Presentation Title

Development of a Modular Wearable Sensing Device for Stress Estimation

Project Collaborators

Ryan S. McGinnis (Graduate Student Mentor), Jeff Frolik (Graduate Student Mentor)

Abstract

To varying degrees, mental and physical stress levels affect all individuals. The manifestation of this stress can have far reaching consequences for employers, from reduced work output and workplace absenteeism to increased workplace negligence and dangerous practices. Before such issues can be properly rectified, there must exist some practical method to quantize stress levels. Traditionally, clinical stress estimation has consisted of self-evaluation methods which suffer inherently from subjectivity. In this work, the authors develop a low-cost and modular wearable sensing device to explore whether methods of self-estimated stress quantification correlate with measurements of physiological signals as collected by the device. In a small scale study, heart rate data collected by the wearable sensing garment strongly correlated with self-perceived stress values (R = 0.75, p < .001). These preliminary results show promise that the garment can serve as a valuable tool in the collection and evaluation of biosignals of clinical interest.

Primary Faculty Mentor Name

Ryan S. McGinnis

Secondary Mentor NetID

jfrolik

Secondary Mentor Name

Jeff Frolik

Status

Graduate

Student College

College of Engineering and Mathematical Sciences

Program/Major

Electrical Engineering

Primary Research Category

Engineering & Physical Sciences

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Development of a Modular Wearable Sensing Device for Stress Estimation

To varying degrees, mental and physical stress levels affect all individuals. The manifestation of this stress can have far reaching consequences for employers, from reduced work output and workplace absenteeism to increased workplace negligence and dangerous practices. Before such issues can be properly rectified, there must exist some practical method to quantize stress levels. Traditionally, clinical stress estimation has consisted of self-evaluation methods which suffer inherently from subjectivity. In this work, the authors develop a low-cost and modular wearable sensing device to explore whether methods of self-estimated stress quantification correlate with measurements of physiological signals as collected by the device. In a small scale study, heart rate data collected by the wearable sensing garment strongly correlated with self-perceived stress values (R = 0.75, p < .001). These preliminary results show promise that the garment can serve as a valuable tool in the collection and evaluation of biosignals of clinical interest.