学科信息

张瑞，博士，副教授，硕士生导师，东莞市特色人才，主要从事人工智能、脑机接口方法和技术研究，紧密围绕重度瘫痪病人的脑机接口功能辅助与康复这一医工交叉领域的重要科学问题，在面向脊髓损伤患者的功能辅助和面向脑卒中患者的运动功能康复两方面取得了系统性创新成果。近年来，主持国家自然科学基金项目、粤港澳大湾区脑科学与类脑研究项目在内的多个项目；发表学术论文10余篇，授权国家发明专利3项，曾获得IEEE TBME封面论文奖、IEEE TNSRE亮点论文奖、吴文俊人工智能科学技术发明奖一等奖和中国自动化学会技术发明一等奖等重量级奖项。

科研项目：

1、基于多模态信号脑机协调控制及其应用研究，国家自然科学基金青年项目，项目批准号：61703101，直接费用：25万元，主持

2、脑机互适应协同控制技术与上肢运动康复研究，粤港澳大湾区脑科学与类脑研究中心开放课题，项目批准号：2019015，直接费用：15万元，主持

论文：

1. Z. Rao, R. Zhang(通讯作者), S. He, Y. Zhou, Z. Lu, K. Li, and Y. Li, “A Once-Calibration Brain-Computer Interface to Enhance Convenience for Continuous BCI Interventions in Stroke Patients,” IEEE Sensors Journal, vol.25, pp. 3949 - 3963, 2025.

2. Z. Rao, J. Zhu, Z. Lu, R. Zhang(通讯作者), K. Li, Z. Guan, and Y. Li, "A Wearable Brain-Computer Interface With Fewer EEG Channels for Online Motor Imagery Detection," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 32, pp. 4143-4154, 2024.

3. R. Zhang, C. Wang, S. He, C. Zhao, K. Zhang, X. Wang and Y. Li, “An Adaptive Brain-Computer Interface to Enhance Motor Recovery After Stroke,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31,pp. 2268 – 2278, May 2023. (JCR Q1，长文，IF:4.528)

4. R. Zhang, S. He, X. Yang, X. Wang, K. Li, Q. Huang, Z. Gu, Z. Yu, X. Zhang, D. Tang, Y. Li*. “An EOG-based Human Machine Interface to Control a Smart Home Environment for Patients with Severe Spinal Cord Injuries,”IEEE Transactions on Biomedical Engineering, vol. 66, no. 1,pp. 89 – 100, Jan. 2019.  (JCR Q1，长文，IF:4.288)

5. R. Zhang, Q. Wang, K. Li, S. He, S. Qin, Z. Feng, Y. Chen, P. Song, T. Yang, Y. Zhang, Z. Yu, Y. Hu, M. Shao*, Y. Li*, “A BCI-based Environmental Control System for Patients with Severe Spinal Cord Injuries,” IEEE Transactions on Biomedical Engineering, vol. 64, no. 8,pp. 1959– 1971, Aug. 2017. (JCR Q1，长文，IF: 4.288, 亮点论文)

6. R. Zhang, Y. Li, Y. Yan, H. Zhang, S. Wu, T. Yu, and Z. Gu, “Control of a Wheelchair in a Indoor Environment Based on a Brain computer interface and automated navigation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 24, no. 1,pp. 128 – 139, Jan. 2016. (JCR Q1, 长文，IF:4.528, 封面论文)

7. S. He, R. Zhang, Q. Wang, Y. Cheng, T. Yang, Z. Feng, Y. Zhang, M. Shao*, Y. Li*, “A P300-based Threshold-free Brain Switch and Its Application in Wheelchair Control,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 6,pp. 715– 725, July. 2016. (JCR Q1, 长文，IF: 4.528)

8. J. Pan, Y. Li, R. Zhang, Z. Gu, and F. Li, “Discrimination Between Control and Idle States in Asynchronous SSVEP-Based Brain Switches: A Pseudo-Key-Based Approach,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 21, no. 3, pp. 435–443, May 2013. (JCR Q1, 长文，IF:4.528)

9. S. He, Y. Zhou, T. Yu, R. Zhang, Q. Huang, L. Chuai, M. Musfafa, Z. Gu, Z. Yu, H. Tan, Y.Li*. “EEG- and EOG-based Asynchronous Hybrid BCI: A System Integrating a Speller, a Web Browser, an E-mail Client, and a File Explorer,” IEEE Transactions on Neural System and Rehabilitation Engineering, vol. 28, no.2, pp. 519 - 530, Feb. 2020. (JCR Q1, 长文，IF:4.528)

10. T. Yu, J. Xiao, F. Wang, R. Zhang, Z. Gu, A. Cichocki and Y. Li, “Enhanced motor imagery training using a hybrid BCI with feedback,” IEEE Transactions on Biomedical Engineering, vol. 62, pp. 1706 - 1717, July 2015. (JCR Q1, 长文，IF:4.288)

11. Q. Huang, Y. Chen, Z. Zhang, S. He, R. Zhang, J. Liu, Y. Zhang, M. Shao, Y. Li*. “An EOG-based wheelchair robotic arm system for assisting patients with severe spinal cord injuries,” Journal of Neural Engineering, vol. 16, no. 026021, 2019. (JCR Q1, 长文，IF:4.551)

12. F. Wang, Y. He, J. Pan, Q. Xie, R. Yu, R. Zhang, Y. Li, “A Novel Audiovisual Brain-Computer Interface and Its Application in Awareness Detection,” Scientific Reports, 2015. (JCR Q1, 长文，IF:5.578)

13. J. Long, X. Huang, Y. Liao, X. Hu, J. Hu, S. Lui, R. Zhang, Y. Li, Q. Gong, “Prediction of post- earthquake depressive and anxiety symptoms: a longitudinal resting-state fMRI study,” Scientific Reports, 2014 (4). (JCR Q1, 长文，IF:5.578)

获奖：

1、2024年 吴文俊人工智能科学技术奖 技术发明奖 一等奖

2、2023年 中国自动化学会技术发明奖 一等奖

3、2018年 中国图象图形学学会优秀博士学位论文 提名奖