Bioengineering

15 pages, 1584 KiB

Open AccessArticle

Tuning Microelectrodes’ Impedance to Improve Fast Ripples Recording

by Hajar Mousavi, Gautier Dauly, Gabriel Dieuset, Amira El Merhie, Esma Ismailova, Fabrice Wendling and Mariam Al Harrach

Bioengineering 2024, 11(1), 102; https://doi.org/10.3390/bioengineering11010102 - 22 Jan 2024

Viewed by 1021

Abstract

Epilepsy is a chronic neurological disorder characterized by recurrent seizures resulting from abnormal neuronal hyperexcitability. In the case of pharmacoresistant epilepsy requiring resection surgery, the identification of the Epileptogenic Zone (EZ) is critical. Fast Ripples (FRs; 200–600 Hz) are one of the promising [...] Read more.

Epilepsy is a chronic neurological disorder characterized by recurrent seizures resulting from abnormal neuronal hyperexcitability. In the case of pharmacoresistant epilepsy requiring resection surgery, the identification of the Epileptogenic Zone (EZ) is critical. Fast Ripples (FRs; 200–600 Hz) are one of the promising biomarkers that can aid in EZ delineation. However, recording FRs requires physically small electrodes. These microelectrodes suffer from high impedance, which significantly impacts FRs’ observability and detection. In this study, we investigated the potential of a conductive polymer coating to enhance FR observability. We employed biophysical modeling to compare two types of microelectrodes: Gold (Au) and Au coated with the conductive polymer poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (Au/PEDOT:PSS). These electrodes were then implanted into the CA1 hippocampal neural network of epileptic mice to record FRs during epileptogenesis. The results showed that the polymer-coated electrodes had a two-order lower impedance as well as a higher transfer function amplitude and cut-off frequency. Consequently, FRs recorded with the PEDOT:PSS-coated microelectrode yielded significantly higher signal energy compared to the uncoated one. The PEDOT:PSS coating improved the observability of the recorded FRs and thus their detection. This work paves the way for the development of signal-specific microelectrode designs that allow for better targeting of pathological biomarkers. Full article

(This article belongs to the Special Issue Using Existing Medical Technologies to Solve and Improve Medical Challenges)

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17 pages, 2548 KiB

Open AccessArticle

A Dual Coordinate System Vertebra Landmark Detection Network with Sparse-to-Dense Vertebral Line Interpolation

by Han Zhang and Albert C. S. Chung

Bioengineering 2024, 11(1), 101; https://doi.org/10.3390/bioengineering11010101 - 22 Jan 2024

Viewed by 1004

Abstract

Precise surveillance and assessment of spinal disorders are important for improving health care and patient survival rates. The assessment of spinal disorders, such as scoliosis assessment, depends heavily on precise vertebra landmark localization. However, existing methods usually search for only a handful of [...] Read more.

Precise surveillance and assessment of spinal disorders are important for improving health care and patient survival rates. The assessment of spinal disorders, such as scoliosis assessment, depends heavily on precise vertebra landmark localization. However, existing methods usually search for only a handful of keypoints in a high-resolution image. In this paper, we propose the S2D-VLI VLDet network, a unified end-to-end vertebra landmark detection network for the assessment of scoliosis. The proposed network considers the spatially relevant information both from inside and between vertebrae. The new vertebral line interpolation method converts the training labels from sparse to dense, which can improve the network learning process and method performance. In addition, through the combined use of the Cartesian and polar coordinate systems in our method, the symmetric mean absolute percentage error (SMAPE) in scoliosis assessment can be reduced substantially. Specifically, as shown in the experiments, the SMAPE value decreases from 9.82 to 8.28. The experimental results indicate that our proposed approach is beneficial for estimating the Cobb angle and identifying landmarks in X-ray scans with low contrast. Full article

(This article belongs to the Section Biosignal Processing)

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15 pages, 856 KiB

Open AccessArticle

Predictive Model of Anxiety and Depression Perception in Multiple Sclerosis Patients: Possible Implications for Clinical Treatment

by María Cuerda-Ballester, Antonio Bustos, David Sancho-Cantus, David Martínez-Rubio, Jesús Privado, Jorge Alarcón-Jiménez, Carlos Villarón-Casales, Nieves de Bernardo, Esther Navarro Illana and José Enrique de la Rubia Ortí

Bioengineering 2024, 11(1), 100; https://doi.org/10.3390/bioengineering11010100 - 22 Jan 2024

Viewed by 1140

Abstract

Multiple Sclerosis (MS) is a neurodegenerative disease characterized by motor and non-motor symptoms, including emotional distress, anxiety, and depression. These emotional symptoms currently have a pharmacological treatment with limited effectiveness; therefore, it is necessary to delve into their relationship with other psychological, functional, [...] Read more.

Multiple Sclerosis (MS) is a neurodegenerative disease characterized by motor and non-motor symptoms, including emotional distress, anxiety, and depression. These emotional symptoms currently have a pharmacological treatment with limited effectiveness; therefore, it is necessary to delve into their relationship with other psychological, functional, or prefrontal alterations. Additionally, exploring non-pharmacological therapeutic alternatives that have shown benefits in addressing emotional distress in MS patients is essential. Aim: To establish a predictive model for the presence of anxiety and depression in MS patients, based on variables such as psychological well-being, functional activity, and prefrontal symptoms. Additionally, this study aimed to propose non-pharmacological therapeutic alternatives based on this model. Materials and Methods: A descriptive, observational, and cross-sectional study was conducted with a sample of 64 diagnosed MS patients who underwent functional and cognitive assessments using the following questionnaires and scales: Functional Activities Questionnaire (FAQ), Acceptance and Action Questionnaire (AAQ-II), Experiences Questionnaire (EQ), Self-Compassion Scale Short Form (SCS-SF), Beck Depression Inventory II (BDI-II), State-Trait Anxiety Inventory (STAI), and Prefrontal Symptoms Inventory (PSI). Results: The model showed an excellent fit to the data and indicated that psychological well-being was the most significant predictor of the criteria (β = −0.83), followed by functional activity (β = −0.18) and prefrontal symptoms (β = 0.15). The latter two are negatively related to psychological well-being (β = −0.16 and β = −0.75, respectively). Conclusions: Low psychological well-being is the variable that most significantly predicts the presence of anxiety and depression in MS patients, followed by functional activity and prefrontal alterations. Interventions based on mindfulness and acceptance are recommended, along with nutritional interventions such as antioxidant-enriched ketogenic diets and moderate group physical exercise. Full article

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18 pages, 6542 KiB

Open AccessArticle

The Evolution of Spinal Endoscopy: Design and Image Analysis of a Single-Use Digital Endoscope Versus Traditional Optic Endoscope

by Shih-Hao Cheng, Yen-Tsung Lin, Hsin-Tzu Lu, Yu-Chuan Tsuei, William Chu and Woei-Chyn Chu

Bioengineering 2024, 11(1), 99; https://doi.org/10.3390/bioengineering11010099 - 20 Jan 2024

Viewed by 1148

Abstract

Spinal endoscopy has evolved significantly since its inception, offering minimally invasive solutions for various spinal pathologies. This study introduces a promising innovation in spinal endoscopy—a single-use digital endoscope designed to overcome the drawbacks of traditional optic endoscopes. Traditional endoscopes, despite their utility, present [...] Read more.

