Applications and challenges of wearable electroencephalogram signals in depression recognition and personalized music intervention.
10.7507/1001-5515.202210065
- Author:
Xingran CUI
1
;
Zeguang QIN
1
;
Zhilin GAO
1
;
Wang WAN
1
;
Zhongze GU
1
Author Information
1. School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.
- Publication Type:Journal Article
- Keywords:
Brain-computer music interface;
Depression recognition;
Personalized intervention;
Wearable electroencephalogram signals
- MeSH:
Humans;
Algorithms;
Depression/therapy*;
Music;
Music Therapy;
Electroencephalography;
Wearable Electronic Devices
- From:
Journal of Biomedical Engineering
2023;40(6):1093-1101
- CountryChina
- Language:Chinese
-
Abstract:
Rapid and accurate identification and effective non-drug intervention are the worldwide challenges in the field of depression. Electroencephalogram (EEG) signals contain rich quantitative markers of depression, but whole-brain EEG signals acquisition process is too complicated to be applied on a large-scale population. Based on the wearable frontal lobe EEG monitoring device developed by the authors' laboratory, this study discussed the application of wearable EEG signal in depression recognition and intervention. The technical principle of wearable EEG signals monitoring device and the commonly used wearable EEG devices were introduced. Key technologies for wearable EEG signals-based depression recognition and the existing technical limitations were reviewed and discussed. Finally, a closed-loop brain-computer music interface system for personalized depression intervention was proposed, and the technical challenges were further discussed. This review paper may contribute to the transformation of relevant theories and technologies from basic research to application, and further advance the process of depression screening and personalized intervention.
