Cross-subject classification of depression by using multiparadigm EEG feature fusion

• Published in: Computer methods and programs in biomedicine Vol. 233; p. 107360
• Main Authors: Yang, Jianli, Zhang, Zhen, Fu, Zhiyu, Li, Bing, Xiong, Peng, Liu, Xiuling
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.05.2023
• Subjects: Brain; Cross-subject; Depression; Depression - diagnosis; EEG; Electroencephalography - methods; Eye; Feature fusion; Multiparadigm; Support Vector Machine; Multiparadigm; Depression; Feature fusion; Cross-subject; EEG

•A multiparadigm feature fusion method was proposed to distinguish depression.•The significance of EEG feature from eyes open and closed in the resting state for depression classification were discussed and compared in detail.•It proved that fusion of eyes open and closed EEG can efficiently promote...