Spinal endoscopy has evolved significantly since its inception, offering minimally invasive solutions for various spinal pathologies. This study introduces a promising innovation in spinal endoscopy—a single-use digital endoscope designed to overcome the drawbacks of traditional optic endoscopes. Traditional endoscopes, despite their utility, present challenges such as fragility, complex disinfection processes, weight issues, and susceptibility to mechanical malfunctions. The digital endoscope, with its disposable nature, lighter weight, and improved image quality, aims to enhance surgical procedures and patient safety. The digital endoscope system comprises a 30-degree 1000 × 1000 pixel resolution camera sensor with a 4.3 mm working channel, and LED light sources replacing optical fibers. The all-in-one touch screen tablet serves as the host computer, providing portability and simplified operation. Image comparisons between the digital and optic endoscopes revealed advantages in the form of increased field of view, lesser distortion, greater close-range resolution, and enhanced luminance. The single-use digital endoscope demonstrates great potential for revolutionizing spine endoscopic surgeries, offering convenience, safety, and superior imaging capabilities compared to traditional optic endoscopes. Full article

(This article belongs to the Section Biomedical Engineering and Biomaterials)

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14 pages, 1059 KiB

Open AccessArticle

Concurrent Validity of the Ergotex Device for Measuring Low Back Posture

by Marco A. García-Luna, Jose M. Jimenez-Olmedo, Basilio Pueo, Carmen Manchado and Juan M. Cortell-Tormo

Bioengineering 2024, 11(1), 98; https://doi.org/10.3390/bioengineering11010098 - 20 Jan 2024

Cited by 2 | Viewed by 872

Abstract

Highlighting the crucial role of monitoring and quantifying lumbopelvic rhythm for spinal curvature, the Ergotex IMU, a portable, lightweight, cost-effective, and energy-efficient technology, has been specifically designed for the pelvic and lumbar area. This study investigates the concurrent validity of the Ergotex device [...] Read more.

Highlighting the crucial role of monitoring and quantifying lumbopelvic rhythm for spinal curvature, the Ergotex IMU, a portable, lightweight, cost-effective, and energy-efficient technology, has been specifically designed for the pelvic and lumbar area. This study investigates the concurrent validity of the Ergotex device in measuring sagittal pelvic tilt angle. We utilized an observational, repeated measures design with healthy adult males (mean age: 39.3 ± 7.6 y, body mass: 82.2 ± 13.0 kg, body height: 179 ± 8 cm), comparing Ergotex with a 3D optical tracking system. Participants performed pelvic tilt movements in anterior, neutral, and posterior conditions. Statistical analysis included paired samples t-tests, Bland–Altman plots, and regression analysis. The findings show minimal systematic error (0.08° overall) and high agreement between the Ergotex and optical tracking, with most data points falling within limits of agreement of Bland–Altman plots (around ±2°). Significant differences were observed only in the anterior condition (0.35°, p < 0.05), with trivial effect sizes (ES = 0.08), indicating that these differences may not be clinically meaningful. The high Pearson’s correlation coefficients across conditions underscore a robust linear relationship between devices (r > 0.9 for all conditions). Regression analysis showed a standard error of estimate (SEE) of 1.1° with small effect (standardized SEE < 0.26 for all conditions), meaning that the expected average deviation from the true value is around 1°. These findings validate the Ergotex as an effective, portable, and cost-efficient tool for assessing sagittal pelvic tilt, with practical implications in clinical and sports settings where traditional methods might be impractical or costly. Full article

(This article belongs to the Special Issue Smartphone- or Tablet-Based Technologies for Balance and Gait Rehabilitation)

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31 pages, 13580 KiB

Open AccessArticle

Multi-Dimensional Validation of the Integration of Syntactic and Semantic Distance Measures for Clustering Fibromyalgia Patients in the Rheumatic Monitor Big Data Study

by Ayelet Goldstein, Yuval Shahar, Michal Weisman Raymond, Hagit Peleg, Eldad Ben-Chetrit, Arie Ben-Yehuda, Erez Shalom, Chen Goldstein, Shmuel Shay Shiloh and Galit Almoznino

Bioengineering 2024, 11(1), 97; https://doi.org/10.3390/bioengineering11010097 - 19 Jan 2024

Viewed by 1432

Abstract

This study primarily aimed at developing a novel multi-dimensional methodology to discover and validate the optimal number of clusters. The secondary objective was to deploy it for the task of clustering fibromyalgia patients. We present a comprehensive methodology that includes the use of [...] Read more.

This study primarily aimed at developing a novel multi-dimensional methodology to discover and validate the optimal number of clusters. The secondary objective was to deploy it for the task of clustering fibromyalgia patients. We present a comprehensive methodology that includes the use of several different clustering algorithms, quality assessment using several syntactic distance measures (the Silhouette Index (SI), Calinski–Harabasz index (CHI), and Davies–Bouldin index (DBI)), stability assessment using the adjusted Rand index (ARI), and the validation of the internal semantic consistency of each clustering option via the performance of multiple clustering iterations after the repeated bagging of the data to select multiple partial data sets. Then, we perform a statistical analysis of the (clinical) semantics of the most stable clustering options using the full data set. Finally, the results are validated through a supervised machine learning (ML) model that classifies the patients back into the discovered clusters and is interpreted by calculating the Shapley additive explanations (SHAP) values of the model. Thus, we refer to our methodology as the clustering, distance measures and iterative statistical and semantic validation (CDI-SSV) methodology. We applied our method to the analysis of a comprehensive data set acquired from 1370 fibromyalgia patients. The results demonstrate that the K-means was highly robust in the syntactic and the internal consistent semantics analysis phases and was therefore followed by a semantic assessment to determine the optimal number of clusters (k), which suggested k = 3 as a more clinically meaningful solution, representing three distinct severity levels. the random forest model validated the results by classification into the discovered clusters with high accuracy (AUC: 0.994; accuracy: 0.946). SHAP analysis emphasized the clinical relevance of "functional problems" in distinguishing the most severe condition. In conclusion, the CDI-SSV methodology offers significant potential for improving the classification of complex patients. Our findings suggest a classification system for different profiles of fibromyalgia patients, which has the potential to improve clinical care, by providing clinical markers for the evidence-based personalized diagnosis, management, and prognosis of fibromyalgia patients. Full article

(This article belongs to the Special Issue New Sight of Intelligent Algorithm Model and Medical Device in Bioengineering: Updates and Direction)

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15 pages, 2373 KiB

Open AccessArticle

Experimentally Validated Finite Element Analysis of Thoracic Spine Compression Fractures in a Porcine Model

by Sacha Guitteny, Cadence F. Lee and Farid Amirouche

Bioengineering 2024, 11(1), 96; https://doi.org/10.3390/bioengineering11010096 - 18 Jan 2024

Viewed by 1037

Abstract

Vertebral compression fractures (VCFs) occur in 1 to 1.5 million patients in the US each year and are associated with pain, disability, altered pulmonary function, secondary vertebral fracture, and increased mortality risk. A better understanding of VCFs and their management requires preclinical models [...] Read more.

Vertebral compression fractures (VCFs) occur in 1 to 1.5 million patients in the US each year and are associated with pain, disability, altered pulmonary function, secondary vertebral fracture, and increased mortality risk. A better understanding of VCFs and their management requires preclinical models that are both biomechanically analogous and accessible. We conducted a study using twelve spinal vertebrae (T12–T14) from porcine specimens. We created mathematical simulations of vertebral compression fractures (VCFs) using CT scans for reconstructing native anatomy and validated the results by conducting physical axial compression experiments. The simulations accurately predicted the behavior of the physical compressions. The coefficient of determination for stiffness was 0.71, the strength correlation was 0.88, and the failure of the vertebral bodies included vertical splitting on the lateral sides or horizontal separation in the anterior wall. This finite element method has important implications for the preventative, prognostic, and therapeutic management of VCFs. This study also supports the use of porcine specimens in orthopedic biomechanical research. Full article

(This article belongs to the Special Issue Computational Biomechanics, Volume II)

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16 pages, 524 KiB

Open AccessArticle

Dyadic and Individual Variation in 24-Hour Heart Rates of Cancer Patients and Their Caregivers

by Rajnish Kumar, Junhan Fu, Bengie L. Ortiz, Xiao Cao, Kerby Shedden and Sung Won Choi

Bioengineering 2024, 11(1), 95; https://doi.org/10.3390/bioengineering11010095 - 18 Jan 2024

Cited by 1 | Viewed by 1072

Abstract

Background: Twenty-four-hour heart rate (HR) integrates multiple physiological and psychological systems related to health and well-being, and can be continuously monitored in high temporal resolution over several days with wearable HR monitors. Using HR data from two independent datasets of cancer patients and [...] Read more.

