Sensors

27 pages, 5188 KiB

Open AccessArticle

Autonomous Underwater Vehicles: Identifying Critical Issues and Future Perspectives in Image Acquisition

by Alberto Monterroso Muñoz, Maria-Jose Moron-Fernández, Daniel Cascado-Caballero, Fernando Diaz-del-Rio and Pedro Real

Sensors 2023, 23(10), 4986; https://doi.org/10.3390/s23104986 - 22 May 2023

Cited by 5 | Viewed by 2811

Abstract

Underwater imaging has been present for many decades due to its relevance in vision and navigation systems. In recent years, advances in robotics have led to the availability of autonomous or unmanned underwater vehicles (AUVs, UUVs). Despite the rapid development of new studies [...] Read more.

Underwater imaging has been present for many decades due to its relevance in vision and navigation systems. In recent years, advances in robotics have led to the availability of autonomous or unmanned underwater vehicles (AUVs, UUVs). Despite the rapid development of new studies and promising algorithms in this field, there is currently a lack of research toward standardized, general-approach proposals. This issue has been stated in the literature as a limiting factor to be addressed in the future. The key starting point of this work is to identify a synergistic effect between professional photography and scientific fields by analyzing image acquisition issues. Subsequently, we discuss underwater image enhancement and quality assessment, image mosaicking and algorithmic concerns as the last processing step. In this line, statistics about 120 AUV articles fro recent decades have been analyzed, with a special focus on state-of-the-art papers from recent years. Therefore, the aim of this paper is to identify critical issues in autonomous underwater vehicles encompassing the entire process, starting from optical issues in image sensing and ending with some issues related to algorithmic processing. In addition, a global underwater workflow is proposed, extracting future requirements, outcome effects and new perspectives in this context. Full article

(This article belongs to the Special Issue Advanced Sensor Applications in Marine Objects Recognition)

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15 pages, 5778 KiB

Open AccessArticle

Improved Optical Path Structure for Symmetric Demodulation Method in EFPI Fiber Optic Acoustic Sensors Using Wavelength Division Multiplexing

by Hao Chen, Chenggang Guan, Hui Lv, Can Guo and Shiyi Chai

Sensors 2023, 23(10), 4985; https://doi.org/10.3390/s23104985 - 22 May 2023

Cited by 2 | Viewed by 1223

Abstract

This paper presents a novel improvement in the optical path structure of a three-wavelength symmetric demodulation method applied to extrinsic Fabry–Perot interferometer (EFPI) fiber optic acoustic sensors. The traditional approach of using couplers to construct the phase difference in the symmetric demodulation method [...] Read more.

This paper presents a novel improvement in the optical path structure of a three-wavelength symmetric demodulation method applied to extrinsic Fabry–Perot interferometer (EFPI) fiber optic acoustic sensors. The traditional approach of using couplers to construct the phase difference in the symmetric demodulation method is replaced with a new approach that combines the symmetric demodulation algorithm with wavelength division multiplexing (WDM) technology. This improvement addresses the issue of a suboptimal coupler split ratio and phase difference, which can affect the accuracy and performance of the symmetric demodulation method. In an anechoic chamber test environment, the symmetric demodulation algorithm implemented with the WDM optical path structure achieved a signal-to-noise ratio (SNR) of 75.5 dB (1 kHz), a sensitivity of 1104.9 mV/Pa (1 kHz), and a linear fitting coefficient of 0.9946. In contrast, the symmetric demodulation algorithm implemented with the traditional coupler-based optical path structure achieved an SNR of 65.1 dB (1 kHz), a sensitivity of 891.75 mV/Pa (1 kHz), and a linear fitting coefficient of 0.9905. The test results clearly indicate that the improved optical path structure based on WDM technology outperforms the traditional coupler-based optical path structure in terms of sensitivity, SNR, and linearity. Full article

(This article belongs to the Special Issue Fiber Optics Sensor Technology and Its Applications)

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13 pages, 4790 KiB

Open AccessArticle

A Microfluidic, Flow-Through, Liquid Reagent Fluorescence Sensor Applied to Oxygen Concentration Measurement

by Dominik Gril and Denis Donlagic

Sensors 2023, 23(10), 4984; https://doi.org/10.3390/s23104984 - 22 May 2023

Cited by 1 | Viewed by 1448

Abstract

A concept of a microfluidic fluorescent chemical sensing system is presented and demonstrated as a sensor for measurement of dissolved oxygen in water. The system utilizes on-line mixing of a fluorescent reagent with the analyzed sample, while it measures the fluorescence decay time [...] Read more.

A concept of a microfluidic fluorescent chemical sensing system is presented and demonstrated as a sensor for measurement of dissolved oxygen in water. The system utilizes on-line mixing of a fluorescent reagent with the analyzed sample, while it measures the fluorescence decay time of the mixture. The system is built entirely out of silica capillaries and optical fibers, and allows for very low consumption of the reagent (of the order of mL/month) and the analyzed sample (of the order of L/month). The proposed system can, thus, be applied to continuous on-line measurements, while utilizing a broad variety of different and proven fluorescent reagents or dyes. The proposed system allows for the use of relatively high-excitation light powers, as the flow-through concept of the system reduces the probability of the appearance of bleaching, heating, or other unwanted effects on the fluorescent dye/reagent caused significantly by the excitation light. The high amplitudes of fluorescent optical signals captured by an optical fiber allow for low-noise and high-bandwidth optical signal detection, and, consequently, the possibility for utilization of reagents with nanosecond fluorescent lifetimes. Full article

(This article belongs to the Topic Micro/Nanofluidics and Structures Based Sensing, Material Processing and Energy Conversion)

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20 pages, 5760 KiB

Open AccessArticle

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson’s Disease

by Stefano Filippo Castiglia, Dante Trabassi, Carmela Conte, Alberto Ranavolo, Gianluca Coppola, Gabriele Sebastianelli, Chiara Abagnale, Francesca Barone, Federico Bighiani, Roberto De Icco, Cristina Tassorelli and Mariano Serrao

Sensors 2023, 23(10), 4983; https://doi.org/10.3390/s23104983 - 22 May 2023

Cited by 4 | Viewed by 1500

Abstract

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson’s disease (swPD) and healthy subjects, regardless of [...] Read more.

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson’s disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1–6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD. Full article

(This article belongs to the Special Issue Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis)

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11 pages, 1718 KiB

Open AccessCommunication

Maximizing Antenna Array Aperture Efficiency for Footprint Patterns

by Cibrán López-Álvarez, María Elena López-Martín, Juan Antonio Rodríguez-González and Francisco José Ares-Pena

Sensors 2023, 23(10), 4982; https://doi.org/10.3390/s23104982 - 22 May 2023

Viewed by 1280

Abstract

Despite playing a central role in antenna design, aperture efficiency is often disregarded. Consequently, the present study shows that maximizing the aperture efficiency reduces the required number of radiating elements, which leads to cheaper antennas with more directivity. For this, it is considered [...] Read more.

