A cross-subject MDD detection approach based on multiscale nonlinear analysis in resting state EEG

• Published in: Neuroscience Vol. 582; pp. 1 - 10
• Main Authors: Zhang, Zhen, Yang, Jianli, Xiong, Peng, Hao, Huaqing, Zhang, Jieshuo, Li, Licong, Wang, Changyong, Liu, Xiuling
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 30.08.2025
• Subjects: Adult; Brain - physiopathology; Cross-subject; Depressive Disorder, Major - diagnosis; Depressive Disorder, Major - physiopathology; Electroencephalography - methods; Female; Humans; Male; MDD; Middle Aged; Multiscale; Nonlinear Dynamics; Rest - physiology; Resting state EEG; Signal Processing, Computer-Assisted; Young Adult; Resting state EEG; MDD; Cross-subject; Multiscale

•A multiscale nonlinear feature fusion method is proposed to detect MDD patients.•Cross-subject experiments are conducted on multi datasets to validate the experimental results.•LZC of high frequency scale in resting state EEG signals is proved to be more effective for MDD diagnosis. Exploring multi...