Background: Twenty-four-hour heart rate (HR) integrates multiple physiological and psychological systems related to health and well-being, and can be continuously monitored in high temporal resolution over several days with wearable HR monitors. Using HR data from two independent datasets of cancer patients and their caregivers, we aimed to identify dyadic and individual patterns of 24 h HR variation and assess their relationship to demographic, environmental, psychological, and clinical variables of interest. Methods: a novel regularized approach to high-dimensional canonical correlation analysis (CCA) was used to identify factors reflecting dyadic and individual variation in the 24 h (circadian) HR trajectories of 430 people in 215 dyads, then regression analysis was used to relate these patterns to explanatory variables. Results: Four distinct factors of dyadic covariation in circadian HR were found, contributing approximately 7% to overall circadian HR variation. These factors, along with non-dyadic factors reflecting individual variation exhibited diverse and statistically robust patterns of association with explanatory variables of interest. Conclusions: Both dyadic and individual anomalies are present in the 24 h HR patterns of cancer patients and their caregivers. These patterns are largely synchronous, and their presence robustly associates with multiple explanatory variables. One notable finding is that higher mood scores in cancer patients correspond to an earlier HR nadir in the morning and higher HR during the afternoon. Full article

(This article belongs to the Special Issue Wearable Sensors and Measurement Systems for Human Physiology Monitoring)

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Graphical abstract

18 pages, 1362 KiB

Open AccessArticle

Research on Multimodal Fusion of Temporal Electronic Medical Records

by Moxuan Ma, Muyu Wang, Binyu Gao, Yichen Li, Jun Huang and Hui Chen

Bioengineering 2024, 11(1), 94; https://doi.org/10.3390/bioengineering11010094 - 18 Jan 2024

Viewed by 1195

Abstract

The surge in deep learning-driven EMR research has centered on harnessing diverse data forms. Yet, the amalgamation of diverse modalities within time series data remains an underexplored realm. This study probes a multimodal fusion approach, merging temporal and non-temporal clinical notes along with [...] Read more.

The surge in deep learning-driven EMR research has centered on harnessing diverse data forms. Yet, the amalgamation of diverse modalities within time series data remains an underexplored realm. This study probes a multimodal fusion approach, merging temporal and non-temporal clinical notes along with tabular data. We leveraged data from 1271 myocardial infarction and 6450 stroke inpatients at a Beijing tertiary hospital. Our dataset encompassed static, and time series note data, coupled with static and time series table data. The temporal data underwent a preprocessing phase, padding to a 30-day interval, and segmenting into 3-day sub-sequences. These were fed into a long short-term memory (LSTM) network for sub-sequence representation. Multimodal attention gates were implemented for both static and temporal subsequence representations, culminating in fused representations. An attention-backtracking module was introduced for the latter, adept at capturing enduring dependencies in temporal fused representations. The concatenated results were channeled into an LSTM to yield the ultimate fused representation. Initially, two note modalities were designated as primary modes, and subsequently, the proposed fusion model was compared with comparative models including recent models such as Crossformer. The proposed model consistently exhibited superior predictive prowess in both tasks. Removing the attention-backtracking module led to performance decline. The proposed model consistently shows excellent predictive capabilities in both tasks. The proposed method not only effectively integrates data from the four modalities, but also has a good understanding of how to handle irregular time series data and lengthy clinical texts. An effective method is provided, which is expected to be more widely used in multimodal medical data representation. Full article

(This article belongs to the Special Issue Machine Learning and Artificial Intelligence for Biomedical Applications)

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16 pages, 1215 KiB

Open AccessReview

Biophysical Control of the Glioblastoma Immunosuppressive Microenvironment: Opportunities for Immunotherapy

by Landon Teer, Kavitha Yaddanapudi and Joseph Chen

Bioengineering 2024, 11(1), 93; https://doi.org/10.3390/bioengineering11010093 - 18 Jan 2024

Viewed by 1644

Abstract

GBM is the most aggressive and common form of primary brain cancer with a dismal prognosis. Current GBM treatments have not improved patient survival, due to the propensity for tumor cell adaptation and immune evasion, leading to a persistent progression of the disease. [...] Read more.

GBM is the most aggressive and common form of primary brain cancer with a dismal prognosis. Current GBM treatments have not improved patient survival, due to the propensity for tumor cell adaptation and immune evasion, leading to a persistent progression of the disease. In recent years, the tumor microenvironment (TME) has been identified as a critical regulator of these pro-tumorigenic changes, providing a complex array of biomolecular and biophysical signals that facilitate evasion strategies by modulating tumor cells, stromal cells, and immune populations. Efforts to unravel these complex TME interactions are necessary to improve GBM therapy. Immunotherapy is a promising treatment strategy that utilizes a patient’s own immune system for tumor eradication and has exhibited exciting results in many cancer types; however, the highly immunosuppressive interactions between the immune cell populations and the GBM TME continue to present challenges. In order to elucidate these interactions, novel bioengineering models are being employed to decipher the mechanisms of immunologically “cold” GBMs. Additionally, these data are being leveraged to develop cell engineering strategies to bolster immunotherapy efficacy. This review presents an in-depth analysis of the biophysical interactions of the GBM TME and immune cell populations as well as the systems used to elucidate the underlying immunosuppressive mechanisms for improving current therapies. Full article

(This article belongs to the Section Biomedical Engineering and Biomaterials)

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21 pages, 5882 KiB

Open AccessArticle

A Cost-Effective Pichia pastoris Cell-Free System Driven by Glycolytic Intermediates Enables the Production of Complex Eukaryotic Proteins

by Jeffrey L. Schloßhauer, Srujan Kumar Dondapati, Stefan Kubick and Anne Zemella

Bioengineering 2024, 11(1), 92; https://doi.org/10.3390/bioengineering11010092 - 18 Jan 2024

Viewed by 1494

Abstract

Cell-free systems are particularly attractive for screening applications and the production of difficult-to-express proteins. However, the production of cell lysates is difficult to implement on a larger scale due to large time requirements, cultivation costs, and the supplementation of cell-free reactions with energy [...] Read more.

Cell-free systems are particularly attractive for screening applications and the production of difficult-to-express proteins. However, the production of cell lysates is difficult to implement on a larger scale due to large time requirements, cultivation costs, and the supplementation of cell-free reactions with energy regeneration systems. Consequently, the methylotrophic yeast Pichia pastoris, which is widely used in recombinant protein production, was utilized in the present study to realize cell-free synthesis in a cost-effective manner. Sensitive disruption conditions were evaluated, and appropriate signal sequences for translocation into ER vesicles were identified. An alternative energy regeneration system based on fructose-1,6-bisphosphate was developed and a ~2-fold increase in protein production was observed. Using a statistical experiment design, the optimal composition of the cell-free reaction milieu was determined. Moreover, functional ion channels could be produced, and a G-protein-coupled receptor was site-specifically modified using the novel cell-free system. Finally, the established P. pastoris cell-free protein production system can economically produce complex proteins for biotechnological applications in a short time. Full article

(This article belongs to the Special Issue Yeast Biotechnology: Current Challenges and Future Directions)

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13 pages, 2984 KiB

Open AccessCommunication

Mini-Implant Insertion Using a Guide Manufactured with Computer-Aided Design and Computer-Aided Manufacturing in an Adolescent Patient Suffering from Tooth Eruption Disturbance

by Christina Weismann, Kathrin Heise, Maite Aretxabaleta, Marcel Cetindis, Bernd Koos and Matthias C. Schulz

Bioengineering 2024, 11(1), 91; https://doi.org/10.3390/bioengineering11010091 - 18 Jan 2024

Viewed by 956

Abstract

Due to dental diseases, anatomical restrictions, and mixed dentition, the reduction in the number of teeth and the displacement of tooth germs pose challenges in orthodontic treatment, limiting anchorage options. The presented case demonstrates an advanced treatment solution using digital CAD/CAM-technologies and medical [...] Read more.

