenger. Through these media, patients communicated their orthodontic emergencies. These mainly involved fixed multibracket appliances and the most common issues were discomfort and pain, fracture or loss of the appliance, protruding distal ends of archwires, brackets, tubes and bands or retainer detachment. Through teleorthodontics, patients could solve these issues by using orthodontic relief wax, cutting the protruding distal ends of the archwire with a nail clipper or a stronger cutter and removing or replacing detached bands, brackets, tubes or metallic ligature with a clean tweezer. Conclusions. In situations where personal contact is limited, teleorthodontics represents a valuable aid for professionals and patients facing orthodontic emergencies. The hope is that it may continue to represent a valuable aid for patients with difficulties in planning an in-office visit. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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8 pages, 1225 KiB

Open AccessArticle

Differential Screening of Herniated Lumbar Discs Based on Bag of Visual Words Image Classification Using Digital Infrared Thermographic Images

by Gi Nam Kim, Ho Yeol Zhang, Yong Eun Cho and Seung Jun Ryu

Healthcare 2022, 10(6), 1094; https://doi.org/10.3390/healthcare10061094 - 13 Jun 2022

Cited by 2 | Viewed by 1758

Abstract

Doctors in primary hospitals can obtain the impression of lumbosacral radiculopathy with a physical exam and need to acquire medical images, such as an expensive MRI, for diagnosis. Then, doctors will perform a foraminal root block to the target root for pain control. [...] Read more.

Doctors in primary hospitals can obtain the impression of lumbosacral radiculopathy with a physical exam and need to acquire medical images, such as an expensive MRI, for diagnosis. Then, doctors will perform a foraminal root block to the target root for pain control. However, there was insufficient screening medical image examination for precise L5 and S1 lumbosacral radiculopathy, which is most prevalent in the clinical field. Therefore, to perform differential screening of L5 and S1 lumbosacral radiculopathy, the authors applied digital infrared thermographic images (DITI) to the machine learning (ML) algorithm, which is the bag of visual words method. DITI dataset included data from the healthy population and radiculopathy patients with herniated lumbar discs (HLDs) L4/5 and L5/S1. A total of 842 patients were enrolled and the dataset was split into a 7:3 ratio as the training algorithm and test dataset to evaluate model performance. The average accuracy was 0.72 and 0.67, the average precision was 0.71 and 0.77, the average recall was 0.69 and 0.74, and the F1 score was 0.70 and 0.75 for the training and test datasets. Application of the bag of visual words algorithm to DITI classification will aid in the differential screening of lumbosacral radiculopathy and increase the therapeutic effect of primary pain interventions with economical cost. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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10 pages, 255 KiB

Open AccessArticle

Physical Activity Energy Expenditure Predicts Quality of Life in Ambulatory School-Age Children with Cerebral Palsy

by Jinuk Lee, Min-Hwa Suk, Soojin Yoo and Jeong-Yi Kwon

J. Clin. Med. 2022, 11(12), 3362; https://doi.org/10.3390/jcm11123362 - 11 Jun 2022

Cited by 1 | Viewed by 1570

Abstract

Background: Participation in physical activities is positively associated with better quality of life in children with cerebral palsy (CP). The objective of this study was to elucidate the relationship between the intensity of habitual physical activity (HPA) measured with an accelerometer and health-related [...] Read more.

Background: Participation in physical activities is positively associated with better quality of life in children with cerebral palsy (CP). The objective of this study was to elucidate the relationship between the intensity of habitual physical activity (HPA) measured with an accelerometer and health-related quality of life (HRQOL) in school-age children with CP. Method: A secondary analysis of the cross-sectional data of 46 ambulatory children with CP was conducted. The participants wore an accelerometer for seven days to measure HPA: activity counts (counts/min) and physical activity energy expenditure (PAEE, kcal/kg/day), as well as %moderate-to-vigorous intensity physical activity (%MVPA), %light intensity physical activity (%LPA), and %sedentary physical activity (%SPA) were measured. Pediatric Quality of Life Inventory (PedsQL) 4.0 Generic Core Scales and Child Health Questionnaire Parent Form 50 Questions (CHQ-PF50) were used to measure HRQOL. A Pearson analysis and a hierarchical regression analysis were performed. Results: PAEE significantly predicted the results of the PedsQL(child) physical domain (β = 0.579, p = 0.030), PedsQL(child) emotional domain (β = 0.570, p = 0.037), PedsQL(child) social domain (β = 0.527, p = 0.043), and PedsQL(child) total (β = 0.626, p = 0.017). However, other HPA parameters could not predict any other HRQOL. Conclusions: PAEE could be used as a biomarker in studies on HRQOL and HPA in ambulatory school-age children with CP. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

12 pages, 522 KiB

Open AccessArticle

Weighting of Firefighting Turnout Gear Risk Factors According to Expert Opinion

by Tsui-Yuan Chang, Hsi-Peng Lu, Tain-Yi Luor and Ping-Wu Chang

Sustainability 2022, 14(12), 7040; https://doi.org/10.3390/su14127040 - 08 Jun 2022

Cited by 5 | Viewed by 1871 | Correction

Abstract

Firefighters in Taiwan often wear expired protective clothing, which raises concerns regarding their safety. Extending the service life of fire protective clothing can improve firefighter safety and ensure environmental sustainability. In this study, an analytic hierarchy process was used to understand which risk [...] Read more.