Despite playing a central role in antenna design, aperture efficiency is often disregarded. Consequently, the present study shows that maximizing the aperture efficiency reduces the required number of radiating elements, which leads to cheaper antennas with more directivity. For this, it is considered that the boundary of the antenna aperture has to be inversely proportional to the half-power beamwidth of the desired footprint for each

ϕ

-cut. As an example of application, it has been considered the rectangular footprint, for which a mathematical expression was deduced to calculate the aperture efficiency in terms of the beamwidth, synthesizing a rectangular footprint of a 2:1 aspect ratio by starting from a pure real flat-topped beam pattern. In addition, a more realistic pattern was studied, the asymmetric coverage defined by the European Telecommunications Satellite Organization, including the numerical computation of the contour of the resulting antenna and its aperture efficiency. Full article

(This article belongs to the Topic Antennas)

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10 pages, 2444 KiB

Open AccessCommunication

Frequency Modulation Control of an FMCW LiDAR Using a Frequency-to-Voltage Converter

by Jubong Lee, Jinseo Hong and Kyihwan Park

Sensors 2023, 23(10), 4981; https://doi.org/10.3390/s23104981 - 22 May 2023

Cited by 1 | Viewed by 4565

Abstract

An FMCW LiDAR (frequency-modulated continuous-wave light detection and ranging) is a sensor that can measure distance using optical interference frequency (

f_{b}

). This sensor has recently attracted interest because it is robust to harsh environmental conditions and sunlight due to the [...] Read more.

An FMCW LiDAR (frequency-modulated continuous-wave light detection and ranging) is a sensor that can measure distance using optical interference frequency (

f_{b}

). This sensor has recently attracted interest because it is robust to harsh environmental conditions and sunlight due to the wave properties of the laser. Theoretically, when the frequency of the reference beam is linearly modulated, a constant

f_{b}

is obtained with respect to the distance. However, when the frequency of the reference beam fails to be linearly modulated, the distance measurement is not accurate. In this work, linear frequency modulation control using frequency detection is proposed to improve the distance accuracy. The FVC (frequency to voltage converting) method is used to measure

f_{b}

for high-speed frequency modulation control. The experimental results show that linear frequency modulation control using an FVC improves FMCW LiDAR performance in terms of control speed and frequency accuracy. Full article

(This article belongs to the Section Physical Sensors)

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20 pages, 7919 KiB

Open AccessArticle

WM–STGCN: A Novel Spatiotemporal Modeling Method for Parkinsonian Gait Recognition

by Jieming Zhang, Jongmin Lim, Moon-Hyun Kim, Sungwook Hur and Tai-Myoung Chung

Sensors 2023, 23(10), 4980; https://doi.org/10.3390/s23104980 - 22 May 2023

Cited by 5 | Viewed by 1557

Abstract

Parkinson’s disease (PD) is a neurodegenerative disorder that causes gait abnormalities. Early and accurate recognition of PD gait is crucial for effective treatment. Recently, deep learning techniques have shown promising results in PD gait analysis. However, most existing methods focus on severity estimation [...] Read more.

Parkinson’s disease (PD) is a neurodegenerative disorder that causes gait abnormalities. Early and accurate recognition of PD gait is crucial for effective treatment. Recently, deep learning techniques have shown promising results in PD gait analysis. However, most existing methods focus on severity estimation and frozen gait detection, while the recognition of Parkinsonian gait and normal gait from the forward video has not been reported. In this paper, we propose a novel spatiotemporal modeling method for PD gait recognition, named WM–STGCN, which utilizes a Weighted adjacency matrix with virtual connection and Multi-scale temporal convolution in a Spatiotemporal Graph Convolution Network. The weighted matrix enables different intensities to be assigned to different spatial features, including virtual connections, while the multi-scale temporal convolution helps to effectively capture the temporal features at different scales. Moreover, we employ various approaches to augment skeleton data. Experimental results show that our proposed method achieved the best accuracy of 87.1% and an F1 score of 92.85%, outperforming Long short-term memory (LSTM), K-nearest neighbors (KNN), Decision tree, AdaBoost, and ST–GCN models. Our proposed WM–STGCN provides an effective spatiotemporal modeling method for PD gait recognition that outperforms existing methods. It has the potential for clinical application in PD diagnosis and treatment. Full article

(This article belongs to the Section Biomedical Sensors)

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25 pages, 4418 KiB

Open AccessArticle

A Framework for Cybersecurity Requirements Management in the Automotive Domain

by Feng Luo, Yifan Jiang, Jiajia Wang, Zhihao Li and Xiaoxian Zhang

Sensors 2023, 23(10), 4979; https://doi.org/10.3390/s23104979 - 22 May 2023

Viewed by 1474

Abstract

The rapid development of intelligent connected vehicles has increased the attack surface of vehicles and made the complexity of vehicle systems unprecedented. Original equipment manufacturers (OEMs) need to accurately represent and identify threats and match corresponding security requirements. Meanwhile, the fast iteration cycle [...] Read more.

The rapid development of intelligent connected vehicles has increased the attack surface of vehicles and made the complexity of vehicle systems unprecedented. Original equipment manufacturers (OEMs) need to accurately represent and identify threats and match corresponding security requirements. Meanwhile, the fast iteration cycle of modern vehicles requires development engineers to quickly obtain cybersecurity requirements for new features in their developed systems in order to develop system code that meets cybersecurity requirements. However, existing threat identification and cybersecurity requirement methods in the automotive domain cannot accurately describe and identify threats for a new feature while also quickly matching appropriate cybersecurity requirements. This article proposes a cybersecurity requirements management system (CRMS) framework to assist OEM security experts in conducting comprehensive automated threat analysis and risk assessment and to help development engineers identify security requirements prior to software development. The proposed CRMS framework enables development engineers to quickly model their systems using the UML-based (i.e., capable of describing systems using UML) Eclipse Modeling Framework and security experts to integrate their security experience into a threat library and security requirement library expressed in Alloy formal language. In order to ensure accurate matching between the two, a middleware communication framework called the component channel messaging and interface (CCMI) framework, specifically designed for the automotive domain, is proposed. The CCMI communication framework enables the fast model of development engineers to match with the formal model of security experts for threat and security requirement matching, achieving accurate and automated threat and risk identification and security requirement matching. To validate our work, we conducted experiments on the proposed framework and compared the results with the HEAVENS approach. The results showed that the proposed framework is superior in terms of threat detection rates and coverage rates of security requirements. Moreover, it also saves analysis time for large and complex systems, and the cost-saving effect becomes more pronounced with increasing system complexity. Full article

(This article belongs to the Special Issue Security, Privacy and Trust in Connected and Automated Vehicles)

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15 pages, 23625 KiB

Open AccessArticle

Fiber-Optic Telecommunication Network Wells Monitoring by Phase-Sensitive Optical Time-Domain Reflectometer with Disturbance Recognition

by Andrey A. Zhirnov, German Y. Chesnokov, Konstantin V. Stepanov, Tatyana V. Gritsenko, Roman I. Khan, Kirill I. Koshelev, Anton O. Chernutsky, Cesare Svelto, Alexey B. Pnev and Olga V. Valba

Sensors 2023, 23(10), 4978; https://doi.org/10.3390/s23104978 - 22 May 2023

Cited by 7 | Viewed by 1861

Abstract

The paper presents the application of a phase-sensitive optical time-domain reflectometer (phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched structure of the urban network of telecommunication wells. The encountered tasks and difficulties are described. The possibilities of usage are [...] Read more.

