Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal

Computer Methods and Programs in Biomedicine

Volumn 109, Issue 3, 2013, Pages 339-345

  Hosseinifard, Behshad ^a   Moradi, Mohammad Hassan ^a   Rostami, Reza ^b  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Correlation dimension; Depression; Detrended fluctuation analysis; EEG; Higuchi fractal; Lyapunov exponent

Indexed keywords

CLASSIFICATION ACCURACY; COMPLEMENTARY TOOLS; CORRELATION DIMENSIONS; DEPRESSION; DETRENDED FLUCTUATION ANALYSIS; EEG SIGNALS; IMPORTANT FEATURES; K-NEAREST NEIGHBORS; LINEAR DISCRIMINANT ANALYSIS; LOGISTIC REGRESSIONS; LYAPUNOV EXPONENT; MACHINE LEARNING TECHNIQUES; NONLINEAR FEATURES; NORMAL CONTROLS;

DIFFERENTIAL EQUATIONS; ELECTROENCEPHALOGRAPHY; FRACTAL DIMENSION; LEARNING SYSTEMS; LOGISTICS; LYAPUNOV FUNCTIONS; NONLINEAR ANALYSIS;

LYAPUNOV METHODS;

ADULT; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; CORRELATION DIMENSION ANALYSIS; DEPRESSION; DETRENDED FLUCTUATION ANALYSIS; ELECTROENCEPHALOGRAPHY; FEMALE; FRACTAL ANALYSIS; GENETIC ALGORITHM; HIGUCHI FRACTAL ANALYSIS; HUMAN; K NEAREST NEIGHBOR; LINEAR SYSTEM; LOGISTIC REGRESSION ANALYSIS; LYAPUNOV EXPONENT ANALYSIS; MACHINE LEARNING; MALE; NONLINEAR SYSTEM; PATIENT CODING;

ADULT; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN MAPPING; COMPUTER SIMULATION; DEPRESSION; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAPHY; FEMALE; FRACTALS; HUMANS; LEAST-SQUARES ANALYSIS; LOGISTIC MODELS; MALE; MIDDLE AGED; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; SOFTWARE;

EID: 84874239884     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2012.10.008     Document Type: Article

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