Firefighters in Taiwan often wear expired protective clothing, which raises concerns regarding their safety. Extending the service life of fire protective clothing can improve firefighter safety and ensure environmental sustainability. In this study, an analytic hierarchy process was used to understand which risk factors should be prioritized in the design of firefighting turnout gear. We surveyed 30 experts in the field of firefighting and safety management on the importance of various risk factors related to turnout gear. A risk level of 70% was taken as the threshold of tolerable risk. The rankings of the weighted risk factors demonstrate that eliminating 12 of the 28 risk factors will result in 73% safety. These 12 factors are, in order of maximum risk, insufficient flame resistance, insufficient heat resistance, putting on the suit components in the wrong order, insufficient resistance to tears and punctures, poor agility, heavy overall weight, insufficient water resistance, lack of flame-retardant fibers, high levels of toxicity, insufficient internal circulation, no air filtration device, and poor air permeability. Consideration of these factors in the design of fire protective clothing can extend service life, help achieve sustainable development goals, and ensure firefighters’ safety. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 3182 KiB

Open AccessArticle

Self-Assembled Hydrogel Microparticle-Based Tooth-Germ Organoids

by Cemile Kilic Bektas, Weibo Zhang, Yong Mao, Xiaohuan Wu, Joachim Kohn and Pamela C. Yelick

Bioengineering 2022, 9(5), 215; https://doi.org/10.3390/bioengineering9050215 - 17 May 2022

Cited by 10 | Viewed by 4168

Abstract

Here, we describe the characterization of tooth-germ organoids, three-dimensional (3D) constructs cultured in vitro with the potential to develop into living teeth. To date, the methods used to successfully create tooth organoids capable of forming functional teeth have been quite limited. Recently, hydrogel [...] Read more.

Here, we describe the characterization of tooth-germ organoids, three-dimensional (3D) constructs cultured in vitro with the potential to develop into living teeth. To date, the methods used to successfully create tooth organoids capable of forming functional teeth have been quite limited. Recently, hydrogel microparticles (HMP) have demonstrated utility in tissue repair and regeneration based on their useful characteristics, including their scaffolding ability, effective cell and drug delivery, their ability to mimic the natural tissue extracellular matrix, and their injectability. These outstanding properties led us to investigate the utility of using HMPs (average diameter: 158 ± 32 µm) derived from methacrylated gelatin (GelMA) (degree of substitution: 100%) to create tooth organoids. The tooth organoids were created by seeding human dental pulp stem cells (hDPSCs) and porcine dental epithelial cells (pDE) onto the HMPs, which provided an extensive surface area for the cells to effectively attach and proliferate. Interestingly, the cell-seeded HMPs cultured on low-attachment tissue culture plates with gentle rocking self-assembled into organoids, within which the cells maintained their viability and morphology throughout the incubation period. The self-assembled organoids reached a volume of ~50 mm³ within two weeks of the in vitro tissue culture. The co-cultured hDPSC-HMP and pDE-HMP structures effectively attached to each other without any externally applied forces. The presence of polarized, differentiated dental cells in these composite tooth-bud organoids demonstrated the potential of self-assembled dental cell HMPs to form tooth-bud organoid-like structures for potential applications in tooth regeneration strategies. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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15 pages, 2590 KiB

Open AccessArticle

Comprehensive Overview of Backpropagation Algorithm for Digital Image Denoising

by Abha Singh, Sumit Kushwaha, Maryam Alarfaj and Manoj Singh

Electronics 2022, 11(10), 1590; https://doi.org/10.3390/electronics11101590 - 17 May 2022

Cited by 23 | Viewed by 3878

Abstract

Artificial ANNs (ANNs) are relatively new computational tools used in the development of intelligent systems, some of which are inspired by biological ANNs, and have found widespread application in the solving of a variety of complex real-world problems. It boasts enticing features as [...] Read more.

Artificial ANNs (ANNs) are relatively new computational tools used in the development of intelligent systems, some of which are inspired by biological ANNs, and have found widespread application in the solving of a variety of complex real-world problems. It boasts enticing features as well as remarkable data processing capabilities. In this paper, a comprehensive overview of the backpropagation algorithm for digital image denoising was discussed. Then, we presented a probabilistic analysis of how different algorithms address this challenge, arguing that small ANNs can denoise small-scale texture patterns almost as effectively as their larger equivalents. The results also show that self-similarity and ANNs are complementary paradigms for patch denoising, as demonstrated by an algorithm that effectively complements BM3D with small ANNs, surpassing BM3D at a low cost. Here, one of the most significant advantages of this learning technique is that, once taught, digital images may be recovered without prior knowledge of the degradation model (noise/blurring) that caused the digital image to become distorted. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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15 pages, 2329 KiB

Open AccessArticle

Hybrid Zero Dynamics Control for Gait Guidance of a Novel Adjustable Pediatric Lower-Limb Exoskeleton

by Anthony Goo, Curt A. Laubscher, Jason J. Wiebrecht, Ryan J. Farris and Jerzy T. Sawicki

Bioengineering 2022, 9(5), 208; https://doi.org/10.3390/bioengineering9050208 - 12 May 2022

Cited by 4 | Viewed by 2544

Abstract

Exoskeleton technology has undergone significant developments for the adult population but is still lacking for the pediatric population. This paper presents the design of a hip–knee exoskeleton for children 6 to 11 years old with gait abnormalities. The actuators are housed in an [...] Read more.

Exoskeleton technology has undergone significant developments for the adult population but is still lacking for the pediatric population. This paper presents the design of a hip–knee exoskeleton for children 6 to 11 years old with gait abnormalities. The actuators are housed in an adjustable exoskeleton frame where the thigh part can adjust in length and the hip cradle can adjust in the medial-lateral and posterior-anterior directions concurrently. Proper control of exoskeletons to follow nominal healthy gait patterns in a time-invariant manner is important for ease of use and user acceptance. In this paper, a hybrid zero dynamics (HZD) controller was designed for gait guidance by defining the zero dynamics manifold to resemble healthy gait patterns. HZD control utilizes a time-invariant feedback controller to create dynamically stable gaits in robotic systems with hybrid models containing both discrete and continuous dynamics. The effectiveness of the controller on the novel pediatric exoskeleton was demonstrated via simulation. The presented preliminary results suggest that HZD control provides a viable method to control the pediatric exoskeleton for gait guidance. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 633 KiB

Open AccessArticle

Patient-Perceived Health System Responsiveness of the Epilepsy Management Project in Rural China during the Period of COVID-19

by Lulu Qin, Si Chen, Xianglin Feng, Bangan Luo and Yiwei Chen

Healthcare 2022, 10(5), 799; https://doi.org/10.3390/healthcare10050799 - 25 Apr 2022

Cited by 1 | Viewed by 2331

Abstract

Health system responsiveness (HSR) measures the experience of health-system users in terms of the non-clinical domains of the health system, which has been regarded as the three major goals of health performance evaluation. Good HSR may promote the use of health services and [...] Read more.

