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Integrated Circuit and System Design for Health Monitoring

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

Deadline for manuscript submissions: 15 July 2024 | Viewed by 9633

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Special Issue Editors

Dr. Glenn Cowan

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Guest Editor

Department of Electrical & Computer Engineering, Concordia University, Montreal, QC, Canada
Interests: analog and mixed-signal design

Dr. Vinicius G. Sirtoli

E-Mail Website
Guest Editor

Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada
Interests: biomedical devices

Special Issue Information

Dear Colleagues,

Advances in technology are leading to ever smaller devices accompanied by the democratization of nanotechnologies. Hence, nowadays most researchers across the globe have access to integrated circuits and systems.

The healthcare area is especially benefited by these sorts of devices because they allow the embedding of medical equipment into daily life objects and clothing. Hence, people can have real-time access to health quality information, which facilitates preventive medicine, speeds intervention when needed, and reduces costs of medical infrastructure.

In this special issue of MDPI Sensors, the goal is to provide readers with the latest original research and review papers on integrated circuits and systems aimed at monitoring and assessing health quality. Researchers investigating integrated designs in the following areas are urged to contribute.

Biosensors
Biopotential recording
Bioimpedance and bioelectricity
Wearable devices
Frond-end circuits
Rehabilitation tools
Haptics
Sensor networks and multi-modality sensing devices
Swallowable and implantable devices
Prosthetics and biorobotics

Dr. Glenn Cowan
Dr. Vinicius G. Sirtoli
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

sensors
biosensors
wearable devices
CMOS
sensor networks
healthcare
telemedicine

Published Papers (4 papers)

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Research

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16 pages, 4127 KiB

Open AccessArticle

Flexible Textile Sensors-Based Smart T-Shirt for Respiratory Monitoring: Design, Development, and Preliminary Validation

by Chiara Romano, Daniela Lo Presti, Sergio Silvestri, Emiliano Schena and Carlo Massaroni

Sensors 2024, 24(6), 2018; https://doi.org/10.3390/s24062018 - 21 Mar 2024

Viewed by 603

Abstract

Respiratory rate (

f_{R}

Respiratory rate (

f_{R}

) monitoring through wearable devices is crucial in several scenarios, providing insights into well-being and sports performance while minimizing interference with daily activities. Strain sensors embedded into garments stand out but require thorough investigation for optimal deployment. Optimal sensor positioning is often overlooked, and when addressed, the quality of the respiratory signal is neglected. Additionally, sensor metrological characterization after sensor integration is often omitted. In this study, we present the design, development, and feasibility assessment of a smart t-shirt embedded with two flexible sensors for

f_{R}

monitoring. Guided by a motion capture system, optimal sensor design and position on the chest wall were defined, considering both signal magnitude and quality. The sensors were developed, embedded into the wearable system, and metrologically characterized, demonstrating a remarkable response to both static (sensitivity 9.4

Ω \cdot %^{- 1}

and 9.1

Ω \cdot %^{- 1}

for sensor A and sensor B, respectively) and cyclic loads (min. hysteresis span 20.4% at 36 bpm obtained for sensor A). The feasibility of the wearable system was assessed on healthy volunteers both under static and dynamic conditions (such as running, walking, and climbing stairs). A mean absolute error of 0.32 bpm was obtained by averaging all subjects and tests using the combination of the two sensors. This value was lower than that obtained using both sensor A (0.53 bpm) and sensor B (0.78 bpm) individually. Our study highlights the importance of signal amplitude and quality in optimal sensor placement evaluation, as well as the characterization of the embedded sensors for metrological assessment. Full article

(This article belongs to the Special Issue Integrated Circuit and System Design for Health Monitoring)