Due to dental diseases, anatomical restrictions, and mixed dentition, the reduction in the number of teeth and the displacement of tooth germs pose challenges in orthodontic treatment, limiting anchorage options. The presented case demonstrates an advanced treatment solution using digital CAD/CAM-technologies and medical imaging for the creation of a mini-implant template. A 12-year-old male patient experiencing delayed tooth eruption, multiple impacted germs, and maxillary constriction underwent intraoral scanning and CBCT. Utilizing coDiagnostiX^TM Version 10.2 software, the acquired data were merged to determine the mini-implant placement and to design the template. The template was then manufactured through stereolithography using surgical-guide material. Mini-implants were inserted using the produced appliance, enabling safe insertion by avoiding vital structures. Surgically exposed displaced teeth were aligned using a Hyrax screw appliance anchored on the mini-implants for rapid palatal expansion (RPE) and subsequently used as fixed orthodontics to align impacted teeth. The screw was activated daily for 10 weeks, resulting in a 7 mm posterior and 5 mm anterior maxillary transversal increase. Skeletal anchorage facilitated simultaneous RPE and tooth alignment, ensuring accuracy, patient safety, and appliance stability. The presented case shows a scenario in which computer-aided navigation for mini-implant positioning can enhance precision and versatility in challenging anatomical cases. Full article

(This article belongs to the Special Issue Recent Advances in the Treatment of Dental Diseases)

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16 pages, 4681 KiB

Open AccessArticle

Systemic Lupus Erythematosus: How Machine Learning Can Help Distinguish between Infections and Flares

by Iciar Usategui, Yoel Arroyo, Ana María Torres, Julia Barbado and Jorge Mateo

Bioengineering 2024, 11(1), 90; https://doi.org/10.3390/bioengineering11010090 - 17 Jan 2024

Cited by 2 | Viewed by 1208

Abstract

Systemic Lupus Erythematosus (SLE) is a multifaceted autoimmune ailment that impacts multiple bodily systems and manifests with varied clinical manifestations. Early detection is considered the most effective way to save patients’ lives, but detecting severe SLE activity in its early stages is proving [...] Read more.

Systemic Lupus Erythematosus (SLE) is a multifaceted autoimmune ailment that impacts multiple bodily systems and manifests with varied clinical manifestations. Early detection is considered the most effective way to save patients’ lives, but detecting severe SLE activity in its early stages is proving to be a formidable challenge. Consequently, this work advocates the use of Machine Learning (ML) algorithms for the diagnosis of SLE flares in the context of infections. In the pursuit of this research, the Random Forest (RF) method has been employed due to its performance attributes. With RF, our objective is to uncover patterns within the patient data. Multiple ML techniques have been scrutinized within this investigation. The proposed system exhibited around a 7.49% enhancement in accuracy when compared to k-Nearest Neighbors (KNN) algorithm. In contrast, the Support Vector Machine (SVM), Binary Linear Discriminant Analysis (BLDA), Decision Trees (DT) and Linear Regression (LR) methods demonstrated inferior performance, with respective values around 81%, 78%, 84% and 69%. It is noteworthy that the proposed method displayed a superior area under the curve (AUC) and balanced accuracy (both around 94%) in comparison to other ML approaches. These outcomes underscore the feasibility of crafting an automated diagnostic support method for SLE patients grounded in ML systems. Full article

(This article belongs to the Special Issue Machine Learning and Medicine: The Interface of Medicine, Engineering and Artificial Intelligence)

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17 pages, 737 KiB

Open AccessArticle

ECG Forecasting System Based on Long Short-Term Memory

by Henriques Zacarias, João Alexandre Lôbo Marques, Virginie Felizardo, Mehran Pourvahab and Nuno M. Garcia

Bioengineering 2024, 11(1), 89; https://doi.org/10.3390/bioengineering11010089 - 17 Jan 2024

Viewed by 1133

Abstract

Worldwide, cardiovascular diseases are some of the primary causes of death; yet the early detection and diagnosis of such diseases have the potential to save many lives. Technological means of detection are becoming increasingly essential and numerous techniques have been created for this [...] Read more.

Worldwide, cardiovascular diseases are some of the primary causes of death; yet the early detection and diagnosis of such diseases have the potential to save many lives. Technological means of detection are becoming increasingly essential and numerous techniques have been created for this purpose, such as forecasting. Of these techniques, the time series forecasting technique seeks to predict future events. The long-term time series forecasting of physiological data could assist medical professionals in predicting and treating patients based on very early diagnosis. This article presents a model that utilizes a deep learning technique to predict long-term ECG signals. The forecasting model can learn signals’ nonlinearity, nonstationarity, and complexity based on a long short-term memory architecture. However, this is not a trivial task as the correct forecasting of a signal that closely resembles the original complex signal’s structure and behavior while minimizing any differences in amplitude continues to pose challenges. To achieve this goal, we used a dataset available on the Physio net database, called MIT-BIH, with 48 ECG recordings of 30 min each. The developed model starts with pre-processing to reduce interference in the original signals, then applies a deep learning algorithm, based on a long short-term memory (LTSM) neural network with two hidden layers. Next, we applied the root mean square error (RMSE) and mean absolute error (MAE) metrics to evaluate the performance of the model and obtained an average RMSE of

0.0070 \pm 0.0028

and an average MAE of

0.0522 \pm 0.0098

across all simulations. The results indicate that the proposed LSTM model is a promising technique for ECG forecasting, considering the trends of the changes in the original data series, most notably in R-peak amplitude. Given the model’s accuracy and the features of the physiological signals, the system could be used to improve existing predictive healthcare systems for cardiovascular monitoring. Full article

(This article belongs to the Section Biosignal Processing)

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15 pages, 300 KiB

Open AccessArticle

Hidden Markov Model for Parkinson’s Disease Patients Using Balance Control Data

by Khaled Safi, Wael Hosny Fouad Aly, Hassan Kanj, Tarek Khalifa, Mouna Ghedira and Emilie Hutin

Bioengineering 2024, 11(1), 88; https://doi.org/10.3390/bioengineering11010088 - 17 Jan 2024

Viewed by 874

Abstract

Understanding the behavior of the human postural system has become a very attractive topic for many researchers. This system plays a crucial role in maintaining balance during both stationary and moving states. Parkinson’s disease (PD) is a prevalent degenerative movement disorder that significantly [...] Read more.

Understanding the behavior of the human postural system has become a very attractive topic for many researchers. This system plays a crucial role in maintaining balance during both stationary and moving states. Parkinson’s disease (PD) is a prevalent degenerative movement disorder that significantly impacts human stability, leading to falls and injuries. This research introduces an innovative approach that utilizes a hidden Markov model (HMM) to distinguish healthy individuals and those with PD. Interestingly, this methodology employs raw data obtained from stabilometric signals without any preprocessing. The dataset used for this study comprises 60 subjects divided into healthy and PD patients. Impressively, the proposed method achieves an accuracy rate of up to 98% in effectively differentiating healthy subjects from those with PD. Full article

(This article belongs to the Section Biosignal Processing)

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21 pages, 4043 KiB

Open AccessArticle

Joint Stress Analysis of the Navicular Bone of the Horse and Its Implications for Navicular Disease

by Franz Konstantin Fuss

Bioengineering 2024, 11(1), 87; https://doi.org/10.3390/bioengineering11010087 - 17 Jan 2024

Viewed by 836

Abstract

The horse’s navicular bone is located inside the hoof between the deep flexor tendon (DDFT) and the middle and end phalanges. The aim of this study was to calculate the stress distribution across the articular surface of the navicular bone and to investigate [...] Read more.