Health system responsiveness (HSR) measures the experience of health-system users in terms of the non-clinical domains of the health system, which has been regarded as the three major goals of health performance evaluation. Good HSR may promote the use of health services and ultimately the health of patients. However, the HSR has not been measured as the main goal of the Epilepsy Management Project (EMP) in rural China. This study aims to evaluate the levels and distributions of the patient-perceived HSR of the EMP in rural China during the period of COVID-19 and identify its relevant factors so as to provide advice on the improvement of further strategies. Based on the key informant survey (KIS) of responsiveness from the World Health Organization proposal, we conducted a cross-sectional survey of 420 epilepsy patients selected proportional randomly from seven rural areas in the Hunan province of China in 2021. Eight domains of patients-perceived HSR were assessed by face-to-face interview. The overall HSR scored at a fairly “good” level of 8.3 (8.3 out of a maximum of 10.0). During the COVID-19 period, the scores of responsiveness domains were highest at 8.66 to 8.93 in “confidentiality”, “dignity” and “choice of providers”, while lowest at 8.38 to 8.53 in “prompt attention”, “social support” and “basic amenities”. The representative responsiveness equality index (REI) was 0.732, indicating the moderately balanced distributions of responsiveness of the EMP in rural China. Female, old age, and low education were significantly related to the lower HSR scores of rural EMP (p < 0.05). The HSR of EMP in rural China was fairly good. However, measures to improve the patient-perceived HSR are still needed, especially including better service, higher social support, and more comfortable medical environments. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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14 pages, 1437 KiB

Open AccessArticle

Pre-Pandemic Dietary Assessment of Elderly Persons Residing in Nursing Homes—Silesia (Poland)

by Mateusz Grajek, Karolina Krupa-Kotara, Joanna Kobza and Antoniya Yanakieva

Healthcare 2022, 10(5), 765; https://doi.org/10.3390/healthcare10050765 - 20 Apr 2022

Viewed by 1684

Abstract

Background. Residents of nursing homes (NHs) are one of the most vulnerable social groups to SARS-CoV-2 infection. It seems obvious that all preventive methods, including nutrition, should be a priority for these homes. Objective. The aim of this study was to evaluate the [...] Read more.

Background. Residents of nursing homes (NHs) are one of the most vulnerable social groups to SARS-CoV-2 infection. It seems obvious that all preventive methods, including nutrition, should be a priority for these homes. Objective. The aim of this study was to evaluate the menus of elderly people residing in nursing homes and to compare them with the recommendations and especially with the scientific literature that proves the protective effect of nutrition on the course of COVID-19 disease. Material and methods. The material investigated in the research were decade menus selected at several nursing homes between 2017 and 2020. The total number of 4640 daily menus from 58 NHs located in Silesia (Poland) were analyzed in the research. Data analysis included mathematical tools of Kruskal–Wallis and U Mann–Whitney tests for multiple comparisons in scarcely observed samples (p = 0.05). Results. It has been noted that the energy value provided with food scored 1780.22 kcal, which denoted 102.72% of the daily standard for females and 98.23% for males. The investigated menus differed in terms of energy and nutrition value. The mean content of proteins totaled 47.95 g/day, which covered 93.83% of the daily requirements for this nutrient. When it came to fat content, a level of 109.12 g/day was observed; this covered 160.47% of the daily requirement for females and 143.58% for males. Absorbable carbohydrates constituted 116.60% of the daily standard, i.e., 151.59 g/day. It was stated that values for vitamin D reached 7.01 (±0.63) µg per day, which can be interpreted as 41.00% of the recommended intake for females and 42.00% for males. It was also noted that the values for vitamins A and E were respectively two and fifteen times lower than the recommendations. Conclusions. The evaluated menus must not be an aid in the prevention and treatment of COVID-19. The content of energy from food, fats, and carbohydrates substantially exceeded recommended standards, whereas the content of proteins, vitamins A, E, D, zinc and calcium did not meet requirements regarding nutrition standards for the analyzed group. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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9 pages, 878 KiB

Open AccessArticle

Immunomodulation of Oxidative Stress during Organ Donation Process: Preliminary Results

by Nora Palomo-López, Ana Rodríguez-Rodríguez, Luis Martín-Villén, María Mendoza-Prieto, Zaida Ruiz de Azúa-López, Lluis Sempere-Bordes, Laura Boyero-Corral, Domingo Daga-Ruiz, Antonio Gordillo-Brenes, María Pacheco-Sánchez, José Miguel Perez-Villares, Ángel Vilches-Arenas and Juan José Egea-Guerrero

Healthcare 2022, 10(5), 762; https://doi.org/10.3390/healthcare10050762 - 20 Apr 2022

Viewed by 1492

Abstract

The objective was to quantify oxidative stress resulting from ischemia during the donation process, using malondialdehyde (MDA) measurement, and its modulation by the administration of melatonin. We designed a triple-blind clinical trial with donors randomized to melatonin or placebo. We collected donors by [...] Read more.

