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Wearable Sensors for Biomedical, Environmental, and Security Applications

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 39825

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Special Issue Editors

Dr. Yugender Goud Kotagiri

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Guest Editor

Department of Chemistry, Indian Institute of Technology Palakkad, Palakkad 678623, Kerala, India
Interests: biosensors; electrochemical sensors; wearable sensors; aptamers; point-of-care diagnostics; electrochemistry
Special Issues, Collections and Topics in MDPI journals

Dr. Kuldeep Mahato

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Guest Editor

Department of Nanoengineering, University of California San Diego, 9500 Gilman Dr, La Jolla, San Diego, CA 92093, USA
Interests: biosensors; electrochemical sensor; wearable sensors; bio-fuel cells; aptamer-based sensors
Special Issues, Collections and Topics in MDPI journals

Dr. K. Koteshwara Reddy

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Guest Editor

Laboratory of Materials Science, Instituto de Química de Recursos Naturales, Universidad de Talca, Chile
Interests: electrochemical biosensors; biomarkers; wearable sensors; hybrid nanomaterials

Dr. Rupesh Kumar Mishra

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Guest Editor

Amity Institute of Biotechnology, Amity University Rajasthan, Rajasthan, India
Interests: biosensors; wearable sensors; aptamers; pesticides

Dr. Ahmed Abdelhamid Khorshed

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Guest Editor

Department of Pharmaceutical Analytical Chemistry Faculty of Pharmacy Sohag University - Sohag- Egypt
Interests: biosensors; wearable sensors; aptamers; chromatography

Special Issue Information

Dear Colleagues,

Investigating the performance of wearable sensors in biomedical, environmental, and security applications is one of the significant research themes. Innovative strategies in the fabrication of non-invasive and minimally invasive wearable sensing devices facilitate the continuous monitoring of vital biomarkers in physiological body fluids viz. sweat, tears, saliva, interstitial fluid, nasal fluid, etc. Sensor systems constructed with biocompatible materials and electrochemical/ optical methods generate unique and rich analytical information for users/ patients. Researchers are working meticulously to tackle the biofouling of wearable sensors, one of the major challenges that restricts long-term stability. Wearable sensors have been developed on distinct platforms such as microneedles, bandages, textiles, tattoo, gloves, eyeglasses, rings, and mouthguards for various sensing applications. Wearable sensors have also been demonstrated in the real time monitoring of pathophysiological biomarkers/ions for health management, such as diabetes, Parkinson’s, Alzheimer’s, and cancer. The horizon of wearable sensors is extending in various ways, where these platforms have constantly been used for assessing environmental hazards by identifying potential chemical threats such as nerve disrupting agents, explosives, opioids, and gunshot residues. Apart from these, self-powered wearable sensors have also recently found considerable attention, where biofuel cells assist the sensor with its power requirement during the operation. All of these are advanced and trending sensing device platforms, which are in the scope of the journal Sensors. Thus, this Special Volume, titled “Wearable Sensors for Biomedical, Environmental, and Security Applications”, will bring about a high impact on the wide range of readers. For this Issue, we would like to invite manuscripts related to wearable sensors from various domains of biomedical, environmental, and security-based applications.

Dr. Yugender Goud Kotagiri
Dr. Kuldeep Mahato
Dr. K. Koteshwara Reddy
Dr. Rupesh Kumar Mishra
Dr. Ahmed Abdelhamid Khorshed
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

biosensors
wearable sensors
aptamers
immunosensors
biomarkers
MIPs
electrochemical sensors
optical sensors
microneedle sensors
textile sensors
tattoo sensors
glove sensors
bandage sensors
self-powered biosensors

Published Papers (9 papers)

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Research

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31 pages, 10265 KiB

Open AccessArticle

Wearable Edge AI Applications for Ecological Environments

by Mateus C. Silva, Jonathan C. F. da Silva, Saul Delabrida, Andrea G. C. Bianchi, Sérvio P. Ribeiro, Jorge Sá Silva and Ricardo A. R. Oliveira

Sensors 2021, 21(15), 5082; https://0-doi-org.brum.beds.ac.uk/10.3390/s21155082 - 27 Jul 2021