The horse’s navicular bone is located inside the hoof between the deep flexor tendon (DDFT) and the middle and end phalanges. The aim of this study was to calculate the stress distribution across the articular surface of the navicular bone and to investigate how morphological variations of the navicular bone affect the joint forces and stress distribution. Joint forces normalised to the DDFT force were calculated from force and moment equilibria from morphological parameters determined on mediolateral radiographs. The stress distribution on the articular surface was determined from the moment equilibrium of the stress vectors around the centre of pressure. The ratio of the proximal to the distal moment arms of the DDFT, as well as the proximo-distal position and extent of the navicular bone, individually or in combination, have a decisive influence on the position and magnitude of the joint force and the stress distribution. If the moment arms are equal and the bone is more proximal, the joint force vector originates from the centre of the joint surface and the joint load is evenly distributed. However, in a more distal position with a longer distal moment arm, the joint force is close to the distal edge, where the joint stress reaches its peak. Degenerative navicular disease, which causes lameness and pathological changes in the distal portion of the bone in sport horses, is likely to be more severe in horses with wedge-shaped navicular bones than in horses with square bones. Full article

(This article belongs to the Section Biomechanics and Sports Medicine)

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19 pages, 321 KiB

Open AccessReview

Stroke Lesion Segmentation and Deep Learning: A Comprehensive Review

by Mishaim Malik, Benjamin Chong, Justin Fernandez, Vickie Shim, Nikola Kirilov Kasabov and Alan Wang

Bioengineering 2024, 11(1), 86; https://doi.org/10.3390/bioengineering11010086 - 17 Jan 2024

Viewed by 1367

Abstract

Stroke is a medical condition that affects around 15 million people annually. Patients and their families can face severe financial and emotional challenges as it can cause motor, speech, cognitive, and emotional impairments. Stroke lesion segmentation identifies the stroke lesion visually while providing [...] Read more.

Stroke is a medical condition that affects around 15 million people annually. Patients and their families can face severe financial and emotional challenges as it can cause motor, speech, cognitive, and emotional impairments. Stroke lesion segmentation identifies the stroke lesion visually while providing useful anatomical information. Though different computer-aided software are available for manual segmentation, state-of-the-art deep learning makes the job much easier. This review paper explores the different deep-learning-based lesion segmentation models and the impact of different pre-processing techniques on their performance. It aims to provide a comprehensive overview of the state-of-the-art models and aims to guide future research and contribute to the development of more robust and effective stroke lesion segmentation models. Full article

(This article belongs to the Section Biosignal Processing)

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16 pages, 1181 KiB

Open AccessArticle

Pull-Up Performance Is Affected Differently by the Muscle Contraction Regimens Practiced during Training among Climbers

by Laurent Vigouroux and Marine Devise

Bioengineering 2024, 11(1), 85; https://doi.org/10.3390/bioengineering11010085 - 17 Jan 2024

Viewed by 1129

Abstract

Sport climbing performance is highly related to upper limb strength and endurance. Although finger-specific methods are widely analyzed in the literature, no study has yet quantified the effects of arm-specific training. This study aims to compare the effects of three types of training [...] Read more.

Sport climbing performance is highly related to upper limb strength and endurance. Although finger-specific methods are widely analyzed in the literature, no study has yet quantified the effects of arm-specific training. This study aims to compare the effects of three types of training involving different muscle contraction regimens on climbers’ pull-up capabilities. Thirty advanced to high-elite climbers were randomly divided into four groups: eccentric (ECC; n = 8), isometric (ISO; n = 7), plyometric (PLYO; n = 6), and no specific training (CTRL; n = 9), and they participated in a 5-week training, twice a week, focusing on pull-ups on hangboard. Pre- and post-training assessments were conducted using a force-sensing hangboard, analyzing force, velocity, power, and muscle work during three pull-up exercises: pull-ups at body weight under different conditions, incremental weighted pull-ups, and an exhaustion test. The CTRL group showed no change. Maximum strength improved in all three training groups (from +2.2 ± 3.6% to +5.0 ± 2.4%; p < 0.001); velocity variables enhanced in the ECC and PLYO groups (from +5.7 ± 7.4 to +28.7 ± 42%; p < 0.05), resulting in greater power; amplitude increased in the ECC group; and muscle work increased in the PLYO group (+21.9 ± 16.6%; p = 0.015). A 5-week training period effectively enhanced arm performance, but outcomes were influenced by the chosen muscle contraction regimens and initial individual characteristics. Full article

(This article belongs to the Special Issue Biomechanics and Sports Medicine in Sport Climbing, Featuring Selected Contributions Presented at the 6th IRCRA Congress 2023)

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20 pages, 3056 KiB

Open AccessArticle

Toward Digital Twin Development for Implant Placement Planning Using a Parametric Reduced-Order Model

by Seokho Ahn, Jaesung Kim, Seokheum Baek, Cheolyong Kim, Hyunsoo Jang and Seojin Lee

Bioengineering 2024, 11(1), 84; https://doi.org/10.3390/bioengineering11010084 - 16 Jan 2024

Viewed by 957

Abstract

Real-time stress distribution data for implants and cortical bones can aid in determining appropriate implant placement plans and improving the post-placement success rate. This study aims to achieve these goals via a parametric reduced-order model (ROM) method based on stress distribution data obtained [...] Read more.

Real-time stress distribution data for implants and cortical bones can aid in determining appropriate implant placement plans and improving the post-placement success rate. This study aims to achieve these goals via a parametric reduced-order model (ROM) method based on stress distribution data obtained using finite element analysis. For the first time, the finite element analysis cases for six design variables related to implant placement were determined simultaneously via the design of experiments and a sensitivity analysis. The differences between the minimum and maximum stresses obtained for the six design variables confirm that the order of their influence is: Young’s modulus of the cancellous bone > implant thickness > front–rear angle > left–right angle > implant length. Subsequently, a one-dimensional (1-D) CAE solver was created using the ROM with the highest coefficient of determination and prognosis accuracy. The proposed 1-D CAE solver was loaded into the Ondemand3D program and used to implement a digital twin that can aid with dentists’ decision making by combining various tooth image data to evaluate and visualize the adequacy of the placement plan in real time. Because the proposed ROM method does not rely entirely on the doctor’s judgment, it ensures objectivity. Full article

(This article belongs to the Special Issue Dental Implant Reconstruction and Biomechanical Evaluation)

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14 pages, 2878 KiB

Open AccessArticle

Enzymatically Driven Mineralization of a Calcium–Polyphosphate Bleaching Gel

by Mariangela Ivette Guanipa Ortiz, Yendry Regina Corrales Ureña, Flávio Henrique Baggio Aguiar, Débora Alves Nunes Leite Lima and Klaus Rischka

Bioengineering 2024, 11(1), 83; https://doi.org/10.3390/bioengineering11010083 - 16 Jan 2024

Viewed by 1047

Abstract

To examined alkaline phosphatase enzyme (ALP) activity and the effects of incorporating it in the thickener solution of a hydrogen-peroxide-based bleaching gel containing calcium-polyphosphate (CaPP) on the orthophosphate (PO₄³⁻) levels, bleaching effectiveness, and enamel microhardness. ALP activity was assessed at [...] Read more.

