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　　目前在研项目：

2019.12–2024.11，国家重点研发计划，2019YFA0706200，基于心理生理多模态信息的抑郁障碍早期识别与干预方法，子课题负责人。

　　近5年主要论文如下：

[1]Cai H, Qu Z, et al. Feature-level fusion approaches based on multimodal EEG data for depression recognition[J]. Information Fusion. 2020, 59 (2020): 127-138. (SCI一区IF 10.716)

[2]Cai H, Zhang X, et al. A Case-based Reasoning Model for Depression based on Three-electrode EEG Data[J].IEEE Transactions on Affective Computing. 2018. (SCI二区IF 6.288)

[3]Cai H, Han J, et al. A Pervasive Approach to EEG-based Depression Detection[J]. Complexity. 2018. (SCI二区IF2.591)

[4]Cai H, Chen Y, et al. Study on Feature Selection Methods for Depression Detection Using Three-Electrode EEG Data[J]. Interdisciplinary Sciences: Computational Life Sciences. 2018, 2018: 1-8. (SCI三区IF1.418)

[5]Cai H, Zhang Y, et al. Study on Depression Classification Based on Electroencephalography Data Collected by Wearable Devices[C]. 2017 International Conference on Brain Informatics. Springer, Cham, 2017: 244-253. (EI)

[6]Cai H, Wang Z, et al. A Virtual-Reality Based Neurofeedback Game Framework for Depression Rehabilitation using Pervasive Three-Electrode EEG Collector[C]. Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing. ACM, 2017: 173-176. (EI)

[7]Cai H, Sha X, et al. Pervasive EEG diagnosis of depression using Deep Belief Network with three-electrodes EEG collector[C]. Bioinformatics and Biomedicine (BIBM), 2016 IEEE International Conference on. IEEE, 2016: 1239-1246. (CCF B类)

[8]Cai H, Wei S, et al. Brief Discussion on Current Computerized Cognitive Behavioral Therapy[C]. International Conference on Brain Informatics and Health. Springer, Cham, 2015: 420-431. (EI)

[9]Cai H, Wang Z, et al. A Novel Depression Rehabilitation Game Framework Using VR Based on Neurofeedback[J].计算机工程, 2018, 44(10): 264-273,280.(CSCD)

2019.06-至今，担任中国医学救援协会神经生物反馈治疗与干预分会副秘书长