The paper presents the application of a phase-sensitive optical time-domain reflectometer (phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched structure of the urban network of telecommunication wells. The encountered tasks and difficulties are described. The possibilities of usage are substantiated, and the numerical values of the event quality classification algorithms applied to experimental data are calculated using machine learning methods. Among the considered methods, the best results were shown by convolutional neural networks, with a probability of correct classification as high as 98.55%. Full article

(This article belongs to the Topic Advance and Applications of Fiber Optic Measurement)

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35 pages, 13250 KiB

Open AccessArticle

Educational Case Studies: Creating a Digital Twin of the Production Line in TIA Portal, Unity, and Game4Automation Framework

by Michal Balla, Oto Haffner, Erik Kučera and Ján Cigánek

Sensors 2023, 23(10), 4977; https://doi.org/10.3390/s23104977 - 22 May 2023

Cited by 5 | Viewed by 3394

Abstract

In today’s industry, the fourth industrial revolution is underway, characterized by the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data. One of the key pillars of this revolution is the technology of digital twin, which is [...] Read more.

In today’s industry, the fourth industrial revolution is underway, characterized by the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data. One of the key pillars of this revolution is the technology of digital twin, which is rapidly gaining importance in various industries. However, the concept of digital twins is often misunderstood or misused as a buzzword, leading to confusion in its definition and applications. This observation inspired the authors of this paper to create their own demonstration applications that allow the control of both the real and virtual systems through automatic two-way communication and mutual influence in context of digital twins. The paper aims to demonstrate the use of digital twin technology aimed at discrete manufacturing events in two case studies. In order to create the digital twins for these case studies, the authors used technologies as Unity, Game4Automation, Siemens TIA portal, and Fishertechnik models. The first case study involves the creation of a digital twin for a production line model, while the second case study involves the virtual extension of a warehouse stacker using a digital twin. These case studies will form the basis for the creation of pilot courses for Industry 4.0 education and can be further modified for the development of Industry 4.0 educational materials and technical practice. In conclusion, selected technologies are affordable, which makes the presented methodologies and educational studies accessible to a wide range of researchers and solution developers tackling the issue of digital twins, with a focus on discrete manufacturing events. Full article

(This article belongs to the Special Issue Intelligent Control and Digital Twins for Industry 4.0)

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12 pages, 4003 KiB

Open AccessCommunication

Enhanced Optical Response of SnS/SnS₂ Layered Heterostructure

by Der-Yuh Lin, Hung-Pin Hsu, Kuang-Hsin Liu, Po-Hung Wu, Yu-Tai Shih, Ya-Fen Wu, Yi-Ping Wang and Chia-Feng Lin

Sensors 2023, 23(10), 4976; https://doi.org/10.3390/s23104976 - 22 May 2023

Cited by 3 | Viewed by 1601

Abstract

The SnS/SnS₂ heterostructure was fabricated by the chemical vapor deposition method. The crystal structure properties of SnS₂ and SnS were characterized by X-ray diffraction (XRD) pattern, Raman spectroscopy, and field emission scanning electron microscopy (FESEM). The frequency dependence photoconductivity explores its [...] Read more.

The SnS/SnS₂ heterostructure was fabricated by the chemical vapor deposition method. The crystal structure properties of SnS₂ and SnS were characterized by X-ray diffraction (XRD) pattern, Raman spectroscopy, and field emission scanning electron microscopy (FESEM). The frequency dependence photoconductivity explores its carrier kinetic decay process. The SnS/SnS₂ heterostructure shows that the ratio of short time constant decay process reaches 0.729 with a time constant of 4.3 × 10⁻⁴ s. The power-dependent photoresponsivity investigates the mechanism of electron–hole pair recombination. The results indicate that the photoresponsivity of the SnS/SnS₂ heterostructure has been increased to 7.31 × 10⁻³ A/W, representing a significant enhancement of approximately 7 times that of the individual films. The results show the optical response speed has been improved by using the SnS/SnS₂ heterostructure. These results indicate an application potential of the layered SnS/SnS₂ heterostructure for photodetection. This research provides valuable insights into the preparation of the heterostructure composed of SnS and SnS₂, and presents an approach for designing high-performance photodetection devices. Full article

(This article belongs to the Special Issue Recent Advances of Optoelectronic Devices and Semiconductor Sensors)

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18 pages, 4210 KiB

Open AccessArticle

Evaluation of the Health Status of Indonesian Watersheds Using Impervious Surface Area as an Indicator

by Rossi Hamzah and Bunkei Matsushita

Sensors 2023, 23(10), 4975; https://doi.org/10.3390/s23104975 - 22 May 2023

Cited by 1 | Viewed by 1066

Abstract

Impervious surfaces affect the ecosystem function of watersheds. Therefore, the impervious surface area percentage (ISA%) in watersheds has been regarded as an important indicator for assessing the health status of watersheds. However, accurate and frequent estimation of ISA% from satellite data remains a [...] Read more.

Impervious surfaces affect the ecosystem function of watersheds. Therefore, the impervious surface area percentage (ISA%) in watersheds has been regarded as an important indicator for assessing the health status of watersheds. However, accurate and frequent estimation of ISA% from satellite data remains a challenge, especially at large scales (national, regional, or global). In this study, we first developed a method to estimate ISA% by combining daytime and nighttime satellite data. We then used the developed method to generate an annual ISA% distribution map from 2003 to 2021 for Indonesia. Third, we used these ISA% distribution maps to assess the health status of Indonesian watersheds according to Schueler’s criteria. Accuracy assessment results show that the developed method performed well from low ISA% (rural) to high ISA% (urban) values, with a root mean square difference value of 0.52 km², a mean absolute percentage difference value of 16.2%, and a bias of −0.08 km². In addition, since the developed method uses only satellite data as input, it can be easily implemented in other regions with some modifications according to differences in light use efficiency and economic development in each region. We also found that 88% of Indonesian watersheds remain without impact in 2021, indicating that the health status of Indonesian watersheds is not a serious problem. Nevertheless, Indonesia’s total ISA increased significantly from 3687.4 km² in 2003 to 10,505.5 km² in 2021, and most of the increased ISA was in rural areas. These results indicate that negative trends in health status in Indonesian watersheds may emerge in the future without proper watershed management. Full article

(This article belongs to the Section Remote Sensors)

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20 pages, 4338 KiB

Open AccessArticle

Using HVS Dual-Pathway and Contrast Sensitivity to Blindly Assess Image Quality

by Fan Chen, Hong Fu, Hengyong Yu and Ying Chu

Sensors 2023, 23(10), 4974; https://doi.org/10.3390/s23104974 - 22 May 2023

Cited by 1 | Viewed by 1217

Abstract

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of the human visual system (HVS) can be combined. In this paper, inspired [...] Read more.

