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.
如何实现快速准确的识别和有效的非药物干预是目前抑郁症领域亟待解决的难题。脑电信号蕴藏丰富的抑郁症定量标记，但全脑脑电信号的采集操作过程繁琐，不易应用于大规模人群。本文基于笔者课题组自主研发的可穿戴额叶脑电信号监测设备及其在抑郁症识别和干预中的应用展开讨论，介绍可穿戴脑电信号监测设备的技术原理和常见类型，综述基于可穿戴脑电信号的抑郁症识别关键技术及其存在的技术瓶颈。最后，本文提出一种面向抑郁症个性化干预的闭环脑机音乐接口系统，并进一步探讨了其所面临的技术挑战。本文有助于促进相关理论和技术从基础研究向应用转化，推动抑郁症筛查和个性化干预的进程。.
Keywords: Brain-computer music interface; Depression recognition; Personalized intervention; Wearable electroencephalogram signals.