M. Subramanian, V. Kanishkan, P. Venkatesan, S. Vivek, S. Maheswari
{"title":"Psychological Stress Monitoring and Reporting System for Industries","authors":"M. Subramanian, V. Kanishkan, P. Venkatesan, S. Vivek, S. Maheswari","doi":"10.1109/TIIEC.2013.26","DOIUrl":null,"url":null,"abstract":"This project focuses on combining cognitive cues with the conventional physiological cues to have an improved approach for detecting stress. Current stress detection techniques rely on the measurement of certain physiological parameters based on which they determine stress. However, these techniques are not completely reliable because of the effect of other phenomenon on the physiological parameters. In this paper, an alternative method is proposed for the same purpose which involves the extraction of various cognitive features along with the traditional physiological data and processing it through neural networks aiming to make the results more accurate than existing system.","PeriodicalId":250687,"journal":{"name":"2013 Texas Instruments India Educators' Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Texas Instruments India Educators' Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIIEC.2013.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This project focuses on combining cognitive cues with the conventional physiological cues to have an improved approach for detecting stress. Current stress detection techniques rely on the measurement of certain physiological parameters based on which they determine stress. However, these techniques are not completely reliable because of the effect of other phenomenon on the physiological parameters. In this paper, an alternative method is proposed for the same purpose which involves the extraction of various cognitive features along with the traditional physiological data and processing it through neural networks aiming to make the results more accurate than existing system.