Presentation Title
Development of a Modular Wearable Sensing Device for Stress Estimation
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 Name
Jeff Frolik
Faculty/Staff Collaborators
Ryan S. McGinnis (Graduate Student Mentor), Jeff Frolik (Graduate Student Mentor)
Status
Graduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Electrical Engineering
Primary Research Category
Engineering & Physical Sciences
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.