The objective was to quantify oxidative stress resulting from ischemia during the donation process, using malondialdehyde (MDA) measurement, and its modulation by the administration of melatonin. We designed a triple-blind clinical trial with donors randomized to melatonin or placebo. We collected donors by donation after brain death (DBD) and controlled donation after circulatory death (DCD), the latter maintained by normothermic regional perfusion (NRP). Melatonin or placebo was administered prior to donation or following limitation of therapeutic effort (LTE). Demographic variables and medical history were collected. We also collected serial measurements of MDA, at 60 and 90 min after melatonin or placebo administration. A total of 53 donors were included (32 from DBD and 21 from DCD). In the DBD group, 17 donors received melatonin, and 15 placebo. Eight DCD donors were randomized to melatonin and 13 to placebo. Medical history and cause for LTE were similar between groups. Although MDA values did not differ in the DBD group, statistical differences were observed in DCD donors during the 0–60 min interval: −4.296 (−6.752; −2.336) in the melatonin group and −1.612 (−2.886; −0.7445) in controls. Given the antioxidant effect of melatonin, its use could reduce the production of oxidative stress in controlled DCD. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 928 KiB

Open AccessArticle

Efficacy of Four-Channel Functional Electrical Stimulation on Moderate Arm Paresis in Subacute Stroke Patients—Results from a Randomized Controlled Trial

by Thomas Schick, Daniela Kolm, Andreas Leitner, Sandra Schober, Maria Steinmetz and Klemens Fheodoroff

Healthcare 2022, 10(4), 704; https://doi.org/10.3390/healthcare10040704 - 10 Apr 2022

Cited by 2 | Viewed by 2775

Abstract

This preliminary randomized clinical trial explores the efficacy of task-oriented electromyography (EMG)-triggered multichannel functional electrical stimulation (EMG-MES) compared to single-channel cyclic neuromuscular electrical stimulation (cNMES) on regaining control of voluntary movements (CVM) and the ability to execute arm-hand-activities in subacute stroke patients with [...] Read more.

This preliminary randomized clinical trial explores the efficacy of task-oriented electromyography (EMG)-triggered multichannel functional electrical stimulation (EMG-MES) compared to single-channel cyclic neuromuscular electrical stimulation (cNMES) on regaining control of voluntary movements (CVM) and the ability to execute arm-hand-activities in subacute stroke patients with moderate arm paresis. Twelve ischemic stroke patients (Fugl-Meyer Assessment Arm Section (FMA-AS) score: 19–47) with comparable demographics were block-randomized to receive 15 sessions of cNMES or EMG-MES over three weeks additionally to a conventional neurorehabilitation program including task-oriented arm training. FMA-AS, Box-and-Block Test (BBT), and Stroke-Impact-Scale (SIS) were recorded at baseline and follow-up. All participants demonstrated significant improvement in FMA-AS and BBT. Participants treated with EMG-MES had a higher mean gain in FMA-AS than those treated with cNMES. In the SIS daily activities domain, both groups improved non-significantly; participants in the EMG-MES group had higher improvement in arm-hand use and stroke recovery. EMG-MES treatment demonstrated a higher gain of CVM and self-reported daily activities, arm-hand use, and stroke recovery compared to cNMES treatment of the wrist only. The protocol of this proof-of-concept study seems robust enough to be used in a larger trial to confirm these preliminary findings. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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11 pages, 616 KiB

Open AccessArticle

Minimal Contact Robotic Stroke Rehabilitation on Risk of COVID-19, Work Efficiency and Sensorimotor Function

by Bu Hyun Yoon, Chanhee Park and Joshua (Sung) Hyun You

Healthcare 2022, 10(4), 691; https://doi.org/10.3390/healthcare10040691 - 06 Apr 2022

Cited by 4 | Viewed by 2520

Abstract

Patients with hemiparetic stroke undergo direct, labor-intensive hands-on conventional physical therapy to improve sensorimotor function, spasticity, balance, trunk stability, and activities of daily living (ADLs). Currently, direct, intensive hands-on therapeutic modalities have increased concerns during the coronavirus (COVID-19) global pandemic. We developed an [...] Read more.

Patients with hemiparetic stroke undergo direct, labor-intensive hands-on conventional physical therapy to improve sensorimotor function, spasticity, balance, trunk stability, and activities of daily living (ADLs). Currently, direct, intensive hands-on therapeutic modalities have increased concerns during the coronavirus (COVID-19) global pandemic. We developed an innovative Walkbot to mitigate the issues surrounding conventional hands-on physical therapy. We aimed to compare the effects of minimal-contact robotic rehabilitation (MRR) and full-contact conventional rehabilitation (FCR) on static and dynamic balance, trunk stability, ADLs, spasticity, and cognition changes in patients with hemiparetic stroke. A total of 64 patients with hemiparetic stroke (mean age = 66.38 ± 13.17; 27 women) underwent either MRR or FCR three times/week for 6 weeks. Clinical outcome measurements included the Trunk Impairment Scale (TIS), the Berg Balance Scale (BBS), the modified Ashworth Scale (MAS), the Fugl—Meyer Assessment (FMA), and the modified Barthel Index (MBI) scores. A 2 × 2 repeated analysis of variance (ANOVA) was performed, and an independent t-test was used to determine statistical differences in the physiotherapists’ work efficiency and COVID-19 transmission risk. The ANOVA showed that MRR had effects superior to those of FCR on the TIS, the BBS, the FMA, and the MBI (p < 0.05), but not on the MAS (p = 0.230). MRR showed a greater decrease on the physiotherapist’s work efficiency and COVID-19 transmission risk (p < 0.05). Our results provide clinical evidence that robot-assisted locomotor training helps maximize the recovery of sensorimotor function, abnormal synergy, balance, ADLs, and trunk stability, and facilitates a safer environment and less labor demand than conventional stroke rehabilitation. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 580 KiB

Open AccessArticle

Integrated Equipment for Parkinson’s Disease Early Detection Using Graph Convolution Network

by Yefei He, Tao Yang, Cheng Yang and Hong Zhou

Electronics 2022, 11(7), 1154; https://doi.org/10.3390/electronics11071154 - 06 Apr 2022

Cited by 3 | Viewed by 2507

Abstract

There is an increasing need to diagnose Parkinson’s disease (PD) in an early stage. Existing solutions mainly focused on traditional ways such as MRI, thus suffering from the ease-of-use issue. This work presents a new approach using video and skeleton-based techniques to solve [...] Read more.

