An Individual-Oriented Algorithm for Stress Detection in Wearable Sensor Measurements

Abstract

Accurately measuring a person's level of stress can have a wide variety of impacts, not only for human health, but also for the perceived feeling of safety when going after daily habits, such as walking, cycling, or driving from one place to another. While there is a vast amount of research done on stress and the related physiological responses of the human body, there is no go-to method when it comes to measuring acute stress in a live setting. This work proposes an advancement of the rule-based stress detection algorithm proposed in [1], to identify moments of stress (MOS) more reliably, through an adaptation and an individualization of the rules proposed in the original paper. The proposed algorithm leverages electrodermal activity and skin temperature, both recorded by the Empatica E4 wristband, for the assessment of an individual's stress when exposed to an audible stimulus. The algorithm achieves an average recall of 81.31%, with a precision of 46.23%, and an accuracy of 92.74%, measured on 16 test subjects. The trade-off between precision and recall can be controlled by adjusting the MOS threshold that needs to be reached for a MOS to be detected.

Stress Assessment for Augmented Reality Applications Based on Head Movement Features

“…The unpleasant pictures in the International Affective Picture System (IAPS) database can be used to induce a stress response [21]. In [22], [23], the onset of stress is caused by a horn sound played randomly during the test. In the Cold Pressor Test [24], participants are asked to immerse a hand or foot in cold water.…”

ENSS (Expanded Nursing Stress Assessment) version 1,0: An Android-Based Mobile Application Efficient Stress Assessment in Nurses

“…The Cronbach value of the Indonesian version of ENSS is 0.956 and the test-retest reliability test obtained an Intra-Class Correlation value of 0.939, which means that the Indonesian version of ENSS has good internal stability. Indicators for this instrument include: death and dying, conflicts with doctors, insufficient preparation, problems with co-workers, problems with supervisors/superiors, workload, unclear treatment, problems with patient families and discrimination [26].…”

“…There are several components of an Android application, namely: activity, broadcast receiver, service and content provider. Android software development kit is a tool used to create Android platform applications with the Java programming language which includes development tools, emulators and libraries needed to build Android applications [26].…”

Personalized Stress Detection Using Biosignals from Wearables: A Scoping Review

“…Like machine learning, this approach heavily depends on the signal selected to identify stress and quality of such signal. For this reason, all the studies utilizing the statistical approach included in the review employ signal filtering methods based on motion detection [23] and filters [43,52]. Regarding the signals examined in the studies, two focused on EDA [23,52], while one considered PPG [43].…”

“…For this reason, all the studies utilizing the statistical approach included in the review employ signal filtering methods based on motion detection [23] and filters [43,52]. Regarding the signals examined in the studies, two focused on EDA [23,52], while one considered PPG [43]. In general, the pipeline employed by studies based on statistical approaches can be summarized in two main steps, with an optional third step: collecting a baseline (composed of filtered biosignals) for the subject, constructing rules through statistical algorithms, and potentially adapting these rules on the fly over time.…”