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of the human visual system (HVS) can be combined. In this paper, inspired by the ventral pathway and the dorsal pathway of the HVS, a dual-pathway convolutional neural network is proposed for BIQA tasks. The proposed method consists of two pathways: the “what” pathway, which mimics the ventral pathway of the HVS to extract the content features of distorted images, and the “where” pathway, which mimics the dorsal pathway of the HVS to extract the global shape features of distorted images. Then, the features from the two pathways are fused and mapped to an image quality score. Additionally, gradient images weighted by contrast sensitivity are used as the input to the “where” pathway, allowing it to extract global shape features that are more sensitive to human perception. Moreover, a dual-pathway multi-scale feature fusion module is designed to fuse the multi-scale features of the two pathways, enabling the model to capture both global features and local details, thus improving the overall performance of the model. Experiments conducted on six databases show that the proposed method achieves state-of-the-art performance. Full article

(This article belongs to the Section Sensing and Imaging)

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16 pages, 4794 KiB

Open AccessArticle

Robotic Intracellular Pressure Measurement Using Micropipette Electrode

by Minghui Li, Jinyu Qiu, Ruimin Li, Yuzhu Liu, Yue Du, Yaowei Liu, Mingzhu Sun, Xin Zhao and Qili Zhao

Sensors 2023, 23(10), 4973; https://doi.org/10.3390/s23104973 - 22 May 2023

Cited by 1 | Viewed by 1681

Abstract

Intracellular pressure, a key physical parameter of the intracellular environment, has been found to regulate multiple cell physiological activities and impact cell micromanipulation results. The intracellular pressure may reveal the mechanism of these cells’ physiological activities or improve the micro-manipulation accuracy for cells. [...] Read more.

Intracellular pressure, a key physical parameter of the intracellular environment, has been found to regulate multiple cell physiological activities and impact cell micromanipulation results. The intracellular pressure may reveal the mechanism of these cells’ physiological activities or improve the micro-manipulation accuracy for cells. The involvement of specialized and expensive devices and the significant damage to cell viability that the current intracellular pressure measurement methods cause significantly limit their wide applications. This paper proposes a robotic intracellular pressure measurement method using a traditional micropipette electrode system setup. First, the measured resistance of the micropipette inside the culture medium is modeled to analyze its variation trend when the pressure inside the micropipette increases. Then, the concentration of KCl solution filled inside the micropipette electrode that is suitable for intracellular pressure measurement is determined according to the tested electrode resistance–pressure relationship; 1 mol/L KCl solution is our final choice. Further, the measurement resistance of the micropipette electrode inside the cell is modeled to measure the intracellular pressure through the difference in key pressure before and after the release of the intracellular pressure. Based on the above work, a robotic measurement procedure of the intracellular pressure is established based on a traditional micropipette electrode system. The experimental results on porcine oocytes demonstrate that the proposed method can operate on cells at an average speed of 20~40 cells/day with measurement efficiency comparable to the related work. The average repeated error of the relationship between the measured electrode resistance and the pressure inside the micropipette electrode is less than 5%, and no observable intracellular pressure leakage was found during the measurement process, both guaranteeing the measurement accuracy of intracellular pressure. The measured results of the porcine oocytes are in accordance with those reported in related work. Moreover, a 90% survival rate of operated oocytes was obtained after measurement, proving limited damage to cell viability. Our method does not rely on expensive instruments and is conducive to promotion in daily laboratories. Full article

(This article belongs to the Special Issue Sensors for Robots II)

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16 pages, 1030 KiB

Open AccessArticle

Analysis of Movement Variability in Cycling: An Exploratory Study

by Lachlan Winter, Clint Bellenger, Paul Grimshaw and Robert George Crowther

Sensors 2023, 23(10), 4972; https://doi.org/10.3390/s23104972 - 22 May 2023

Viewed by 1674

Abstract

The purpose of this study was to determine the test-retest repeatability of Blue Trident inertial measurement units (IMUs) and VICON Nexus kinematic modelling in analysing the Lyapunov Exponent (LyE) during a maximal effort 4000 m cycling bout in different body segments/joints. An additional [...] Read more.

The purpose of this study was to determine the test-retest repeatability of Blue Trident inertial measurement units (IMUs) and VICON Nexus kinematic modelling in analysing the Lyapunov Exponent (LyE) during a maximal effort 4000 m cycling bout in different body segments/joints. An additional aim was to determine if changes in the LyE existed across a trial. Twelve novice cyclists completed four sessions of cycling; one was a familiarisation session to determine a bike fit and become better accustomed to the time trial position and pacing of a 4000 m effort. IMUs were attached to the head, thorax, pelvis and left and right shanks to analyse segment accelerations, respectively, and reflective markers were attached to the participant to analyse neck, thorax, pelvis, hip, knee and ankle segment/joint angular kinematics, respectively. Both the IMU and VICON Nexus test-retest repeatability ranged from poor to excellent at the different sites. In each session, the head and thorax IMU acceleration LyE increased across the bout, whilst pelvic and shank acceleration remained consistent. Differences across sessions were evident in VICON Nexus segment/joint angular kinematics, but no consistent trend existed. The improved reliability and the ability to identify a consistent trend in performance, combined with their improved portability and reduced cost, advocate for the use of IMUs in analysing movement variability in cycling. However, additional research is required to determine the applicability of analysing movement variability during cycling. Full article

(This article belongs to the Special Issue Inertial Measurement Units in Sport)

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21 pages, 1723 KiB

Open AccessArticle

An Improved Mutual Information Feature Selection Technique for Intrusion Detection Systems in the Internet of Medical Things

by Mousa Alalhareth and Sung-Chul Hong

Sensors 2023, 23(10), 4971; https://doi.org/10.3390/s23104971 - 22 May 2023

Cited by 5 | Viewed by 1817

Abstract

In healthcare, the Internet of Things (IoT) is used to remotely monitor patients and provide real-time diagnoses, which is referred to as the Internet of Medical Things (IoMT). This integration poses a risk from cybersecurity threats that can harm patient data and well-being. [...] Read more.