Cited by 10 | Viewed by 2704

Abstract

Ecological environments research helps to assess the impacts on forests and managing forests. The usage of novel software and hardware technologies enforces the solution of tasks related to this problem. In addition, the lack of connectivity for large data throughput raises the demand for edge-computing-based solutions towards this goal. Therefore, in this work, we evaluate the opportunity of using a Wearable edge AI concept in a forest environment. For this matter, we propose a new approach to the hardware/software co-design process. We also address the possibility of creating wearable edge AI, where the wireless personal and body area networks are platforms for building applications using edge AI. Finally, we evaluate a case study to test the possibility of performing an edge AI task in a wearable-based environment. Thus, in this work, we evaluate the system to achieve the desired task, the hardware resource and performance, and the network latency associated with each part of the process. Through this work, we validated both the design pattern review and case study. In the case study, the developed algorithms could classify diseased leaves with a circa 90% accuracy with the proposed technique in the field. This results can be reviewed in the laboratory with more modern models that reached up to 96% global accuracy. The system could also perform the desired tasks with a quality factor of 0.95, considering the usage of three devices. Finally, it detected a disease epicenter with an offset of circa 0.5 m in a 6 m × 6 m × 12 m space. These results enforce the usage of the proposed methods in the targeted environment and the proposed changes in the co-design pattern. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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15 pages, 3845 KiB

Open AccessArticle

Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications

by Fabian Andres Castaño and Alher Mauricio Hernández

Sensors 2021, 21(14), 4822; https://0-doi-org.brum.beds.ac.uk/10.3390/s21144822 - 15 Jul 2021

Cited by 1 | Viewed by 2310

Abstract

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by World Health Organization. Some wearables devices have been developed to monitor the Electrocardiographic in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an Electrocardiographic signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effects of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain Electrocardiographic signals, the result was compared with a computational model of the heart behavior through the Ensemble Average Electrocardiographic, Dynamic Time Warping and Signal-to-Noise Ratio methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the Electrocardiographic signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6

c

m

at most from the suggested location by the Einthoven triangle in Mason–Likar’s method. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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17 pages, 4096 KiB

Open AccessArticle

Dataset of Tactile Signatures of the Human Right Hand in Twenty-One Activities of Daily Living Using a High Spatial Resolution Pressure Sensor

by Javier Cepriá-Bernal and Antonio Pérez-González

Sensors 2021, 21(8), 2594; https://0-doi-org.brum.beds.ac.uk/10.3390/s21082594 - 07 Apr 2021

Cited by 7 | Viewed by 2544

Abstract

Successful grasping with multi-fingered prosthetic or robotic hands remains a challenge to be solved for the effective use of these hands in unstructured environments. To this end, currently available tactile sensors need to improve their sensitivity, robustness, and spatial resolution, but a better knowledge of the distribution of contact forces in the human hand in grasping tasks is also necessary. The human tactile signatures can inform models for an efficient control of the artificial hands. In this study we present and analyze a dataset of tactile signatures of the human hand in twenty-one representative activities of daily living, obtained using a commercial high spatial resolution pressure sensor. The experiments were repeated for twenty-two subjects. The whole dataset includes more than one hundred million pressure data. The effect of the task and the subject on the grip force and the contribution to this grip force made by the different hand regions were analyzed. We also propose a method to effectively synchronize the measurements from different subjects and a method to represent the tactile signature of each task, highlighting the hand regions mainly involved in the task. The correlations between hand regions and between different tasks were also analyzed. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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11 pages, 4206 KiB

Open AccessArticle

NFC-Based Wearable Optoelectronics Working with Smartphone Application for Untact Healthcare

by Min Hyung Kang, Gil Ju Lee, Joo Ho Yun and Young Min Song

Sensors 2021, 21(3), 878; https://0-doi-org.brum.beds.ac.uk/10.3390/s21030878 - 28 Jan 2021

Cited by 11 | Viewed by 5600

Abstract

With growing interest in healthcare, wearable healthcare devices have been developed and researched. In particular, near-field communication (NFC) based wearable devices have been actively studied for device miniaturization. Herein, this article proposes a low-cost and convenient healthcare system, which can monitor heart rate and temperature using a wireless/battery-free sensor and the customized smartphone application. The authors designed and fabricated a customized healthcare device based on the NFC system, and developed a smartphone application for real-time data acquisition and processing. In order to achieve compact size without performance degradation, a dual-layered layout is applied to the device. The authors demonstrate that the device can operate as attached on various body sites such as wrist, fingertip, temple, and neck due to outstanding flexibility of device and adhesive strength between the device and the skin. In addition, the data processing flow and processing result are presented for offering heart rate and skin temperature. Therefore, this work provides an affordable and practical pathway for the popularization of wireless wearable healthcare system. Moreover, the proposed platform can easily delivery the measured health information to experts for contactless/personal health consultation. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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22 pages, 4938 KiB