To examined alkaline phosphatase enzyme (ALP) activity and the effects of incorporating it in the thickener solution of a hydrogen-peroxide-based bleaching gel containing calcium-polyphosphate (CaPP) on the orthophosphate (PO₄³⁻) levels, bleaching effectiveness, and enamel microhardness. ALP activity was assessed at different pH levels and H₂O₂ concentrations, and in H₂O- and Tris-based thickeners. Circular dichroism (CD) was used to examine the ALP secondary structure in water-, Tris-, or H₂O₂-based mediums. The PO₄³⁻ levels were evaluated in thickeners with and without ALP. Enamel/dentin specimens were allocated into the following groups: control (without bleaching); commercial (Whiteness-HP-Maxx); Exp-H (H₂O-based); CaPP-H; ALP-H (CaPP+ALP); Exp-T (Tris-based); CaPP-T; and ALP-T (CaPP+ALP). Color changes (ΔE/ΔE00) and the bleaching index (ΔWID) were calculated, and surface (SMH) and cross-sectional microhardness (CSMH) were assessed. The two-way ANOVA and Tukey’s post-hoc tests were used to compare ALP and PO₄³⁻ levels; generalized linear models were used to examine: ΔE/ΔE00/SMH/CSMH; and Kruskal–Wallis and Dunn’s tests were used for ΔWID (α = 5%). The ALP activity was higher at pH 9, lower in H₂O₂-based mediums, and similar in both thickeners. The CD-spectra indicated denaturation of the enzyme upon contact with H₂O₂. The PO₄³⁻ levels were higher after incorporating ALP, and the ΔE/ΔE00/ΔWID were comparable among bleached groups. SMH was lower after bleaching in Exp-H, while CSMH was highest in ALP-T. Full article

(This article belongs to the Special Issue Oral Health and Dental Restoration and Regeneration)

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11 pages, 1093 KiB

Open AccessArticle

Reliability of Panoramic Ultrasound in Assessing Rectus Femoris Size, Shape, and Brightness: An Inter-Examiner Study

by Jorge Buffet-García, Gustavo Plaza-Manzano, Umut Varol, Marta Ríos-León, María José Díaz-Arribas, Javier Álvarez-González, Sandra Sánchez-Jorge and Juan Antonio Valera-Calero

Bioengineering 2024, 11(1), 82; https://doi.org/10.3390/bioengineering11010082 - 15 Jan 2024

Viewed by 957

Abstract

Extended field-of-view ultrasound (US) imaging, also known as panoramic US, represents a technical advance that allows for complete visualization of large musculoskeletal structures, which are often limited in conventional 2D US images. Currently, there is no evidence examining whether the experience of examiners [...] Read more.

Extended field-of-view ultrasound (US) imaging, also known as panoramic US, represents a technical advance that allows for complete visualization of large musculoskeletal structures, which are often limited in conventional 2D US images. Currently, there is no evidence examining whether the experience of examiners influences muscle shape deformations that may arise during the glide of the transducer in panoramic US acquisition. As no studies using panoramic US have analyzed whether two examiners with differing levels of experience might obtain varying scores in size, shape, or brightness during the US assessment of the rectus femoris muscle, our aim was to analyze the inter-examiner reliability of panoramic US imaging acquisition in determining muscle size, shape, and brightness between two examiners. Additionally, we sought to investigate whether the examiners’ experience plays a significant role in muscle deformations during imaging acquisition by assessing score differences. Shape (circularity, aspect ratio, and roundness), size (cross-sectional area and perimeter), and brightness (mean echo intensity) were analyzed in 39 volunteers. Intraclass correlation coefficients (ICCs), standard error of measurements (SEM), minimal detectable changes (MDC), and coefficient of absolute errors (CAE%) were calculated. All parameters evaluated showed no significant differences between the two examiners (p > 0.05). Panoramic US proved to be reliable, regardless of examiner experience, as no deformations were observed. Further research is needed to corroborate the validity of panoramic US by comparing this method with gold standard techniques. Full article

(This article belongs to the Section Regenerative Engineering)

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13 pages, 3281 KiB

Open AccessArticle

Implementation of Fluorescent-Protein-Based Quantification Analysis in L-Form Bacteria

by Di Tian, Yiyuan Liu, Yueyue Zhang, Yunfei Liu, Yang Xia, Boying Xu, Jian Xu and Tetsuya Yomo

Bioengineering 2024, 11(1), 81; https://doi.org/10.3390/bioengineering11010081 - 15 Jan 2024

Viewed by 1076

Abstract

Cell-wall-less (L-form) bacteria exhibit morphological complexity and heterogeneity, complicating quantitative analysis of them under internal and external stimuli. Stable and efficient labeling is needed for the fluorescence-based quantitative cell analysis of L-forms during growth and proliferation. Here, we evaluated the expression of multiple [...] Read more.

Cell-wall-less (L-form) bacteria exhibit morphological complexity and heterogeneity, complicating quantitative analysis of them under internal and external stimuli. Stable and efficient labeling is needed for the fluorescence-based quantitative cell analysis of L-forms during growth and proliferation. Here, we evaluated the expression of multiple fluorescent proteins (FPs) under different promoters in the Bacillus subtilis L-form strain LR2 using confocal microscopy and imaging flow cytometry. Among others, P_ylb-derived NBP3510 showed a superior performance for inducing several FPs including EGFP and mKO2 in both the wild-type and L-form strains. Moreover, NBP3510 was also active in Escherichia coli and its L-form strain NC-7. Employing these established FP-labeled strains, we demonstrated distinct morphologies in the L-form bacteria in a quantitative manner. Given cell-wall-deficient bacteria are considered protocell and synthetic cell models, the generated cell lines in our work could be valuable for L-form-based research. Full article

(This article belongs to the Section Cellular and Molecular Bioengineering)

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17 pages, 14873 KiB

Open AccessArticle

Features of Vat-Photopolymerized Masters for Microfluidic Device Manufacturing

by Maria Laura Gatto, Paolo Mengucci, Monica Mattioli-Belmonte, Daniel Munteanu, Roberto Nasini, Emanuele Tognoli, Lucia Denti and Andrea Gatto

Bioengineering 2024, 11(1), 80; https://doi.org/10.3390/bioengineering11010080 - 15 Jan 2024

Cited by 1 | Viewed by 872

Abstract

The growing interest in advancing microfluidic devices for manipulating fluids within micrometer-scale channels has prompted a shift in manufacturing practices, moving from single-component production to medium-size batches. This transition arises due to the impracticality of lab-scale manufacturing methods in accommodating the increased demand. [...] Read more.

The growing interest in advancing microfluidic devices for manipulating fluids within micrometer-scale channels has prompted a shift in manufacturing practices, moving from single-component production to medium-size batches. This transition arises due to the impracticality of lab-scale manufacturing methods in accommodating the increased demand. This experimental study focuses on the design of master benchmarks 1–5, taking into consideration critical parameters such as rib width, height, and the relative width-to-height ratio. Notably, benchmarks 4 and 5 featured ribs that were strategically connected to the inlet, outlet, and reaction chamber of the master, enhancing their utility for subsequent replica production. Vat photopolymerization was employed for the fabrication of benchmarks 1–5, while replicas of benchmarks 4 and 5 were generated through polydimethylsiloxane casting. Dimensional investigations of the ribs and channels in both the master benchmarks and replicas were conducted using an optical technique validated through readability analysis based on the Michelson global contrast index. The primary goal was to evaluate the potential applicability of vat photopolymerization technology for efficiently producing microfluidic devices through a streamlined production process. Results indicate that the combination of vat photopolymerization followed by replication is well suited for achieving a minimum rib size of 25 µm in width and an aspect ratio of 1:12 for the master benchmark. Full article

(This article belongs to the Special Issue Microfluidics and Sensor Technology in Biomedical Engineering)

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21 pages, 4117 KiB

Open AccessArticle

COVID-19 Detection and Diagnosis Model on CT Scans Based on AI Techniques

by Maria-Alexandra Zolya, Cosmin Baltag, Dragoș-Vasile Bratu, Simona Coman and Sorin-Aurel Moraru

Bioengineering 2024, 11(1), 79; https://doi.org/10.3390/bioengineering11010079 - 14 Jan 2024

Viewed by 1106

Abstract

The end of 2019 could be mounted in a rudimentary framing of a new medical problem, which globally introduces into the discussion a fulminant outbreak of coronavirus, consequently spreading COVID-19 that conducted long-lived and persistent repercussions. Hence, the theme proposed to be solved [...] Read more.