There is an increasing need to diagnose Parkinson’s disease (PD) in an early stage. Existing solutions mainly focused on traditional ways such as MRI, thus suffering from the ease-of-use issue. This work presents a new approach using video and skeleton-based techniques to solve this problem. In this paper, an end-to-end Parkinson’s disease early diagnosis method based on graph convolution networks is proposed, which takes patients’ skeletons sequence as input and returns the diagnosis result. The asymmetric dual-branch network architecture is designed to process global and local information separately and capture the subtle manifestation of PD. To train the network, we present the first Parkinson’s disease gait dataset, PD-Walk. This dataset consists of 95 PD patients and 96 healthy people’s walking videos. All the data are annotated by experienced doctors. Furthermore, we implement our method on portable equipment, which has been in operation in the First Affiliated Hospital, Zhejiang University School of Medicine. Experiments show that our method can achieve 84.1% accuracy and achieve real-time performance on the equipment in the real environment. Compared with traditional solutions, the proposed method can detect suspicious PD symptoms quickly and conveniently. Integrated equipment can be easily placed in hospitals or nursing homes to provide services for elderly people. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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26 pages, 2430 KiB

Open AccessArticle

A Hybrid Deep Learning Approach for ECG-Based Arrhythmia Classification

by Parul Madan, Vijay Singh, Devesh Pratap Singh, Manoj Diwakar, Bhaskar Pant and Avadh Kishor

Bioengineering 2022, 9(4), 152; https://doi.org/10.3390/bioengineering9040152 - 02 Apr 2022

Cited by 48 | Viewed by 5540

Abstract

Arrhythmias are defined as irregularities in the heartbeat rhythm, which may infrequently occur in a human’s life. These arrhythmias may cause potentially fatal complications, which may lead to an immediate risk of life. Thus, the detection and classification of arrhythmias is a pertinent [...] Read more.

Arrhythmias are defined as irregularities in the heartbeat rhythm, which may infrequently occur in a human’s life. These arrhythmias may cause potentially fatal complications, which may lead to an immediate risk of life. Thus, the detection and classification of arrhythmias is a pertinent issue for cardiac diagnosis. (1) Background: To capture these sporadic events, an electrocardiogram (ECG), a register containing the heart’s electrical function, is considered the gold standard. However, since ECG carries a vast amount of information, it becomes very complex and challenging to extract the relevant information from visual analysis. As a result, designing an efficient (automated) system to analyse the enormous quantity of data possessed by ECG is critical. (2) Method: This paper proposes a hybrid deep learning-based approach to automate the detection and classification process. This paper makes two-fold contributions. First, 1D ECG signals are translated into 2D Scalogram images to automate the noise filtering and feature extraction. Then, based on experimental evidence, by combining two learning models, namely 2D convolutional neural network (CNN) and the Long Short-Term Memory (LSTM) network, a hybrid model called 2D-CNN-LSTM is proposed. (3) Result: To evaluate the efficacy of the proposed 2D-CNN-LSTM approach, we conducted a rigorous experimental study using the widely adopted MIT–BIH arrhythmia database. The obtained results show that the proposed approach provides ≈98.7%, 99%, and 99% accuracy for Cardiac Arrhythmias (ARR), Congestive Heart Failure (CHF), and Normal Sinus Rhythm (NSR), respectively. Moreover, it provides an average sensitivity of the proposed model of 98.33% and a specificity value of 98.35%, for all three arrhythmias. (4) Conclusions: For the classification of arrhythmias, a robust approach has been introduced where

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scalogram images of ECG signals are trained over the CNN-LSTM model. The results obtained are better as compared to the other existing techniques and will greatly reduce the amount of intervention required by doctors. For future work, the proposed method can be applied over some live ECG signals and Bi-LSTM can be applied instead of LSTM. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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18 pages, 2902 KiB

Open AccessArticle

Performance Characteristics of a Novel 3D-Printed Bubble Intermittent Mandatory Ventilator (B-IMV) for Adult Pulmonary Support

by Jonathan A. Poli, Christopher Howard, Alfredo J. Garcia III, Don Remboski, Peter B. Littlewood, John P. Kress, Narayanan Kasthuri, Alia Comai, Kiran Soni, Philip Kennedy, John Ogger and Robert M. DiBlasi

Bioengineering 2022, 9(4), 151; https://doi.org/10.3390/bioengineering9040151 - 02 Apr 2022

Cited by 3 | Viewed by 2985

Abstract

The COVID-19 pandemic has brought attention to the need for developing effective respiratory support that can be rapidly implemented during critical surge capacity scenarios in healthcare settings. Lung support with bubble continuous positive airway pressure (B-CPAP) is a well-established therapeutic approach for supporting [...] Read more.