In healthcare, the Internet of Things (IoT) is used to remotely monitor patients and provide real-time diagnoses, which is referred to as the Internet of Medical Things (IoMT). This integration poses a risk from cybersecurity threats that can harm patient data and well-being. Hackers can manipulate biometric data from biosensors or disrupt the IoMT system, which is a major concern. To address this issue, intrusion detection systems (IDS) have been proposed, particularly using deep learning algorithms. However, developing IDS for IoMT is challenging due to high data dimensionality leading to model overfitting and degraded detection accuracy. Feature selection has been proposed to prevent overfitting, but the existing methods assume that feature redundancy increases linearly with the size of the selected features. Such an assumption does not hold, as the amount of information a feature carries about the attack pattern varies from feature to feature, especially when dealing with early patterns, due to data sparsity that makes it difficult to perceive the common characteristics of selected features. This negatively affects the ability of the mutual information feature selection (MIFS) goal function to estimate the redundancy coefficient accurately. To overcome this issue, this paper proposes an enhanced feature selection technique called Logistic Redundancy Coefficient Gradual Upweighting MIFS (LRGU-MIFS) that evaluates candidate features individually instead of comparing them with common characteristics of the already-selected features. Unlike the existing feature selection techniques, LRGU calculates the redundancy score of a feature using the logistic function. It increases the redundancy value based on the logistic curve, which reflects the nonlinearity of the relationship of the mutual information between features in the selected set. Then, the LRGU was incorporated into the goal function of MIFS as a redundancy coefficient. The experimental evaluation shows that the proposed LRGU was able to identify a compact set of significant features that outperformed those selected by the existing techniques. The proposed technique overcomes the challenge of perceiving common characteristics in cases of insufficient attack patterns and outperforms existing techniques in identifying significant features. Full article

(This article belongs to the Section Biomedical Sensors)

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17 pages, 1463 KiB

Open AccessArticle

Lightweight Authentication Mechanism for Industrial IoT Environment Combining Elliptic Curve Cryptography and Trusted Token

by Yu-Sheng Yang, Shih-Hsiung Lee, Jie-Min Wang, Chu-Sing Yang, Yuen-Min Huang and Ting-Wei Hou

Sensors 2023, 23(10), 4970; https://doi.org/10.3390/s23104970 - 22 May 2023

Cited by 3 | Viewed by 1621

Abstract

With the promotion of Industry 4.0, which emphasizes interconnected and intelligent devices, several factories have introduced numerous terminal Internet of Things (IoT) devices to collect relevant data or monitor the health status of equipment. The collected data are transmitted back to the backend [...] Read more.

With the promotion of Industry 4.0, which emphasizes interconnected and intelligent devices, several factories have introduced numerous terminal Internet of Things (IoT) devices to collect relevant data or monitor the health status of equipment. The collected data are transmitted back to the backend server through network transmission by the terminal IoT devices. However, as devices communicate with each other over a network, the entire transmission environment faces significant security issues. When an attacker connects to a factory network, they can easily steal the transmitted data and tamper with them or send false data to the backend server, causing abnormal data in the entire environment. This study focuses on investigating how to ensure that data transmission in a factory environment originates from legitimate devices and that related confidential data are encrypted and packaged. This paper proposes an authentication mechanism between terminal IoT devices and backend servers based on elliptic curve cryptography and trusted tokens with packet encryption using the TLS protocol. Before communication between terminal IoT devices and backend servers can occur, the authentication mechanism proposed in this paper must first be implemented to confirm the identity of the devices and, thus, the problem of attackers imitating terminal IoT devices transmitting false data is resolved. The packets communicated between devices are also encrypted, preventing attackers from knowing their content even if they steal the packets. The authentication mechanism proposed in this paper ensures the source and correctness of the data. In terms of security analysis, the proposed mechanism in this paper effectively withstands replay attacks, eavesdropping attacks, man-in-the-middle attacks, and simulated attacks. Additionally, the mechanism supports mutual authentication and forward secrecy. In the experimental results, the proposed mechanism demonstrates approximately 73% improvement in efficiency through the lightweight characteristics of elliptic curve cryptography. Moreover, in the analysis of time complexity, the proposed mechanism exhibits significant effectiveness. Full article

(This article belongs to the Special Issue Security and Trustworthiness in Industrial IoT)

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24 pages, 6919 KiB

Open AccessArticle

Milling Surface Roughness Prediction Based on Physics-Informed Machine Learning

by Shi Zeng and Dechang Pi

Sensors 2023, 23(10), 4969; https://doi.org/10.3390/s23104969 - 22 May 2023

Cited by 2 | Viewed by 1758

Abstract

Surface roughness is a key indicator of the quality of mechanical products, which can precisely portray the fatigue strength, wear resistance, surface hardness and other properties of the products. The convergence of current machine-learning-based surface roughness prediction methods to local minima may lead [...] Read more.

Surface roughness is a key indicator of the quality of mechanical products, which can precisely portray the fatigue strength, wear resistance, surface hardness and other properties of the products. The convergence of current machine-learning-based surface roughness prediction methods to local minima may lead to poor model generalization or results that violate existing physical laws. Therefore, this paper combined physical knowledge with deep learning to propose a physics-informed deep learning method (PIDL) for milling surface roughness predictions under the constraints of physical laws. This method introduced physical knowledge in the input phase and training phase of deep learning. Data augmentation was performed on the limited experimental data by constructing surface roughness mechanism models with tolerable accuracy prior to training. In the training, a physically guided loss function was constructed to guide the training process of the model with physical knowledge. Considering the excellent feature extraction capability of convolutional neural networks (CNNs) and gated recurrent units (GRUs) in the spatial and temporal scales, a CNN–GRU model was adopted as the main model for milling surface roughness predictions. Meanwhile, a bi-directional gated recurrent unit and a multi-headed self-attentive mechanism were introduced to enhance data correlation. In this paper, surface roughness prediction experiments were conducted on the open-source datasets S45C and GAMHE 5.0. In comparison with the results of state-of-the-art methods, the proposed model has the highest prediction accuracy on both datasets, and the mean absolute percentage error on the test set was reduced by 3.029% on average compared to the best comparison method. Physical-model-guided machine learning prediction methods may be a future pathway for machine learning evolution. Full article

(This article belongs to the Section Physical Sensors)

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17 pages, 3070 KiB

Open AccessArticle

Inertial-Sensor-Based Monitoring of Sample Entropy and Peak Frequency Changes in Treadmill Walking during Recovery after Total Knee Arthroplasty

by Werner A. F. van de Ven, Jurjen Bosga, Wim Hullegie, Wiebe C. Verra and Ruud G. J. Meulenbroek

Sensors 2023, 23(10), 4968; https://doi.org/10.3390/s23104968 - 22 May 2023

Viewed by 1291

Abstract

This study aimed to investigate whether sample entropy (SEn) and peak frequency values observed in treadmill walking could provide physical therapists valuable insights into gait rehabilitation following total knee arthroplasty (TKA). It was recognized that identifying movement strategies that during rehabilitation are initially [...] Read more.

