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StressFit: A Hybrid Wearable Physicochemical Sensor Suite for Simultaneously Measuring Electromyogram and Sweat Cortisol
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Abstract
This study introduces StressFit, a novel hybrid wearable sensor system designed to simultaneously monitor electromyogram (EMG) signals and sweat cortisol levels. Our approach involves the development of a noninvasive skin patch capable of monitoring skin temperature, sweat pH, cortisol levels, and corresponding EMG signals using a combination of physical and electrochemical sensors integrated with EMG electrodes. StressFit was optimized by enhancing sensor output and mechanical resilience for practical application on curved body surfaces, ensuring accurate acquisition of cortisol, pH, body temperature, and EMG data without sensor interference. In addition, we integrated an onboard data processing unit with Internet of Things (IoT) capabilities for real-time acquisition, processing, and wireless transmission of sensor measurements. Sweat cortisol and EMG signals were measured during cycling exercises to evaluate the sensor suite’s performance. Our results demonstrate an increase in sweat cortisol levels and decrease in the EMG signal’s power spectral density following exercise. These findings suggest that combining sweat cortisol levels with EMG signals in real-time could serve as valuable indicators for stress assessment and early detection of abnormal physiological changes.
Springer Science and Business Media LLC
Title: StressFit: A Hybrid Wearable Physicochemical Sensor Suite for Simultaneously Measuring Electromyogram and Sweat Cortisol
Description:
Abstract
This study introduces StressFit, a novel hybrid wearable sensor system designed to simultaneously monitor electromyogram (EMG) signals and sweat cortisol levels.
Our approach involves the development of a noninvasive skin patch capable of monitoring skin temperature, sweat pH, cortisol levels, and corresponding EMG signals using a combination of physical and electrochemical sensors integrated with EMG electrodes.
StressFit was optimized by enhancing sensor output and mechanical resilience for practical application on curved body surfaces, ensuring accurate acquisition of cortisol, pH, body temperature, and EMG data without sensor interference.
In addition, we integrated an onboard data processing unit with Internet of Things (IoT) capabilities for real-time acquisition, processing, and wireless transmission of sensor measurements.
Sweat cortisol and EMG signals were measured during cycling exercises to evaluate the sensor suite’s performance.
Our results demonstrate an increase in sweat cortisol levels and decrease in the EMG signal’s power spectral density following exercise.
These findings suggest that combining sweat cortisol levels with EMG signals in real-time could serve as valuable indicators for stress assessment and early detection of abnormal physiological changes.
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