The COVID-19 pandemic has brought attention to the need for developing effective respiratory support that can be rapidly implemented during critical surge capacity scenarios in healthcare settings. Lung support with bubble continuous positive airway pressure (B-CPAP) is a well-established therapeutic approach for supporting neonatal patients. However, the effectiveness of B-CPAP in larger pediatric and adult patients has not been addressed. Using similar principles of B-CPAP pressure generation, application of intermittent positive pressure inflations above CPAP could support gas exchange and high work of breathing levels in larger patients experiencing more severe forms of respiratory failure. This report describes the design and performance characteristics of the BubbleVent, a novel 3D-printed valve system that combined with commonly found tubes, hoses, and connectors can provide intermittent mandatory ventilation (IMV) suitable for adult mechanical ventilation without direct electrification. Testing of the BubbleVent was performed on a passive adult test lung model and compared with a critical care ventilator commonly used in tertiary care centers. The BubbleVent was shown to deliver stable PIP and PEEP levels, as well as timing control of breath delivery that was comparable with a critical care ventilator. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 57283 KiB

Open AccessArticle

Fully Implantable Neural Stimulator with Variable Parameters

by Tan Pan and Yuanwen Zou

Electronics 2022, 11(7), 1104; https://doi.org/10.3390/electronics11071104 - 31 Mar 2022

Cited by 1 | Viewed by 2228

Abstract

Neural implantable systems have promoted the development of neurosurgery research and clinical practice. However, traditional tethered neural implants use physical wires for power supply and signal transmission, which have many restrictions on implant targets. Therefore, untethered, wireless, and controllable neural stimulation has always [...] Read more.

Neural implantable systems have promoted the development of neurosurgery research and clinical practice. However, traditional tethered neural implants use physical wires for power supply and signal transmission, which have many restrictions on implant targets. Therefore, untethered, wireless, and controllable neural stimulation has always been widely recognized as the engineering goal of neural implants. In this paper, magnetically coupled resonant wireless power transfer (MCR-WPT) technology is adopted to design and manufacture a wireless stimulator for the electrical stimulation experiment of nerve repair. In the process of device development, SCM technology, signal modulation, demodulation, wireless power supply, and integration/packaging are used. Through experimental tests, the stimulator can output single-phase pulse signals with a variable frequency of (1–20 Hz), a duty cycle of (1–50%), and voltage. The average power is approximately 25 mW. The minimum pulse width of the signal is 200 μs and the effective distance of transmission is 1–4 cm. The stimulator can perform low-frequency, safe and controllable wireless stimulation. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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6 pages, 1290 KiB

Open AccessBrief Report

The Telecardiology Revolution: From Emergency Management to Daily Clinical Practice

by Silvana De Bonis, Nadia Salerno, Antonio Bisignani, Antonella Verta, Cristina Capristo, Antonio Capristo, Gennaro Sosto, Sabato Sorrentino and Giovanni Bisignani

J. Clin. Med. 2022, 11(7), 1920; https://doi.org/10.3390/jcm11071920 - 30 Mar 2022

Viewed by 1914

Abstract

Aims: Telecardiology is one of the most widespread applications of telemedicine. We aimed to report the design and development of a telecardiology system in the sanitary district of Cosenza, one of the largest in Italy, with a complex orography, and healthcare reorganization needs, [...] Read more.

Aims: Telecardiology is one of the most widespread applications of telemedicine. We aimed to report the design and development of a telecardiology system in the sanitary district of Cosenza, one of the largest in Italy, with a complex orography, and healthcare reorganization needs, for the management of the emergency network and daily clinical practice. Methods: Our telecardiology network connects 8 hospitals, 9 first aid centers, 20 local 118-EMS stations, 1 helicopter station, 8 hospital emergency departments, 59 hospital departments, and 3 catheterization laboratories. All data are centralized on a dedicated server, accessible from any location for real-time assessment. The quality, source, and timing of the electrocardiograms transmitted were evaluated. Results: From October 2015 to December 2019, a total of 389,970 ECGs were transmitted. The quality of ECGs was optimal in 52%, acceptable in 42%, and poor in 6% of the cases. The number of poor-quality ECGs was only 3% in the last 2 years. Out of the total, 145,097 (37.2%) were transmitted from the emergency departments and 5318 (1.4%) from the 118-EMS. Of interest, a sizable part of the ECG was related to routine clinical practice, comprising 110,556 (28.3%) from the cardiology department and 79,256 (20.3%) from other noncardiovascular departments. Finally, the average reporting time was significantly decreased compared to reporting times without a telecardiology system (5–10 vs. 45–90 min). Conclusion: Our telecardiology system provides efficient cardiology assistance for all types, settings, and phases of cardiovascular diseases. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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13 pages, 858 KiB

Open AccessArticle

Home-Based Intermittent Pneumatic Compression Therapy: The Impact in Chronic Leg Lymphedema in Patients Treated for Gynecologic Cancer

by Yoon Kim, Seonghee Kim, Ji Young Lim, Chea Min Hwang, Myoung-Hwan Ko and Ji Hye Hwang

Healthcare 2022, 10(4), 638; https://doi.org/10.3390/healthcare10040638 - 28 Mar 2022

Cited by 5 | Viewed by 2193

Abstract

We conducted a prospective study of cancer patients to investigate the efficacy, quality of life, satisfaction, and safety of a home-based intermittent pneumatic compression (IPC) device during the maintenance phase of lower extremity lymphedema. This device has a unique mode designed to mimic [...] Read more.

