Advanced Energy-Efficient System for Precision Electrodermal Activity Monitoring in Stress Detection

This paper presents a novel Electrodermal Activ-ity (EDA) signal acquisition system, designed to address the challenges of stress monitoring in contemporary society, where stress affects one in four individuals. Our system focuses on enhancing the accuracy and efficiency of EDA measurements, a reliable indicator of stress. Traditional EDA monitoring solutions often grapple with trade-offs between sensor placement, cost, and power consumption, leading to compromised data accuracy. Our innovative design incorporates an adaptive gain mechanism, catering to the broad dynamic range and high-resolution needs of EDA data analysis. The performance of our system was extensively tested through simulations and a custom Printed Circuit Board (PCB), achieving an error rate below 1 % and maintaining power consumption at a mere <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{700}\mu \mathbf{A}$</tex> under a 3. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$7\mathbf{V}$</tex> power supply. This research contributes significantly to the field of wearable health technology, offering a robust and efficient solution for long-term stress monitoring.

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Publication Details

Published
2024-10-15
DOI
https://doi.org/10.1109/bsn63547.2024.10780551
Primary Topic
Sensor Technology and Measurement Systems
Type
article
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article

Advanced Energy-Efficient System for Precision Electrodermal Activity Monitoring in Stress Detection

Houman Homayoun, Ruoyu Zhang, Elahe Hosseini, Ruijie Fang et al.
Sensor Technology and Measurement Systems
article

Advanced Energy-Efficient System for Precision Electrodermal Activity Monitoring in Stress Detection

Houman Homayoun, Ruoyu Zhang, Elahe Hosseini, Ruijie Fang, Chongzhou Fang, Ning Miao
article en

Abstract

This paper presents a novel Electrodermal Activ-ity (EDA) signal acquisition system, designed to address the challenges of stress monitoring in contemporary society, where stress affects one in four individuals. Our system focuses on enhancing the accuracy and efficiency of EDA measurements, a reliable indicator of stress. Traditional EDA monitoring solutions often grapple with trade-offs between sensor placement, cost, and power consumption, leading to compromised data accuracy. Our innovative design incorporates an adaptive gain mechanism, catering to the broad dynamic range and high-resolution needs of EDA data analysis. The performance of our system was extensively tested through simulations and a custom Printed Circuit Board (PCB), achieving an error rate below 1 % and maintaining power consumption at a mere <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{700}\mu \mathbf{A}$</tex> under a 3. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$7\mathbf{V}$</tex> power supply. This research contributes significantly to the field of wearable health technology, offering a robust and efficient solution for long-term stress monitoring.

University of California, Davis (US)
Affordable and clean energy
Openalex Percentile: Top 74%
Sensor Technology and Measurement Systems
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