Computer-aided diagnosis of depression using EEG signals

• Main Authors: Acharya, U.R., Sudarshan, V.K., Adeli, H., Santhosh, J., Koh, J.E.W., Adeli, A.
• Format: Article
• Language: English
• Published: KARGER, ALLSCHWILERSTRASSE 10, CH-4009 BASEL, SWITZERLAND 2015
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/15746/1/Computer-Aided_Diagnosis_of_Depression_Using_EEG_Signals.pdf; http://eprints.um.edu.my/15746/; http://www.ncbi.nlm.nih.gov/pubmed/25997732

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 depres...