The end of 2019 could be mounted in a rudimentary framing of a new medical problem, which globally introduces into the discussion a fulminant outbreak of coronavirus, consequently spreading COVID-19 that conducted long-lived and persistent repercussions. Hence, the theme proposed to be solved arises from the field of medical imaging, where a pulmonary CT-based standardized reporting system could be addressed as a solution. The core of it focuses on certain impediments such as the overworking of doctors, aiming essentially to solve a classification problem using deep learning techniques, namely, if a patient suffers from COVID-19, viral pneumonia, or is healthy from a pulmonary point of view. The methodology’s approach was a meticulous one, denoting an empirical character in which the initial stage, given using data processing, performs an extraction of the lung cavity from the CT scans, which is a less explored approach, followed by data augmentation. The next step is comprehended by developing a CNN in two scenarios, one in which there is a binary classification (COVID and non-COVID patients), and the other one is represented by a three-class classification. Moreover, viral pneumonia is addressed. To obtain an efficient version, architectural changes were gradually made, involving four databases during this process. Furthermore, given the availability of pre-trained models, the transfer learning technique was employed by incorporating the linear classifier from our own convolutional network into an existing model, with the result being much more promising. The experimentation encompassed several models including MobileNetV1, ResNet50, DenseNet201, VGG16, and VGG19. Through a more in-depth analysis, using the CAM technique, MobilneNetV1 differentiated itself via the detection accuracy of possible pulmonary anomalies. Interestingly, this model stood out as not being among the most used in the literature. As a result, the following values of evaluation metrics were reached: loss (0.0751), accuracy (0.9744), precision (0.9758), recall (0.9742), AUC (0.9902), and F1 score (0.9750), from 1161 samples allocated for each of the three individual classes. Full article

(This article belongs to the Special Issue Artificial Intelligence in Biomedical Diagnosis and Prognosis)

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21 pages, 7235 KiB

Open AccessArticle

Photobiomodulation Therapy Improves Repair of Bone Defects Filled by Inorganic Bone Matrix and Fibrin Heterologous Biopolymer

by Maria Fernanda Rossi Vigliar, Lais Furlaneto Marega, Marco Antonio Hungaro Duarte, Murilo Priori Alcalde, Marcelie Priscila de Oliveira Rosso, Rui Seabra Ferreira Junior, Benedito Barraviera, Carlos Henrique Bertoni Reis, Daniela Vieira Buchaim and Rogerio Leone Buchaim

Bioengineering 2024, 11(1), 78; https://doi.org/10.3390/bioengineering11010078 - 13 Jan 2024

Viewed by 1085

Abstract

Biomaterials are used extensively in graft procedures to correct bone defects, interacting with the body without causing adverse reactions. The aim of this pre-clinical study was to analyze the effects of photobiomodulation therapy (PBM) with the use of a low-level laser in the [...] Read more.

Biomaterials are used extensively in graft procedures to correct bone defects, interacting with the body without causing adverse reactions. The aim of this pre-clinical study was to analyze the effects of photobiomodulation therapy (PBM) with the use of a low-level laser in the repair process of bone defects filled with inorganic matrix (IM) associated with heterologous fibrin biopolymer (FB). A circular osteotomy of 4 mm in the left tibia was performed in 30 Wistar male adult rats who were randomly divided into three groups: G1 = IM + PBM, G2 = IM + FB and G3 = IM + FB + PBM. PBM was applied at the time of the experimental surgery and three times a week, on alternate days, until euthanasia, with 830 nm wavelength, in two points of the operated site. Five animals from each group were euthanized 14 and 42 days after surgery. In the histomorphometric analysis, the percentage of neoformed bone tissue in G3 (28.4% ± 2.3%) was higher in relation to G1 (24.1% ± 2.91%) and G2 (22.2% ± 3.11%) at 14 days and at 42 days, the percentage in G3 (35.1% ± 2.55%) was also higher in relation to G1 (30.1% ± 2.9%) and G2 (31.8% ± 3.12%). In the analysis of the birefringence of collagen fibers, G3 showed a predominance of birefringence between greenish-yellow in the neoformed bone tissue after 42 days, differing from the other groups with a greater presence of red-orange fibers. Immunohistochemically, in all experimental groups, it was possible to observe immunostaining for osteocalcin (OCN) near the bone surface of the margins of the surgical defect and tartrate-resistant acid phosphatase (TRAP) bordering the newly formed bone tissue. Therefore, laser photobiomodulation therapy contributed to improving the bone repair process in tibial defects filled with bovine biomaterial associated with fibrin biopolymer derived from snake venom. Full article

(This article belongs to the Special Issue Biomaterials for Cartilage and Bone Tissue Engineering)

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23 pages, 1640 KiB

Open AccessArticle

Optimizing RNNs for EMG Signal Classification: A Novel Strategy Using Grey Wolf Optimization

by Marcos Aviles, José Manuel Alvarez-Alvarado, Jose-Billerman Robles-Ocampo , Perla Yazmín Sevilla-Camacho and Juvenal Rodríguez-Reséndiz

Bioengineering 2024, 11(1), 77; https://doi.org/10.3390/bioengineering11010077 - 13 Jan 2024

Viewed by 915

Abstract

Accurate classification of electromyographic (EMG) signals is vital in biomedical applications. This study evaluates different architectures of recurrent neural networks for the classification of EMG signals associated with five movements of the right upper extremity. A Butterworth filter was implemented for signal preprocessing, [...] Read more.

Accurate classification of electromyographic (EMG) signals is vital in biomedical applications. This study evaluates different architectures of recurrent neural networks for the classification of EMG signals associated with five movements of the right upper extremity. A Butterworth filter was implemented for signal preprocessing, followed by segmentation into 250 ms windows, with an overlap of 190 ms. The resulting dataset was divided into training, validation, and testing subsets. The Grey Wolf Optimization algorithm was applied to the gated recurrent unit (GRU), long short-term memory (LSTM) architectures, and bidirectional recurrent neural networks. In parallel, a performance comparison with support vector machines (SVMs) was performed. The results obtained in the first experimental phase revealed that all the RNN networks evaluated reached a 100% accuracy, standing above the 93% achieved by the SVM. Regarding classification speed, LSTM ranked as the fastest architecture, recording a time of 0.12 ms, followed by GRU with 0.134 ms. Bidirectional recurrent neural networks showed a response time of 0.2 ms, while SVM had the longest time at 2.7 ms. In the second experimental phase, a slight decrease in the accuracy of the RNN models was observed, standing at 98.46% for LSTM, 96.38% for GRU, and 97.63% for the bidirectional network. The findings of this study highlight the effectiveness and speed of recurrent neural networks in the EMG signal classification task. Full article

(This article belongs to the Special Issue Bioengineering of the Motor System)

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13 pages, 6394 KiB

Open AccessArticle

Flow Diverter Performance Comparison of Different Wire Materials for Effective Intracranial Aneurysm Treatment

by Yeo Jin Jun, Doo Kyung Hwang, Hee Sun Lee, Byung Moon Kim and Ki Dong Park

Bioengineering 2024, 11(1), 76; https://doi.org/10.3390/bioengineering11010076 - 12 Jan 2024

Viewed by 1083

Abstract

A flow diverter (FD) is an effective method for treating wide-necked intracranial aneurysms by inducing hemodynamic changes in aneurysms. However, the procedural technique remains challenging, and it is often not performed properly in many cases of deployment or placements. In this study, three [...] Read more.