This study aimed to investigate whether sample entropy (SEn) and peak frequency values observed in treadmill walking could provide physical therapists valuable insights into gait rehabilitation following total knee arthroplasty (TKA). It was recognized that identifying movement strategies that during rehabilitation are initially adaptive but later start to hamper full recovery is critical to meet the clinical goals and minimize the risk of contralateral TKA. Eleven TKA patients were asked to perform clinical walking tests and a treadmill walking task at four different points in time (pre-TKA, 3, 6, and 12 months post-TKA). Eleven healthy peers served as the reference group. The movements of the legs were digitized with inertial sensors and SEn and peak frequency of the recorded rotational velocity–time functions were analyzed in the sagittal plane. SEn displayed a systematic increase during recovery in TKA patients (p < 0.001). Furthermore, lower peak frequency (p = 0.01) and sample entropy (p = 0.028) were found during recovery for the TKA leg. Movement strategies that initially are adaptive, and later hamper recovery, tend to diminish after 12 months post-TKA. It is concluded that inertial-sensor-based SEn and peak frequency analyses of treadmill walking enrich the assessment of movement rehabilitation after TKA. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics—2nd Edition)

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24 pages, 6496 KiB

Open AccessArticle

The Effects Analysis of Contact Stiffness of Double-Row Tapered Roller Bearing under Composite Loads

by Fanyu Zhang, Hangyuan Lv, Qingkai Han and Mingqi Li

Sensors 2023, 23(10), 4967; https://doi.org/10.3390/s23104967 - 22 May 2023

Cited by 2 | Viewed by 1707

Abstract

Double-row tapered roller bearings have been widely used in various equipment recently due to their compact structure and ability to withstand large loads. The dynamic stiffness is composed of contact stiffness, oil film stiffness and support stiffness, and the contact stiffness has the [...] Read more.

Double-row tapered roller bearings have been widely used in various equipment recently due to their compact structure and ability to withstand large loads. The dynamic stiffness is composed of contact stiffness, oil film stiffness and support stiffness, and the contact stiffness has the most significant influence on the dynamic performance of the bearing. There are few studies on the contact stiffness of double-row tapered roller bearings. Firstly, the contact mechanics calculation model of double-row tapered roller bearing under composite loads has been established. On this basis, the influence of load distribution of double-row tapered roller bearing is analyzed, and the calculation model of contact stiffness of double-row tapered roller bearing is obtained according to the relationship between overall stiffness and local stiffness of bearing. Based on the established stiffness model, the influence of different working conditions on the contact stiffness of the bearing is simulated and analyzed, and the effects of radial load, axial load, bending moment load, speed, preload, and deflection angle on the contact stiffness of double row tapered roller bearings have been revealed. Finally, by comparing the results with Adams simulation results, the error is within 8%, which verifies the validity and accuracy of the proposed model and method. The research content of this paper provides theoretical support for the design of double-row tapered roller bearings and the identification of bearing performance parameters under complex loads. Full article

(This article belongs to the Special Issue Multi-Sensor Information Fusion, Advanced Signal Analysis, and Intelligent Fault Diagnosis)

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12 pages, 5504 KiB

Open AccessCommunication

Fast High-Resolution Phase Diversity Wavefront Sensing with L-BFGS Algorithm

by Haoyuan Zhang, Guohao Ju, Liang Guo, Boqian Xu, Xiaoquan Bai, Fengyi Jiang and Shuyan Xu

Sensors 2023, 23(10), 4966; https://doi.org/10.3390/s23104966 - 22 May 2023

Cited by 1 | Viewed by 1022

Abstract

The presence of manufacture error in large mirrors introduces high-order aberrations, which can severely influence the intensity distribution of point spread function. Therefore, high-resolution phase diversity wavefront sensing is usually needed. However, high-resolution phase diversity wavefront sensing is restricted with the problem of [...] Read more.

The presence of manufacture error in large mirrors introduces high-order aberrations, which can severely influence the intensity distribution of point spread function. Therefore, high-resolution phase diversity wavefront sensing is usually needed. However, high-resolution phase diversity wavefront sensing is restricted with the problem of low efficiency and stagnation. This paper proposes a fast high-resolution phase diversity method with limited memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm, which can accurately detect aberrations in the presence of high-order aberrations. An analytical gradient of the objective function for phase-diversity is integrated into the framework of the L-BFGS nonlinear optimization algorithm. L-BFGS algorithm is specifically suitable for high-resolution wavefront sensing where a large phase matrix is optimized. The performance of phase diversity with L-BFGS is compared to other iterative method through simulations and a real experiment. This work contributes to fast high-resolution image-based wavefront sensing with a high robustness. Full article

(This article belongs to the Section Optical Sensors)

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18 pages, 4721 KiB

Open AccessArticle

Estimating Scalp Moisture in a Hat Using Wearable Sensors

by Haomin Mao, Shuhei Tsuchida, Tsutomu Terada and Masahiko Tsukamoto

Sensors 2023, 23(10), 4965; https://doi.org/10.3390/s23104965 - 22 May 2023

Viewed by 1335

Abstract

Hair quality is easily affected by the scalp moisture content, and hair loss and dandruff will occur when the scalp surface becomes dry. Therefore, it is essential to monitor scalp moisture content constantly. In this study, we developed a hat-shaped device equipped with [...] Read more.

Hair quality is easily affected by the scalp moisture content, and hair loss and dandruff will occur when the scalp surface becomes dry. Therefore, it is essential to monitor scalp moisture content constantly. In this study, we developed a hat-shaped device equipped with wearable sensors that can continuously collect scalp data in daily life for estimating scalp moisture with machine learning. We established four machine learning models, two based on learning with non-time-series data and two based on learning with time-series data collected by the hat-shaped device. Learning data were obtained in a specially designed space with a controlled environmental temperature and humidity. The inter-subject evaluation showed a Mean Absolute Error (MAE) of 8.50 using Support Vector Machine (SVM) with 5-fold cross-validation with 15 subjects. Moreover, the intra-subject evaluation showed an average MAE of 3.29 in all subjects using Random Forest (RF). The achievement of this study is using a hat-shaped device with cheap wearable sensors attached to estimate scalp moisture content, which avoids the purchase of a high-priced moisture meter or a professional scalp analyzer for individuals. Full article

(This article belongs to the Special Issue Wearable Sensors and Technology for Human Health Monitoring)

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Graphical abstract

34 pages, 1711 KiB

Open AccessArticle

An Analysis of the Mixed IEEE 802.11ax Wireless Networks in the 5 GHz Band

by Marek Natkaniec and Natalia Bieryt

Sensors 2023, 23(10), 4964; https://doi.org/10.3390/s23104964 - 22 May 2023

Cited by 3 | Viewed by 2368

Abstract

This paper presents an analysis of the IEEE 802.11ax networks’ coexistence with legacy stations, namely IEEE 802.11ac, IEEE 802.11n, and IEEE 802.11a. The IEEE 802.11ax standard introduces several new features that can enhance network performance and capacity. The legacy devices that do not [...] Read more.