We conducted a prospective study of cancer patients to investigate the efficacy, quality of life, satisfaction, and safety of a home-based intermittent pneumatic compression (IPC) device during the maintenance phase of lower extremity lymphedema. This device has a unique mode designed to mimic the manual lymphatic drainage (MLD) technique and thereby gently facilitate lymphatic draining of proximal extremities. Thirty patients with stage 3 chronic secondary unilateral leg lymphedema in the maintenance phase underwent IPC and conventional compression therapy for 4 weeks at home. The participants were guided to use 1 h course (30 min of MLD-mimicking mode and 30 min of conventional mode) of IPC device twice a day for 4 weeks. We assessed the patients’ limb-volume measurement, quality of life (QOL), and satisfaction four times. There were no significant time-dependent interactions in the inter-limb volume difference ratio (V_ratio). In a subgroup analysis, participants who used the home-based IPC device and maintained their routine self-maintenance program of short-stretch bandages (group B, n = 21) showed a more significant decline in V_ratio than those who did not maintained their routine care (group A, n = 9). All scores of QOL decreased significantly after the intervention without subgroup difference. All participants were satisfied with the 4-week intervention. This study demonstrated that a home-based IPC device with an MLD-mimicking program is a useful option for maintaining the volume of limbs and improving the QOL of patients with stage 3 chronic leg lymphedema during the maintenance phase. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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17 pages, 63162 KiB

Open AccessSystematic Review

The Dose-Response Efficacy of Physical Training on Frailty Status and Physical Performance in Community-Dwelling Elderly: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

by Pei-Shan Li, Chia-Jung Hsieh, Eva Berthy Tallutondok and Hsuan-Ju Peng

Healthcare 2022, 10(3), 586; https://doi.org/10.3390/healthcare10030586 - 21 Mar 2022

Cited by 7 | Viewed by 2689

Abstract

Purpose: This systematic review and meta-analysis was conducted to explore the effect of physical training on frailty status and physical performance in the community dwelling elderly. Methods: We set keywords and used the Boolean operator to search the CEPS, CINAHL, Cochrane Library, PubMed, [...] Read more.

Purpose: This systematic review and meta-analysis was conducted to explore the effect of physical training on frailty status and physical performance in the community dwelling elderly. Methods: We set keywords and used the Boolean operator to search the CEPS, CINAHL, Cochrane Library, PubMed, MEDLINE, and EMBASE databases from inception to 10 August 2021. The search was limited to randomized controlled trials (RCTs) conducted within a five-year period. The Cochrane Collaboration bias assessment tool was used to assess article quality, and RevMan 5.4.1. software (Cochrane Training site based in London, UK) was used to conduct the meta-analysis. Results: Physical training was found to improve frailty status, physical performance, lower limb strength and balance. The best dose-response for physical training was 60 min per time, 2–3 times per week, for 3 months. Conclusion: Designing an appropriate physical training program can decrease the frailty score and increase physical performance in frail elderly in the community. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 2215 KiB

Open AccessArticle

Effect of Fresh Dendrobe Juice Consumption on Senile Habitual Constipation for Older People: A Four-Week Randomized Controlled Trial

by Yuchao Le, Shihua Cao, Mengxin Wang, Danni He, Yanfei Chen and Beiying Qian

Sustainability 2022, 14(6), 3656; https://doi.org/10.3390/su14063656 - 21 Mar 2022

Viewed by 1989

Abstract

Background: In Chinese medicine, it is believed that fresh dendrobe juice, which is mild in nature, can relieve the symptom of constipation. Methods: A pilot research design was conducted. Fifty-six older people with senile habitual constipation were recruited and randomly enrolled into control [...] Read more.

Background: In Chinese medicine, it is believed that fresh dendrobe juice, which is mild in nature, can relieve the symptom of constipation. Methods: A pilot research design was conducted. Fifty-six older people with senile habitual constipation were recruited and randomly enrolled into control or experimental groups, each with 28 people. The control group was offered water routinely in a day. In addition, the experimental group received 125 mL of dendrobe juice twice a day for four weeks. Quality of life for the old people was evaluated by the Patient Assessment of Constipation Quality of Life (PAC-QOL) Score and the symptom of constipation was assessed by Wexner score. Results: The four-week intervention brought significant performance improvement in all the measured parameters in the experimental group in comparison with the control group. These included significantly more frequency and shorter durations of defecation (p < 0.01, respectively), improved quality of life based on constipation score (PAC-QOL) (experimental group: 50.41 ± 3.46 vs. control group: 70.25 ± 2.35; p < 0.05), and improved score on the Wexner constipation scale (experimental group: 6.56 ± 0.89 vs. control group: 15.50 ± 0.64; p < 0.05). Conclusions: Fresh dendrobe beverage therapy is effective in improving stool frequency, reducing duration of defecation, and enhancing quality of life. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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12 pages, 292 KiB

Open AccessCase Report

Effect of Online Home-Based Training on Functional Capacity and Strength in Two CKD Patients: A Case Study

by Giulia Marrone, Elisa Grazioli, Eliana Tranchita, Attilio Parisi, Claudia Cerulli, Arianna Murri, Carlo Minganti, Manuela Di Lauro, Nicolò Piacentini, Leonarda Galiuto, Nicola Di Daniele and Annalisa Noce

Healthcare 2022, 10(3), 572; https://doi.org/10.3390/healthcare10030572 - 18 Mar 2022

Viewed by 2338

Abstract

Chronic kidney disease (CKD) is a clinical condition characterized by the loss of kidney function over time, as well as several complications affecting gastrointestinal, cardiovascular, and musculoskeletal systems. Physical exercise seems to induce positive adaptations in CKD patients, without side effects. Usually, these [...] Read more.

