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A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis

Reza Akbari Movahed, Gila Pirzad Jahromi, Shima Shahyad, Gholam Hossein Meftahi

2021Journal of Neuroscience Methods128 citationsDOI

Topics & Concepts

Support vector machineArtificial intelligencePattern recognition (psychology)Feature selectionElectroencephalographyComputer scienceMajor depressive disorderClassifier (UML)WaveletMachine learningFeature extractionPsychologyPsychiatryCognitionEEG and Brain-Computer InterfacesEmotion and Mood RecognitionFunctional Brain Connectivity Studies
A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis | Litcius