Selection of Optimal Physiological Features for Accurate Detection of Stress

Abstract

Stress is an established risk factor in the development of addiction and in reinstating drug seeking. Substance use disorder (SUD) is a dangerous epidemic that affects the brain and behavior. Despite this growing epidemic and its subsequent consequences, there are limited management and treatment options, pharmacotherapies and psychosocial treatments available. To this end, there is a need for new and improved personalized devices and treatments for the detection and management of SUD. Based on documented negative effects of stress in SUD, in this paper, our objective was to select a few significant physiological features from a set of 8 features collected by a chest-worn RespiBAN Professional in 15 individuals. We used three machine learning classifiers on these optimal physiological features to detect stress. Our results indicate that best accuracies were achieved when electrodermal activity (EDA), body temperature and chest-worn accelerometer were considered as features for the classification. Challenges, implications and applications were discussed. In the near future, the proposed methods will be replicated in individuals with SUD.

Identifying Biomarkers for Accurate Detection of Stress

“…In contrast to our preliminary work [19], three different types of classification were performed in order to differentiate social stress and mental stress, and to also explore the effects of meditation on stress:…”

“…This differentiation will prove to be useful in the further stages of this project, as the type of stress can dictate which prevention or intervention method will be the most efficient and effective. Preliminary results from this work were published in [19].…”

Low-cost monitoring for stimulus detection in skin conductance

“…Several hardware technologies have been developed to integrate different physiological quantities into wearables, enabled with wireless connectivity according to the Internet of Things (IoT) [1], [2]. Wearables are often used with the aim of acquiring those parameters that evaluate the subject physiological status, from the physical and health perspective [3]- [8] to the cognitive and emotional one [9]- [11]. Indeed, the connection of smart devices to networking systems can reduce unnecessary hospital visits and lower the burden on healthcare services, by transferring data over secure infrastructures.…”