This paper presents an analysis of the IEEE 802.11ax networks’ coexistence with legacy stations, namely IEEE 802.11ac, IEEE 802.11n, and IEEE 802.11a. The IEEE 802.11ax standard introduces several new features that can enhance network performance and capacity. The legacy devices that do not support these features will continue to coexist with newer devices, creating a mixed network environment. This usually leads to a deterioration in the overall performance of such networks; therefore, in the paper, we want to show how we can reduce the negative impact of legacy devices. In this study, we investigate the performance of mixed networks by applying various parameters to both the MAC and PHY layers. We focus on evaluating the impact of the BSS coloring mechanism introduced to the IEEE 802.11ax standard on network performance. We also examine the impact of A-MPDU and A-MSDU aggregations on network efficiency. Through simulations, we analyze the typical performance metrics such as throughput, mean packet delay, and packet loss of mixed networks with different topologies and configurations. Our findings indicate that implementing the BSS coloring mechanism in dense networks can increase throughput by up to 43%. We also show that the presence of legacy devices in the network disrupts the functioning of this mechanism. To address this, we recommend using an aggregation technique, which can improve throughput by up to 79%. The presented research revealed that it is possible to optimize the performance of mixed IEEE 802.11ax networks. Full article

(This article belongs to the Special Issue Recent Advances in Mobile and Wireless Communication Networks)

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28 pages, 16671 KiB

Open AccessArticle

Location-Based Augmented Reality for Cultural Heritage Communication and Education: The Doltso District Application

by Alexandros Kleftodimos, Athanasios Evagelou, Amalia Triantafyllidou, Magdalini Grigoriou and Georgios Lappas

Sensors 2023, 23(10), 4963; https://doi.org/10.3390/s23104963 - 22 May 2023

Cited by 4 | Viewed by 2438

Abstract

Location-based Augmented Reality applications are increasingly used in many research and commercial fields. Some of the fields that these applications are used are recreational digital games, tourism, education, and marketing. This study aims to present a location-based augmented reality (AR) application for cultural [...] Read more.

Location-based Augmented Reality applications are increasingly used in many research and commercial fields. Some of the fields that these applications are used are recreational digital games, tourism, education, and marketing. This study aims to present a location-based augmented reality (AR) application for cultural heritage communication and education. The application was created to inform the public, especially K12 students, about a district of their city with cultural heritage value. Furthermore, Google Earth was utilized to create an interactive virtual tour for consolidating the knowledge acquired by the location-based AR application. A scheme for evaluating the AR application was also constructed using factors suitable for location-based applications: challenge, educational usefulness (knowledge), collaboration, and intention to reuse. A sample of 309 students evaluated the application. Descriptive statistical analysis showed that the application scored well in all factors, especially in challenge and knowledge (mean values 4.21 and 4.12). Furthermore, structural equation modeling (SEM) analysis led to a model construction that represents how the factors are causally related. Based on the findings, the perceived challenge significantly influenced the perceived educational usefulness (knowledge) (b = 0.459, sig = 0.000) and interaction levels (b = 0.645, sig = 0.000). Interaction amongst users also had a significant positive impact on users’ perceived educational usefulness (b = 0.374, sig = 0.000), which in turn influenced users’ intention to reuse the application (b = 0.624, sig = 0.000). Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

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31 pages, 5695 KiB

Open AccessArticle

Autonomous Robots for Services—State of the Art, Challenges, and Research Areas

by Marius Misaros, Ovidiu-Petru Stan, Ionut-Catalin Donca and Liviu-Cristian Miclea

Sensors 2023, 23(10), 4962; https://doi.org/10.3390/s23104962 - 22 May 2023

Cited by 3 | Viewed by 3988

Abstract

It has been almost half a century since the first interest in autonomous robots was shown, and research is still continuing to improve their ability to make perfectly conscious decisions from a user safety point of view. These autonomous robots are now at [...] Read more.

It has been almost half a century since the first interest in autonomous robots was shown, and research is still continuing to improve their ability to make perfectly conscious decisions from a user safety point of view. These autonomous robots are now at a fairly advanced level, which means that their adoption rate in social environments is also increasing. This article reviews the current state of development of this technology and highlights the evolution of interest in it. We analyze and discuss specific areas of its use, for example, its functionality and current level of development. Finally, challenges related to the current level of research and new methods that are still being developed for the wider adoption of these autonomous robots are highlighted. Full article

(This article belongs to the Special Issue Advanced Research in Intelligent Autonomous Mobile Robots System, Learning and Control)

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17 pages, 3552 KiB

Open AccessArticle

Corner-Point and Foreground-Area IoU Loss: Better Localization of Small Objects in Bounding Box Regression

by Delong Cai, Zhaoyun Zhang and Zhi Zhang

Sensors 2023, 23(10), 4961; https://doi.org/10.3390/s23104961 - 22 May 2023

Cited by 5 | Viewed by 1770

Abstract

Bounding box regression is a crucial step in object detection, directly affecting the localization performance of the detected objects. Especially in small object detection, an excellent bounding box regression loss can significantly alleviate the problem of missing small objects. However, there are two [...] Read more.

Bounding box regression is a crucial step in object detection, directly affecting the localization performance of the detected objects. Especially in small object detection, an excellent bounding box regression loss can significantly alleviate the problem of missing small objects. However, there are two major problems with the broad Intersection over Union (IoU) losses, also known as Broad IoU losses (BIoU losses) in bounding box regression: (i) BIoU losses cannot provide more effective fitting information for predicted boxes as they approach the target box, resulting in slow convergence and inaccurate regression results; (ii) most localization loss functions do not fully utilize the spatial information of the target, namely the target’s foreground area, during the fitting process. Therefore, this paper proposes the Corner-point and Foreground-area IoU loss (CFIoU loss) function by delving into the potential for bounding box regression losses to overcome these issues. First, we use the normalized corner point distance between the two boxes instead of the normalized center-point distance used in the BIoU losses, which effectively suppresses the problem of BIoU losses degrading to IoU loss when the two boxes are close. Second, we add adaptive target information to the loss function to provide richer target information to optimize the bounding box regression process, especially for small object detection. Finally, we conducted simulation experiments on bounding box regression to validate our hypothesis. At the same time, we conducted quantitative comparisons of the current mainstream BIoU losses and our proposed CFIoU loss on the small object public datasets VisDrone2019 and SODA-D using the latest anchor-based YOLOv5 and anchor-free YOLOv8 object detection algorithms. The experimental results demonstrate that YOLOv5s (+3.12% Recall, +2.73% mAP@0.5, and +1.91% mAP@0.5:0.95) and YOLOv8s (+1.72% Recall and +0.60% mAP@0.5), both incorporating the CFIoU loss, achieved the highest performance improvement on the VisDrone2019 test set. Similarly, YOLOv5s (+6% Recall, +13.08% mAP@0.5, and +14.29% mAP@0.5:0.95) and YOLOv8s (+3.36% Recall, +3.66% mAP@0.5, and +4.05% mAP@0.5:0.95), both incorporating the CFIoU loss, also achieved the highest performance improvement on the SODA-D test set. These results indicate the effectiveness and superiority of the CFIoU loss in small object detection. Additionally, we conducted comparative experiments by fusing the CFIoU loss and the BIoU loss with the SSD algorithm, which is not proficient in small object detection. The experimental results demonstrate that the SSD algorithm incorporating the CFIoU loss achieved the highest improvement in the AP (+5.59%) and AP75 (+5.37%) metrics, indicating that the CFIoU loss can also improve the performance of algorithms that are not proficient in small object detection. Full article

(This article belongs to the Topic Applied Computing and Machine Intelligence (ACMI))

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9 pages, 514 KiB

Open AccessCommunication

Prediction of the Physical Activity Level of Community-Dwelling Older Japanese Adults with a Triaxial Accelerometer Containing a Classification Algorithm for Ambulatory and Non-Ambulatory Activities

by Shigeho Tanaka, Kazuko Ishikawa-Takata, Satoshi Nakae and Satoshi Sasaki

Sensors 2023, 23(10), 4960; https://doi.org/10.3390/s23104960 - 22 May 2023

Cited by 1 | Viewed by 1057

Abstract

Accurate methods for the prediction of the total energy expenditure and physical activity level (PAL) in community-dwelling older adults have not been established. Therefore, we examined the validity of estimating the PAL using an activity monitor (Active style Pro HJA-350IT, [ASP]) and proposed [...] Read more.

