Publication:
Comparison of heart rate variability measures for mental stress detection

dc.contributor.authorSansanee Boonnithien_US
dc.contributor.authorSukanya Phongsuphapen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-05-03T08:08:30Z
dc.date.available2018-05-03T08:08:30Z
dc.date.issued2011-12-01en_US
dc.description.abstractMental stress is one of the well known major risk factors for many diseases such as hypertension, coronary artery disease, heart attack, etc. Conventionally, detecting mental stress in an individual is performed by interviews and/or questionnaires. In this study, we have investigated various heart rate variability (HRV) measures for detecting mental stress by using ultra short term HRV analysis. A number of HRV measures were investigated, e.g, Mean of heart rates (mHR), Mean of RR intervals (mRR), Power spectra in Very Low (VLF), Low (LF), and High (HF) frequency ranges, Symphatovagal balance index (SVI), etc. Experiments involved 60 segments of RR interval time series signals during mental stress state and normal state. Results revealed that the following HRV measures: mRR, mHR, normalized LF, difference between normalized LF and normalized HF, and SVI were effective measures for mental stress state and normal state classification. © 2011 CCAL.en_US
dc.identifier.citationComputing in Cardiology. Vol.38, (2011), 85-88en_US
dc.identifier.issn2325887Xen_US
dc.identifier.issn23258861en_US
dc.identifier.other2-s2.0-84859989883en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/11750
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84859989883&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectMedicineen_US
dc.titleComparison of heart rate variability measures for mental stress detectionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84859989883&origin=inwarden_US

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