Open AccessArticle

A Study of Accelerometer and Gyroscope Measurements in Physical Life-Log Activities Detection Systems

by Ahmad Jalal, Majid Ali Khan Quaid, Sheikh Badar ud din Tahir and Kibum Kim

Sensors 2020, 20(22), 6670; https://0-doi-org.brum.beds.ac.uk/10.3390/s20226670 - 21 Nov 2020

Cited by 63 | Viewed by 9593

Abstract

Nowadays, wearable technology can enhance physical human life-log routines by shifting goals from merely counting steps to tackling significant healthcare challenges. Such wearable technology modules have presented opportunities to acquire important information about human activities in real-life environments. The purpose of this paper is to report on recent developments and to project future advances regarding wearable sensor systems for the sustainable monitoring and recording of human life-logs. On the basis of this survey, we propose a model that is designed to retrieve better information during physical activities in indoor and outdoor environments in order to improve the quality of life and to reduce risks. This model uses a fusion of both statistical and non-statistical features for the recognition of different activity patterns using wearable inertial sensors, i.e., triaxial accelerometers, gyroscopes and magnetometers. These features include signal magnitude, positive/negative peaks and position direction to explore signal orientation changes, position differentiation, temporal variation and optimal changes among coordinates. These features are processed by a genetic algorithm for the selection and classification of inertial signals to learn and recognize abnormal human movement. Our model was experimentally evaluated on four benchmark datasets: Intelligent Media Wearable Smart Home Activities (IM-WSHA), a self-annotated physical activities dataset, Wireless Sensor Data Mining (WISDM) with different sporting patterns from an IM-SB dataset and an SMotion dataset with different physical activities. Experimental results show that the proposed feature extraction strategy outperformed others, achieving an improved recognition accuracy of 81.92%, 95.37%, 90.17%, 94.58%, respectively, when IM-WSHA, WISDM, IM-SB and SMotion datasets were applied. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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30 pages, 17853 KiB

Open AccessArticle

A Textile Sleeve for Monitoring Oxygen Saturation Using Multichannel Optical Fibre Photoplethysmography

by Hattan K. Ballaji, Ricardo Correia, Serhiy Korposh, Barrie R. Hayes-Gill, Francisco U. Hernandez, Byron Salisbury and Stephen P. Morgan

Sensors 2020, 20(22), 6568; https://0-doi-org.brum.beds.ac.uk/10.3390/s20226568 - 17 Nov 2020

Cited by 9 | Viewed by 3766

Abstract

Textile-based systems are an attractive prospect for wearable technology as they can provide monitoring of key physiological parameters in a comfortable and unobtrusive form. A novel system based on multichannel optical fibre sensor probes integrated into a textile sleeve is described. The system measures the photoplethysmogram (PPG) at two wavelengths (660 and 830 nm), which is then used to calculate oxygen saturation (SpO₂). In order to achieve reliable measurement without adjusting the position of the garment, four plastic optical fibre (POF) probes are utilised to increase the likelihood that a high-quality PPG is obtained due to at least one of the probes being positioned over a blood vessel. Each probe transmits and receives light into the skin to measure the PPG and SpO₂. All POFs are integrated in a stretchable textile sleeve with a circumference of 15 cm to keep the sensor in contact with the subject’s wrist and to minimise motion artefacts. Tests on healthy volunteers show that the multichannel PPG sensor faithfully provides an SpO₂ reading in at least one of the four sensor channels in all cases with no need for adjusting the position of the sleeve. This could not be achieved using a single sensor alone. The multichannel sensor is used to monitor the SpO₂ of 10 participants with an average wrist circumference of 16.0 ± 0.6 cm. Comparing the developed sensor’s SpO₂ readings to a reference commercial oximeter (reflectance Masimo Radical-7) illustrates that the mean difference between the two sensors’ readings is −0.03%, the upper limit of agreement (LOA) is 0.52% and the lower LOA is −0.58%. This multichannel sensor has the potential to achieve reliable, unobtrusive and comfortable textile-based monitoring of both heart rate and SpO₂ during everyday life. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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14 pages, 5693 KiB

Open AccessArticle

A Multi-Sensor Wearable System for the Quantitative Assessment of Parkinson’s Disease

by Han Zhang, Chuantao Li, Wei Liu, Jingying Wang, Junhong Zhou and Shouyan Wang

Sensors 2020, 20(21), 6146; https://0-doi-org.brum.beds.ac.uk/10.3390/s20216146 - 29 Oct 2020

