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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