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

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

TL;DR

Problem: Continuous stress monitoring requires reliable EDA sensing with high dynamic range and low power in wearables. Approach: A high-accuracy EDA acquisition system with an adaptive gain mechanism using two multiplexers and an AFE, implemented on a custom PCB with an nRF52832 BLE MCU; evaluated via simulations and on-board tests. Findings: Achieved error rate < 1%, correlation of 0.73 vs Empatica E4, and power consumption around 700 μA at 3.7V, with long-term endurance demonstrated over 30 hours. Significance: Enables robust, energy-efficient wearable EDA monitoring for long-term stress assessment and can be integrated into compact wearables or flexible form factors.

Abstract

This paper presents a novel Electrodermal Activity (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 700$μ$A under a 3.7V power supply. This research contributes significantly to the field of wearable health technology, offering a robust and efficient solution for long-term stress monitoring.

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

TL;DR

Problem: Continuous stress monitoring requires reliable EDA sensing with high dynamic range and low power in wearables. Approach: A high-accuracy EDA acquisition system with an adaptive gain mechanism using two multiplexers and an AFE, implemented on a custom PCB with an nRF52832 BLE MCU; evaluated via simulations and on-board tests. Findings: Achieved error rate < 1%, correlation of 0.73 vs Empatica E4, and power consumption around 700 μA at 3.7V, with long-term endurance demonstrated over 30 hours. Significance: Enables robust, energy-efficient wearable EDA monitoring for long-term stress assessment and can be integrated into compact wearables or flexible form factors.

Abstract

This paper presents a novel Electrodermal Activity (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 700A under a 3.7V power supply. This research contributes significantly to the field of wearable health technology, offering a robust and efficient solution for long-term stress monitoring.
Paper Structure (6 sections, 6 figures)

This paper contains 6 sections, 6 figures.

Table of Contents

  1. Introduction
  2. Working Principle
  3. Prototype Development
  4. Accuracy and Power Consumption Evaluation on Board
  5. Discussion
  6. Conclusion and Future Work

Figures (6)

  • Figure 1: Illustration of the External Circuits Modules and MCU for Electrodermal(EDA) Response System
  • Figure 2: Simulated compensation mechanism illustration (a).skin conductivity (b).Gain Ratio (c).Output voltage
  • Figure 3: (a).Simulated Resolutions Between circuits with and without Adaptive gain. (b). Comparison of Output Voltage Between circuits with and without Adaptive gain
  • Figure 4: (a). Measurement Errors (b). Customized PCB for EDA Acquisition System
  • Figure 5: (a) Our device (b) Empatica E4. (c) Comparison of EDA Data
  • ...and 1 more figures