Accurate methods for the prediction of the total energy expenditure and physical activity level (PAL) in community-dwelling older adults have not been established. Therefore, we examined the validity of estimating the PAL using an activity monitor (Active style Pro HJA-350IT, [ASP]) and proposed correction formulae for such populations in Japan. Data for 69 Japanese community-dwelling adults aged 65 to 85 years were used. The total energy expenditure in free-living conditions was measured with the doubly labeled water method and the measured basal metabolic rate. The PAL was also estimated from metabolic equivalent (MET) values obtained with the activity monitor. Adjusted MET values were also calculated with the regression equation of Nagayoshi et al. (2019). The observed PAL was underestimated, but significantly correlated, with the PAL from the ASP. When adjusted using the Nagayoshi et al. regression equation, the PAL was overestimated. Therefore, we developed regression equations to estimate the actual PAL (Y) from the PAL obtained with the ASP for young adults (X) as follows: women: Y = 0.949 × X + 0.205, mean ± standard deviation of the prediction error = 0.00 ± 0.20; men: Y = 0.899 × X + 0.371, mean ± standard deviation of the prediction error = 0.00 ± 0.17. Full article

(This article belongs to the Special Issue Wearable and Unobtrusive Technologies for Healthcare Monitoring)

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16 pages, 9454 KiB

Open AccessArticle

Identification of Abnormal Data for Synchronous Monitoring of Transformer DC Bias Based on Multiple Criteria

by Zhongqing Kou, Sheng Lin, Aimin Wang, Yuanda He and Long Chen

Sensors 2023, 23(10), 4959; https://doi.org/10.3390/s23104959 - 22 May 2023

Cited by 1 | Viewed by 1087

Abstract

Seriously abnormal data exist in the synchronous monitoring data of transformer DC bias, which causes serious data feature contamination and even affects the identification of transformer DC bias. For this reason, this paper aims to ensure the reliability and validity of synchronous monitoring [...] Read more.

Seriously abnormal data exist in the synchronous monitoring data of transformer DC bias, which causes serious data feature contamination and even affects the identification of transformer DC bias. For this reason, this paper aims to ensure the reliability and validity of synchronous monitoring data. This paper proposes an identification of abnormal data for the synchronous monitoring of transformer DC bias based on multiple criteria. By analyzing the abnormal data of different types, the characteristics of abnormal data are obtained. Based on this, the abnormal data identification indexes are introduced, including gradient, sliding kurtosis and Pearson correlation coefficient. Firstly, the Pauta criterion is used to determine the threshold of the gradient index. Then, gradient is used to identify the suspected abnormal data. Finally, the sliding kurtosis and Pearson correlation coefficient are used to identify the abnormal data. Data for synchronous monitoring of transformer DC bias in a certain power grid are used to verify the proposed method. The results show that the accuracy of the proposed method in identifying mutated abnormal data and zero-value abnormal data is claimed to be 100%. Compared with traditional abnormal data identification methods, the accuracy of the proposed method is significantly improved. Full article

(This article belongs to the Section Electronic Sensors)

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9 pages, 3219 KiB

Open AccessCommunication

Design of a Narrow Band Filter Based on a Photonic Crystal Cavity for CO₂ Sensing Application

by Reyhaneh Jannesari, Thomas Grille, Gerald Stocker and Bernhard Jakoby

Sensors 2023, 23(10), 4958; https://doi.org/10.3390/s23104958 - 22 May 2023

Cited by 1 | Viewed by 1272

Abstract

This paper investigates the use of a miniaturized filter based on a triangular lattice of holes in a photonic crystal (PhC) slab. The plane wave expansion method (PWE) and finite-difference time-domain (FDTD) techniques were utilized to analyze the dispersion and transmission spectrum, as [...] Read more.

This paper investigates the use of a miniaturized filter based on a triangular lattice of holes in a photonic crystal (PhC) slab. The plane wave expansion method (PWE) and finite-difference time-domain (FDTD) techniques were utilized to analyze the dispersion and transmission spectrum, as well as the quality factor and free spectral range (FSR) of the filter. A 3D simulation has demonstrated that for the designed filter, an FSR of more than 550 nm and a quality factor of 873 can be attained by adiabatically coupling light from a slab waveguide into a PhC waveguide. This work designs a filter structure that is implemented into the waveguide and is suitable for a fully integrated sensor. The small size of the device provides a strong potential for the realization of large arrays of independent filters on a single chip. The fully integrated character of this filter has further advantages such as reducing power loss in coupling light from sources to filters and also from filters to waveguides. The ease of fabrication is another benefit of completely integrating the filter. Full article

(This article belongs to the Special Issue Advances in Miniaturized Sensors)

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9 pages, 1395 KiB

Open AccessArticle

Co-Designing Digital Technologies for Improving Clinical Care in People with Parkinson’s Disease: What Did We Learn?

by Mariana H. G. Monje, Sylvie Grosjean, Martin Srp, Laura Antunes, Raquel Bouça-Machado, Ricardo Cacho, Sergio Domínguez, John Inocentes, Timothy Lynch, Argyri Tsakanika, Dimitrios Fotiadis, George Rigas, Evžen Růžička, Joaquim Ferreira, Angelo Antonini, Norberto Malpica, Tiago Mestre, Álvaro Sánchez-Ferro and iCARE-PD Consortium

Sensors 2023, 23(10), 4957; https://doi.org/10.3390/s23104957 - 22 May 2023

Cited by 1 | Viewed by 1798

Abstract

The healthcare model is shifting towards integrated care approaches. This new model requires patients to be more closely involved. The iCARE-PD project aims to address this need by developing a technology-enabled, home-based, and community-centered integrated care paradigm. A central part of this project [...] Read more.

The healthcare model is shifting towards integrated care approaches. This new model requires patients to be more closely involved. The iCARE-PD project aims to address this need by developing a technology-enabled, home-based, and community-centered integrated care paradigm. A central part of this project is the codesign process of the model of care, exemplified by the active participation of patients in the design and iterative evaluation of three sensor-based technological solutions. We proposed a codesign methodology used for testing the usability and acceptability of these digital technologies and present initial results for one of them, MooVeo. Our results show the usefulness of this approach in testing the usability and acceptability as well as the opportunity to incorporate patients’ feedback into the development. This initiative will hopefully help other groups incorporate a similar codesign approach and develop tools that are well adapted to patients’ and care teams’ needs. Full article

(This article belongs to the Special Issue Wearable Sensors for Neurological Diseases Remote Monitoring)

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