Cited by 12 | Viewed by 3816

Abstract

The quantitative characterization of movement disorders and their related neurophysiological signals is important for the management of Parkinson’s disease (PD). The aim of this study is to develop a novel wearable system enabling the simultaneous measurement of both motion and other neurophysiological signals in PD patients. We designed a wearable system that consists of five motion sensors and three electrophysiology sensors to measure the motion signals of the body, electroencephalogram, electrocardiogram, and electromyography, respectively. The data captured by the sensors are transferred wirelessly in real time, and the outcomes are analyzed and uploaded to the cloud-based server automatically. We completed pilot studies to (1) test its validity by comparing outcomes to the commercialized systems, and (2) evaluate the deep brain stimulation (DBS) treatment effects in seven PD patients. Our results showed: (1) the motion and neurophysiological signals measured by this wearable system were strongly correlated with those measured by the commercialized systems (r > 0.94, p < 0.001); and (2) by completing the clinical supination and pronation frequency test, the frequency of motion as measured by this system increased when DBS was turned on. The results demonstrated that this multi-sensor wearable system can be utilized to quantitatively characterize and monitor motion and neurophysiological PD. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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Other

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13 pages, 1133 KiB

Open AccessOpinion

Wearable Electrochemical Sensors in Parkinson’s Disease

by Francesco Asci, Giorgio Vivacqua, Alessandro Zampogna, Valentina D’Onofrio, Adolfo Mazzeo and Antonio Suppa

Sensors 2022, 22(3), 951; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030951 - 26 Jan 2022

Cited by 11 | Viewed by 4038

Abstract

Parkinson’s disease (PD) is a neurodegenerative disorder associated with widespread aggregation of α-synuclein and dopaminergic neuronal loss in the substantia nigra pars compacta. As a result, striatal dopaminergic denervation leads to functional changes in the cortico-basal-ganglia-thalamo-cortical loop, which in turn cause most of the parkinsonian signs and symptoms. Despite tremendous advances in the field in the last two decades, the overall management (i.e., diagnosis and follow-up) of patients with PD remains largely based on clinical procedures. Accordingly, a relevant advance in the field would require the development of innovative biomarkers for PD. Recently, the development of miniaturized electrochemical sensors has opened new opportunities in the clinical management of PD thanks to wearable devices able to detect specific biological molecules from various body fluids. We here first summarize the main wearable electrochemical technologies currently available and their possible use as medical devices. Then, we critically discuss the possible strengths and weaknesses of wearable electrochemical devices in the management of chronic diseases including PD. Finally, we speculate about possible future applications of wearable electrochemical sensors in PD, such as the attractive opportunity for personalized closed-loop therapeutic approaches. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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12 pages, 6181 KiB

Open AccessLetter

Development of a Portable All-Wavelength PPG Sensing Device for Robust Adaptive-Depth Measurement: A Spectrometer Approach with a Hydrostatic Measurement Example

by Shao-Hao Chen, Yung-Chi Chuang and Cheng-Chun Chang

Sensors 2020, 20(22), 6556; https://0-doi-org.brum.beds.ac.uk/10.3390/s20226556 - 17 Nov 2020

Cited by 7 | Viewed by 3487

Abstract

Photoplethysmography (PPG), a noninvasive optical sensing technology, has been widely used to measure various physiological indices. Over-the-counter PPG devices are typically composed of a single-wavelength light source, namely, single-wavelength PPG (SW-PPG). It is known that signals of SW-PPG are easily contaminated or distorted by measurement conditions such as motion artifacts, wearing pressure, and skin type. Since lights of different wavelengths can penetrate skin tissues at different depths, how to effectively construct a multiwavelength PPG (MW-PPG) device or even an all-wavelength PPG (AW-PPG) device has attracted great attention. There is also a very interesting question, that is, what could be the potential benefits of using MW-PPG or AW-PPG devices? This paper demonstrates the construction of an AW-PPG portable device and conducts a preliminary evaluation. The presented device consists of four light-emitting diodes, a chip-scale spectrometer, a microcontroller, a Bluetooth Low Energy transceiver, and a phone app. The maximum ratio combining algorithm (MRC) is used to combine the PPG signals derived from different wavelengths to achieve a better signal-to-noise ratio (S/N). The PPG signals from the developed MRC-AW-PPG device versus those from the conventional SW-PPG device are compared in terms of different hydrostatic pressure conditions. It has been observed that the MRC-AW-PPG device can provide more stable PPG signals than that of a conventional PPG device. The results shine a light on the potential benefits of using multiple wavelengths for the next generation of noninvasive PPG sensing. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomedical, Environmental, and Security Applications)

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