Anita Beigzadeh, Vahid Yazdnian, Kamaledin Setarehdan
{"title":"Mental Stress Detection and Performance Enhancement Using FNIRS and Wrist Vibrator Biofeedback","authors":"Anita Beigzadeh, Vahid Yazdnian, Kamaledin Setarehdan","doi":"arxiv-2409.08089","DOIUrl":null,"url":null,"abstract":"Any person in his/her daily life activities experiences different kinds and\nvarious amounts of mental stress which has a destructive effect on their\nperformance. Therefore, it is crucial to come up with a systematic way of\nstress management and performance enhancement. This paper presents a\ncomprehensive portable and real-time biofeedback system that aims at boosting\nstress management and consequently performance enhancement. For this purpose, a\nreal-time brain signal acquisition device, a wireless vibration biofeedback\ndevice, and a software-defined program for stress level classification have\nbeen developed. More importantly, the entire system has been designed to\npresent minimum time delay by propitiously bridging all the essential parts of\nthe system together. We have presented different signal processing and feature\nextraction techniques for an online stress detection application. Accordingly,\nby testing the stress classification section of the system, an accuracy of 83%\nand a recall detecting the true mental stress level of 92% was achieved.\nMoreover, the biofeedback system as integrity has been tested on 20\nparticipants in the controlled experimental setup. Experiment evaluations show\npromising results of system performances, and the findings reveal that our\nsystem is able to help the participants reduce their stress level by 55% and\nincrease their accuracy by 24.5%. It can be concluded from the observations\nthat all primary premises on stress management and performance enhancement\nthrough reward learning are valid as well.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Any person in his/her daily life activities experiences different kinds and
various amounts of mental stress which has a destructive effect on their
performance. Therefore, it is crucial to come up with a systematic way of
stress management and performance enhancement. This paper presents a
comprehensive portable and real-time biofeedback system that aims at boosting
stress management and consequently performance enhancement. For this purpose, a
real-time brain signal acquisition device, a wireless vibration biofeedback
device, and a software-defined program for stress level classification have
been developed. More importantly, the entire system has been designed to
present minimum time delay by propitiously bridging all the essential parts of
the system together. We have presented different signal processing and feature
extraction techniques for an online stress detection application. Accordingly,
by testing the stress classification section of the system, an accuracy of 83%
and a recall detecting the true mental stress level of 92% was achieved.
Moreover, the biofeedback system as integrity has been tested on 20
participants in the controlled experimental setup. Experiment evaluations show
promising results of system performances, and the findings reveal that our
system is able to help the participants reduce their stress level by 55% and
increase their accuracy by 24.5%. It can be concluded from the observations
that all primary premises on stress management and performance enhancement
through reward learning are valid as well.