A flow diverter (FD) is an effective method for treating wide-necked intracranial aneurysms by inducing hemodynamic changes in aneurysms. However, the procedural technique remains challenging, and it is often not performed properly in many cases of deployment or placements. In this study, three types of FDs that changed the material of the wire were prepared within the same structure. Differences in physical properties, such as before and after delivery loading stent size, radial force, and radiopacity, were evaluated. The performances in terms of deployment and trackability force were also evaluated in a simulated model using these FDs. Furthermore, changes of deployment patterns when these FDs were applied to a 3D-printed aneurysm model were determined. The NiTi FD using only nitinol (NiTi) wire showed 100% size recovery and 42% to 45% metal coverage after loading. The low trackability force (10.9 to 22.9 gf) allows smooth movement within the delivery system. However, NiTi FD cannot be used in actual surgeries due to difficulties in X-ray identification. NiTi-Pt/W FD, a combination of NiTi wire and platinum/tungsten (Pt/W) wire, had the highest radiopacity and compression force (6.03 ± 0.29 gf) among the three FDs. However, it suffered from high trackability force (22.4 to 39.9 gf) and the end part braiding mesh tended to loosen easily, so the procedure became more challenging. The NiTi(Pt) FD using a platinum core nitinol (NiTi(Pt)) wire had similar trackability force (11.3 to 22.1 gf) to NiTi FD and uniform deployment, enhancing procedural convenience. However, concerns about low expansion force (1.79 ± 0.30 gf) and the potential for migration remained. This comparative analysis contributes to a comprehensive understanding of how different wire materials influence the performance of FDs. While this study is still in its early stages and requires further research, its development has the potential to guide clinicians and researchers in optimizing the selection and development of FDs for the effective treatment of intracranial aneurysms. Full article

(This article belongs to the Special Issue Using Existing Medical Technologies to Solve and Improve Medical Challenges)

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20 pages, 23941 KiB

Open AccessArticle

Feasibility of a Shape-Memory-Alloy-Actuator System for Modular Acetabular Cups

by Christian Rotsch, Karoline Kemter-Esser, Johanna Dohndorf, Marcel Knothe, Welf-Guntram Drossel and Christoph-Eckhard Heyde

Bioengineering 2024, 11(1), 75; https://doi.org/10.3390/bioengineering11010075 - 12 Jan 2024

Viewed by 969

Abstract

Hip implants have a modular structure which enables patient-specific adaptation but also revision of worn or damaged friction partners without compromising the implant-bone connection. To reduce complications during the extraction of ceramic inlays, this work presents a new approach of a shape-memory-alloy-actuator which [...] Read more.

Hip implants have a modular structure which enables patient-specific adaptation but also revision of worn or damaged friction partners without compromising the implant-bone connection. To reduce complications during the extraction of ceramic inlays, this work presents a new approach of a shape-memory-alloy-actuator which enables the loosening of ceramic inlays from acetabular hip cups without ceramic chipping or damaging the metal cup. This technical in vitro study exam-ines two principles of heating currents and hot water for thermal activation of the shape-memory-alloy-actuator to generate a force between the metal cup and the ceramic inlay. Mechanical tests concerning push-in and push-out forces, deformation of the acetabular cup according to international test standards, and force generated by the actuator were generated to prove the feasibility of this new approach to ceramic inlay revision. The required disassembly force for a modular acetabular device achieved an average value of 602 N after static and 713 N after cyclic loading. The actuator can provide a push-out force up to 1951 N. In addition, it is shown that the necessary modifications to the implant modules for the implementation of the shape-memory-actuator-system do not result in any change in the mechanical properties compared to conventional systems. Full article

(This article belongs to the Special Issue Innovative Medical Technology and Surgical Techniques: Focus on Joint Arthroplasty)

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14 pages, 5164 KiB

Open AccessArticle

Osteoblast Attachment on Bioactive Glass Air Particle Abrasion-Induced Calcium Phosphate Coating

by Faleh Abushahba, Elina Kylmäoja, Nagat Areid, Leena Hupa, Pekka K. Vallittu, Juha Tuukkanen and Timo Närhi

Bioengineering 2024, 11(1), 74; https://doi.org/10.3390/bioengineering11010074 - 12 Jan 2024

Viewed by 918

Abstract

Air particle abrasion (APA) using bioactive glass (BG) effectively decontaminates titanium (Ti) surface biofilms and the retained glass particles on the abraded surfaces impart potent antibacterial properties against various clinically significant pathogens. The objective of this study was to investigate the effect of [...] Read more.

Air particle abrasion (APA) using bioactive glass (BG) effectively decontaminates titanium (Ti) surface biofilms and the retained glass particles on the abraded surfaces impart potent antibacterial properties against various clinically significant pathogens. The objective of this study was to investigate the effect of BG APA and simulated body fluid (SBF) immersion of sandblasted and acid-etched (SA) Ti surfaces on osteoblast cell viability. Another goal was to study the antibacterial effect against Streptococcus mutans. Square-shaped 10 mm diameter Ti substrates (n = 136) were SA by grit blasting with aluminum oxide particles, then acid-etching in an HCl-H₂SO₄ mixture. The SA substrates (n = 68) were used as non-coated controls (NC-SA). The test group (n = 68) was further subjected to APA using experimental zinc-containing BG (Zn4) and then mineralized in SBF for 14 d (Zn4-CaP). Surface roughness, contact angle, and surface free energy (SFE) were calculated on test and control surfaces. In addition, the topography and chemistry of substrate surfaces were also characterized. Osteoblastic cell viability and focal adhesion were also evaluated and compared to glass slides as an additional control. The antibacterial effect of Zn4-CaP was also assessed against S. mutans. After immersion in SBF, a mineralized zinc-containing Ca-P coating was formed on the SA substrates. The Zn4-CaP coating resulted in a significantly lower Ra surface roughness value (2.565 μm; p < 0.001), higher wettability (13.35°; p < 0.001), and higher total SFE (71.13; p < 0.001) compared to 3.695 μm, 77.19° and 40.43 for the NC-SA, respectively. APA using Zn4 can produce a zinc-containing calcium phosphate coating that demonstrates osteoblast cell viability and focal adhesion comparable to that on NC-SA or glass slides. Nevertheless, the coating had no antibacterial effect against S. mutans. Full article

(This article belongs to the Special Issue Titanium Implant and Its Cleaning/Decontamination Techniques)

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15 pages, 892 KiB

Open AccessArticle

Data-Driven Insights into Labor Progression with Gaussian Processes

by Tilekbek Zhoroev, Emily F. Hamilton and Philip A. Warrick

Bioengineering 2024, 11(1), 73; https://doi.org/10.3390/bioengineering11010073 - 11 Jan 2024

Viewed by 885

Abstract

Clinicians routinely perform pelvic examinations to assess the progress of labor. Clinical guidelines to interpret these examinations, using time-based models of cervical dilation, are not always followed and have not contributed to reducing cesarean-section rates. We present a novel Gaussian process model of [...] Read more.

Clinicians routinely perform pelvic examinations to assess the progress of labor. Clinical guidelines to interpret these examinations, using time-based models of cervical dilation, are not always followed and have not contributed to reducing cesarean-section rates. We present a novel Gaussian process model of labor progress, suitable for real-time use, that predicts cervical dilation and fetal station based on clinically relevant predictors available from the pelvic exam and cardiotocography. We show that the model is more accurate than a statistical approach using a mixed-effects model. In addition, it provides confidence estimates on the prediction, calibrated to the specific delivery. Finally, we show that predicting both dilation and station with a single Gaussian process model is more accurate than two separate models with single predictions. Full article

(This article belongs to the Special Issue Fetal-Maternal Monitoring during Pregnancy and Labor: Trends and Opportunities)

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