EEG-based estimation of mental fatigue by using KPCA-HMM and complexity parameters

Biomedical Signal Processing and Control

Volumn 5, Issue 2, 2010, Pages 124-130

  Liu, Jianping ^a   Zhang, Chong ^b   Zheng, Chongxun ^b  

^a Network and Information Security Key Laboratory   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Approximate entropy (ApEn); Electroencephalogram (EEG); Kolmogorov complexity (Kc); KPCA HMM; Mental fatigue

Indexed keywords

COMPUTATIONAL COMPLEXITY; DISEASES; ELECTROENCEPHALOGRAPHY; ENTROPY; HIDDEN MARKOV MODELS;

APPROXIMATE ENTROPY; ELECTRO-ENCEPHALOGRAM (EEG); KOLMOGOROV COMPLEXITY; KPCA-HMM; MENTAL FATIGUE;

PARAMETER ESTIMATION;

ACCURACY; ADULT; ALGORITHM; ARTICLE; CLASSIFICATION; CORRELATION ANALYSIS; DYNAMICS; DYSTHYMIA; ELECTROENCEPHALOGRAM; ENTROPY; HIDDEN MARKOV MODEL; HUMAN; KERNEL METHOD; KOLMOGOROV SMIRNOV TEST; MALE; MODEL; NORMAL HUMAN; PARAMETER; PERFORMANCE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; STATISTICAL SIGNIFICANCE;

EID: 77956650358     PISSN: 17468094     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.bspc.2010.01.001     Document Type: Article

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