Desok Kim, Yunhwan Seo, Sook-hyun Kim, Suntae Jung
{"title":"Short Term Analysis of Long Term Patterns of Heart Rate Variability in Subjects under Mental Stress","authors":"Desok Kim, Yunhwan Seo, Sook-hyun Kim, Suntae Jung","doi":"10.1109/BMEI.2008.272","DOIUrl":null,"url":null,"abstract":"Long term patterns of heart rate variability (HRV) features were decreased in subjects with higher self reporting stress scores. For mobile applications, short term analysis of HRV features may be ideal since conventional heartbeat recordings (3-5 min) might be inadequately long. In this study, short term analysis has been performed for heartbeat data obtained at five different time points from two subject groups (15 under high and 18 under low mental stress). The reliability of short term heartbeat data was demonstrated by detecting significant differences in long term patterns of HR V features between two groups. Fifteen to thirty second heartbeat measurements were long enough to produce reliable long term patterns of HRVfeatures. Thus, short and intermittent recordings of heartbeats could be used to detect long term HR Vpatterns and offer a convenient method to monitor mental stress in mobile environments.","PeriodicalId":138702,"journal":{"name":"2008 International Conference on BioMedical Engineering and Informatics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on BioMedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2008.272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
Long term patterns of heart rate variability (HRV) features were decreased in subjects with higher self reporting stress scores. For mobile applications, short term analysis of HRV features may be ideal since conventional heartbeat recordings (3-5 min) might be inadequately long. In this study, short term analysis has been performed for heartbeat data obtained at five different time points from two subject groups (15 under high and 18 under low mental stress). The reliability of short term heartbeat data was demonstrated by detecting significant differences in long term patterns of HR V features between two groups. Fifteen to thirty second heartbeat measurements were long enough to produce reliable long term patterns of HRVfeatures. Thus, short and intermittent recordings of heartbeats could be used to detect long term HR Vpatterns and offer a convenient method to monitor mental stress in mobile environments.