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19 pages, 22398 KiB

Open AccessArticle

Automated Age-Related Macular Degeneration Detector on Optical Coherence Tomography Images Using Slice-Sum Local Binary Patterns and Support Vector Machine

by Yao-Wen Yu, Cheng-Hung Lin, Cheng-Kai Lu, Jia-Kang Wang and Tzu-Lun Huang

Sensors 2023, 23(17), 7315; https://doi.org/10.3390/s23177315 - 22 Aug 2023

Viewed by 1022

Abstract

Artificial intelligence has revolutionised smart medicine, resulting in enhanced medical care. This study presents an automated detector chip for age-related macular degeneration (AMD) using a support vector machine (SVM) and three-dimensional (3D) optical coherence tomography (OCT) volume. The aim is to assist ophthalmologists by reducing the time-consuming AMD medical examination. Using the property of 3D OCT volume, a modified feature vector connected method called slice-sum is proposed, reducing computational complexity while maintaining high detection accuracy. Compared to previous methods, this method significantly reduces computational complexity by at least a hundredfold. Image adjustment and noise removal steps are excluded for classification accuracy, and the feature extraction algorithm of local binary patterns is determined based on hardware consumption considerations. Through optimisation of the feature vector connection method after feature extraction, the computational complexity of SVM detection is significantly reduced, making it applicable to similar 3D datasets. Additionally, the design supports model replacement, allowing users to train and update classification models as needed. Using TSMC 40 nm CMOS technology, the proposed detector achieves a core area of 0.12 mm² while demonstrating a classification throughput of 8.87 decisions/s at a maximum operating frequency of 454.54 MHz. The detector achieves a final testing classification accuracy of 92.31%. Full article

(This article belongs to the Special Issue Integrated Circuit and System Design for Health Monitoring)

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16 pages, 2302 KiB

Open AccessArticle

Using Ballistocardiogram and Impedance Plethysmogram for Minimal Contact Measurement of Blood Pressure Based on a Body Weight-Fat Scale

by Shing-Hong Liu, Yan-Rong Wu, Wenxi Chen, Chun-Hung Su and Chiun-Li Chin

Sensors 2023, 23(4), 2318; https://doi.org/10.3390/s23042318 - 19 Feb 2023

Cited by 1 | Viewed by 1995

Abstract

Electronic health (eHealth) is a strategy to improve the physical and mental condition of a human, collecting daily physiological data and information from digital apparatuses. Body weight and blood pressure (BP) are the most popular and important physiological data. The goal of this study is to develop a minimal contact BP measurement method based on a commercial body weight-fat scale, capturing biometrics when users stand on it. The pulse transit time (PTT) is extracted from the ballistocardiogram (BCG) and impedance plethysmogram (IPG), measured by four strain gauges and four footpads of a commercial body weight-fat scale. Cuffless BP measurement using the electrocardiogram (ECG) and photoplethysmogram (PPG) serves as the reference method. The BP measured by a commercial BP monitor is considered the ground truth. Twenty subjects participated in this study. By the proposed model, the root-mean-square errors and correlation coefficients (r²s) of estimated systolic blood pressure and diastolic blood pressure are 7.3 ± 2.1 mmHg and 4.5 ± 1.8 mmHg, and 0.570 ± 0.205 and 0.284 ± 0.166, respectively. This accuracy level achieves the C grade of the corresponding IEEE standard. Thus, the proposed method has the potential benefit for eHealth monitoring in daily application. Full article

(This article belongs to the Special Issue Integrated Circuit and System Design for Health Monitoring)

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Review

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21 pages, 3521 KiB

Open AccessReview

Amplifiers in Biomedical Engineering: A Review from Application Perspectives

by Lida Kouhalvandi, Ladislau Matekovits and Ildiko Peter

Sensors 2023, 23(4), 2277; https://doi.org/10.3390/s23042277 - 17 Feb 2023

Cited by 5 | Viewed by 5272

Abstract

Continuous monitoring and treatment of various diseases with biomedical technologies and wearable electronics has become significantly important. The healthcare area is an important, evolving field that, among other things, requires electronic and micro-electromechanical technologies. Designed circuits and smart devices can lead to reduced hospitalization time and hospitals equipped with high-quality equipment. Some of these devices can also be implanted inside the body. Recently, various implanted electronic devices for monitoring and diagnosing diseases have been presented. These instruments require communication links through wireless technologies. In the transmitters of these devices, power amplifiers are the most important components and their performance plays important roles. This paper is devoted to collecting and providing a comprehensive review on the various designed implanted amplifiers for advanced biomedical applications. The reported amplifiers vary with respect to the class/type of amplifier, implemented CMOS technology, frequency band, output power, and the overall efficiency of the designs. The purpose of the authors is to provide a general view of the available solutions, and any researcher can obtain suitable circuit designs that can be selected for their problem by reading this survey. Full article

(This article belongs to the Special Issue Integrated Circuit and System Design for Health Monitoring)

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