Computer-aided diagnosis of depression using EEG signals

Acharya, U.R. and Sudarshan, V.K. and Adeli, H. and Santhosh, J. and Koh, J.E.W. and Adeli, A. (2015) Computer-aided diagnosis of depression using EEG signals. European Neurology, 73 (5-6). pp. 329-336. ISSN 0014-3022 , DOI

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The complex, nonlinear and non-stationary electroencephalogram (EEG) signals are very tedious to interpret visually and highly difficult to extract the significant features from them. The linear and nonlinear methods are effective in identifying the changes in EEG signals for the detection of depression. Linear methods do not exhibit the complex dynamical variations in the EEG signals. Hence, chaos theory and nonlinear dynamic methods are widely used in extracting the EEG signal features for computer-aided diagnosis (CAD) of depression. Hence, this article presents the recent efforts on CAD of depression using EEG signals with a focus on using nonlinear methods. Such a CAD system is simple to use and may be used by the clinicians as a tool to confirm their diagnosis. It should be of a particular value to enable the early detection of depression. (C) 2015 S. Karger AG, Basel

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Additional Information: ISI Document Delivery No.: CJ2LS Times Cited: 0 Cited Reference Count: 98 Cited References: Acharya R. 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Rajendra Sudarshan, Vidya K. Adeli, Hojjat Santhosh, Jayasree Koh, Joel E. W. Adeli, Amir Engineering, Faculty /I-7935-2015 Engineering, Faculty /0000-0002-4848-7052 0 KARGER BASEL EUR NEUROL
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 08 Apr 2016 02:26
Last Modified: 08 Apr 2016 02:26

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