{"title":"Stress detection and reduction using EEG signals","authors":"M. S. Kalas, B. Momin","doi":"10.1109/ICEEOT.2016.7755604","DOIUrl":null,"url":null,"abstract":"According to world health organization, stress is a significant problem of our times and affects both physical as well as the mental health of people. There are various traditional stress detection methods are available. Research in area of stress detection has developed many techniques for monitoring the human brain that can be used to study the human behavior. However, there are researches on stress detection methods and not on stress reduction methods in terms of technology. This research proposes a novel method that detects the stress using EEG signals and reduces the stress by introducing the interventions into the system. This research uses the k-means clustering method to measure the perceived stress which divide the subjects into different categories and estimate the stress level. The proposed method is useful in developing products for human stress reduction. The success of implementation and development of this research will expected to help in reducing time consumed and human power in determining best solution for stress management.","PeriodicalId":383674,"journal":{"name":"2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEOT.2016.7755604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37
Abstract
According to world health organization, stress is a significant problem of our times and affects both physical as well as the mental health of people. There are various traditional stress detection methods are available. Research in area of stress detection has developed many techniques for monitoring the human brain that can be used to study the human behavior. However, there are researches on stress detection methods and not on stress reduction methods in terms of technology. This research proposes a novel method that detects the stress using EEG signals and reduces the stress by introducing the interventions into the system. This research uses the k-means clustering method to measure the perceived stress which divide the subjects into different categories and estimate the stress level. The proposed method is useful in developing products for human stress reduction. The success of implementation and development of this research will expected to help in reducing time consumed and human power in determining best solution for stress management.