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Depression and fatigue analysis using a mental-physical model

Authors
Tian, X.-W.Zhang, Z.-X.Lee, S.-H.Yoon, H.-J.Lim, J.S.
Issue Date
2013
Keywords
Depression; Electroencephalography (EEG); Fatigue; Heart rate variability (HRV); Mental-physical; Takagi-Sugeno defuzzification
Citation
Lecture Notes in Electrical Engineering, v.215 LNEE, pp.813 - 817
Journal Title
Lecture Notes in Electrical Engineering
Volume
215 LNEE
Start Page
813
End Page
817
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14894
DOI
10.1007/978-94-007-5860-5_97
ISSN
1876-1100
Abstract
Recent 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.
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College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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