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Depression and fatigue analysis using a mental-physical model

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dc.contributor.authorTian, X.-W.-
dc.contributor.authorZhang, Z.-X.-
dc.contributor.authorLee, S.-H.-
dc.contributor.authorYoon, H.-J.-
dc.contributor.authorLim, J.S.-
dc.date.available2020-02-29T00:47:23Z-
dc.date.created2020-02-12-
dc.date.issued2013-
dc.identifier.issn1876-1100-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14894-
dc.description.abstractRecent research has indicated a significant association between depression and fatigue. To analyze depression and fatigue, an experiment was conducted that provided the subjects with affective content to induce a variety of emotions and heart rate variability (HRV). This paper presents a mental-physical model that describes the relationship between depression and fatigue by using a neuro-fuzzy network with a weighted fuzzy membership function using two time-domain and four frequency-domain features of HRV. HRV data were collected from 24 patients. At the end of the experiment, we determined the relationship between depression and fatigue with the mental-physical model, and our analysis results had an accuracy of 95.8 %. © 2013 Springer Science+Business Media.-
dc.language영어-
dc.language.isoen-
dc.relation.isPartOfLecture Notes in Electrical Engineering-
dc.subjectDefuzzifications-
dc.subjectDepression-
dc.subjectFatigue analysis-
dc.subjectFrequency domains-
dc.subjectFuzzy membership function-
dc.subjectHeart rate variability-
dc.subjectMental-physical-
dc.subjectNeuro-fuzzy network-
dc.subjectRecent researches-
dc.subjectTime domain-
dc.subjectElectroencephalography-
dc.subjectElectrophysiology-
dc.subjectFatigue of materials-
dc.subjectHeart-
dc.subjectExperiments-
dc.titleDepression and fatigue analysis using a mental-physical model-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.doi10.1007/978-94-007-5860-5_97-
dc.identifier.bibliographicCitationLecture Notes in Electrical Engineering, v.215 LNEE, pp.813 - 817-
dc.identifier.scopusid2-s2.0-84874159318-
dc.citation.endPage817-
dc.citation.startPage813-
dc.citation.titleLecture Notes in Electrical Engineering-
dc.citation.volume215 LNEE-
dc.contributor.affiliatedAuthorTian, X.-W.-
dc.contributor.affiliatedAuthorLee, S.-H.-
dc.contributor.affiliatedAuthorYoon, H.-J.-
dc.contributor.affiliatedAuthorLim, J.S.-
dc.type.docTypeConference Paper-
dc.subject.keywordAuthorDepression-
dc.subject.keywordAuthorElectroencephalography (EEG)-
dc.subject.keywordAuthorFatigue-
dc.subject.keywordAuthorHeart rate variability (HRV)-
dc.subject.keywordAuthorMental-physical-
dc.subject.keywordAuthorTakagi-Sugeno defuzzification-
dc.subject.keywordPlusDefuzzifications-
dc.subject.keywordPlusDepression-
dc.subject.keywordPlusFatigue analysis-
dc.subject.keywordPlusFrequency domains-
dc.subject.keywordPlusFuzzy membership function-
dc.subject.keywordPlusHeart rate variability-
dc.subject.keywordPlusMental-physical-
dc.subject.keywordPlusNeuro-fuzzy network-
dc.subject.keywordPlusRecent researches-
dc.subject.keywordPlusTime domain-
dc.subject.keywordPlusElectroencephalography-
dc.subject.keywordPlusElectrophysiology-
dc.subject.keywordPlusFatigue of materials-
dc.subject.keywordPlusHeart-
dc.subject.keywordPlusExperiments-
dc.description.journalRegisteredClassscopus-
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