Chronic kidney disease (CKD) is a clinical condition characterized by the loss of kidney function over time, as well as several complications affecting gastrointestinal, cardiovascular, and musculoskeletal systems. Physical exercise seems to induce positive adaptations in CKD patients, without side effects. Usually, these patients show a reduced physical activity and physical performance. The aim of this case-report was to evaluate the effects of an online training protocol on functional capacity and on muscle mass, in CKD stage III patients. Methods: Two CKD (stage III according to KDIGO guidelines) participants (1 female, Patient A; 1 male, Patient B) were enrolled and they performed an online tailored-supervised combined training lasting 12 weeks, including multi-joint strength exercises using TheraBand and an aerobic session at 65–70% of the patients’ heart rate reserve. Results: Both patients showed an improving trend on functional capacity (6 min walking test: Patient A = +3%; Patient B = +5.3%) and on strength of the upper arms (handgrip strength test-right: Patient A = +13.4%; Patient B = +19.1%; handgrip strength test-left: Patient A = +42.8%; Patient B= +12.9%), as well as a reduction in inflammation and oxidative stress biomarkers. The protocol was feasible, and no side effects were evidenced. These case studies suggest that the online combined training can produce beneficial effects in CKD patients under conservative therapy, by reducing the CKD-related complications and improving the adherence to exercise of this population of patients, overcoming logistic barriers such as transportation, availability of facilities, and working and personal-life schedule. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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14 pages, 518 KiB

Open AccessArticle

The Institutional Factors Affecting the Growth of Korean Migrant Care Market and Sustainability in Long-Term Care Quality

by Hyun-Jung Kwon, Heaeun Oh and Jung Won Kong

Sustainability 2022, 14(6), 3366; https://doi.org/10.3390/su14063366 - 13 Mar 2022

Viewed by 2146

Abstract

Due to an increase in the ageing population, the migrant care market now includes new home-based long-term care (LTC) under the national long-term care insurance. This study underlines a perspective of the Korean migrant care market in terms of long-term care quality in [...] Read more.

Due to an increase in the ageing population, the migrant care market now includes new home-based long-term care (LTC) under the national long-term care insurance. This study underlines a perspective of the Korean migrant care market in terms of long-term care quality in South Korea. Thus, the study explored the institutional factors that restrict and promote the migrant care workers (MCWs). Two migrant workers groups were analysed: migrant care workers in home-based long-term care versus nursing hospitals. Designed as an in-depth policy-oriented content analysis, this study used three types of data including interviews with eight participants (MCWs, the nursing hospital manager, and the LTC home manager), organisational documents (employment eligibility criteria), and institutional texts (law, administration rules, etc.). Our results indicate that the factors hindering employment of MCWs in home-based LTC were visa status, qualification requirements (the National Qualified License), wage regulation policies, and social security obligations. A promoting factor was jobs that hired on an on-call basis. In conclusion, our findings suggest that the growth of the migration care market and sustainability in LTC quality depend on the policy directions of the Korean long-term care insurance. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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20 pages, 928 KiB

Open AccessArticle

Emergency Nursing-Care Patient Satisfaction Scale (Enpss): Development and Validation of a Patient Satisfaction Scale with Emergency Room Nursing

by Junpei Haruna, Naomi Minamoto, Mizue Shiromaru, Yukiko Taguchi, Natsuko Makino, Naoki Kanda and Hiromi Uchida

Healthcare 2022, 10(3), 518; https://doi.org/10.3390/healthcare10030518 - 12 Mar 2022

Cited by 1 | Viewed by 4312

Abstract

This study aimed to develop and validate an emergency nursing-care patient satisfaction scale to measure patient satisfaction with emergency room (ER) nursing. Patient satisfaction scales for ER nursing have been validated without considering the perspectives of the healthcare system or cultural background of [...] Read more.

This study aimed to develop and validate an emergency nursing-care patient satisfaction scale to measure patient satisfaction with emergency room (ER) nursing. Patient satisfaction scales for ER nursing have been validated without considering the perspectives of the healthcare system or cultural background of the country. Moreover, although nursing care is changing with COVID-19, no scale has been specifically designed to assess patient satisfaction with ER nursing. The study population included patients who visited five ERs in Japan (March to December 2021) (n = 135). The rating scales were provided to patients who visited the ER and gave consent, and the patients were asked to reply. In the process of validating the scale, exploratory and confirmatory factor analyses of the construct and criterion validity were conducted. The confirmatory factor analysis results showed a factorial structure consisting of four factors. The domain and summary scores demonstrated good-to-excellent internal reliability (Cronbach’s range = 0.81–0.89). This patient satisfaction scale was designed and validated from the perspective of the Japanese healthcare system and cultural backgrounds. This scale may be useful for developing assessments and interventions to improve patient satisfaction with ER nursing. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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16 pages, 5948 KiB

Open AccessArticle

Automated Cell Foreground–Background Segmentation with Phase-Contrast Microscopy Images: An Alternative to Machine Learning Segmentation Methods with Small-Scale Data

by Guochang Ye and Mehmet Kaya

Bioengineering 2022, 9(2), 81; https://doi.org/10.3390/bioengineering9020081 - 18 Feb 2022

Viewed by 3614

Abstract

Cell segmentation is a critical step for image-based experimental analysis. Existing cell segmentation methods are neither entirely automated nor perform well under basic laboratory microscopy. This study proposes an efficient and automated cell segmentation method involving morphological operations to automatically achieve cell segmentation [...] Read more.

Cell segmentation is a critical step for image-based experimental analysis. Existing cell segmentation methods are neither entirely automated nor perform well under basic laboratory microscopy. This study proposes an efficient and automated cell segmentation method involving morphological operations to automatically achieve cell segmentation for phase-contrast microscopes. Manual/visual counting of cell segmentation serves as the control group (156 images as ground truth) to evaluate the proposed method’s performance. The proposed technology’s adaptive performance is assessed at varying conditions, including artificial blurriness, illumination, and image size. Compared to the Trainable Weka Segmentation method, the Empirical Gradient Threshold method, and the ilastik segmentation software, the proposed method achieved better segmentation accuracy (dice coefficient: 90.07, IoU: 82.16%, and 6.51% as the average relative error on measuring cell area). The proposed method also has good reliability, even under unfavored imaging conditions at which manual labeling or human intervention is inefficient. Additionally, similar degrees of segmentation accuracy were confirmed when the ground truth data and the generated data from the proposed method were applied individually to train modified U-Net models (16848 images). These results demonstrated good accuracy and high practicality of the proposed cell segmentation method with phase-contrast microscopy image data. Full article

(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)

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