师资

张明明
助理教授
神经康复机器人实验室负责人
+86-755-88015285
zhangmm@sustech.edu.cn

个人简介

张明明,南方科技大学生物医学工程系助理教授,博士生导师,IEEE/ASME Member,主要研究方向包括柔性驱动,智能控制与人机交互,可穿戴外骨骼康复机器人,以及基于肌电/脑电的智能识别算法等。2012-2016年就读于新西兰奥克兰大学并获得工学博士学位,2015-2016年继续在奥克兰大学生物机电一体化实验室从事博士后研究,2017-2018年任奥克兰CASTIOT LIMITED副总裁,负责康复机器人研究开发,同时受聘为奥克兰大学访问研究员。多年来致力于研究康复机器人的鲁棒性和智能性控制问题及临床应用,以及基于实时计算模型的生物力学评估技术,特别在柔性可穿戴设备及临床应用方面取得了重要成果。科研成果多次发表在机器人、智能控制、神经康复、及生物力学等领域的国际知名杂志上,包括IEEE Transactions on Industrial Electronics,IEEE Transactions on Biomedical Engineering,Journal of NeuroEngineering and Rehabilitation,Journal of Biomechanics等共计30余篇,已申请/授权专利25项,出版英文专著1本。

 

教育背景

2012年-2016年,博士,机械工程,奥克兰大学(新西兰)

2009年-2011年,硕士,机械电子,重庆大学

2005年-2009年,学士,机械工程,河南科技大学

 

工作经历

2018年8月-至今,助理教授, 南方科技大学生物医学工程系

2017年-2018年,访问研究员,奥克兰大学(新西兰)

2017年-2018年,副总裁, CASTIOT LIMITED (新西兰奥克兰)

2015年-2016年,博士后研究员,奥克兰大学(新西兰)

 

荣誉与奖励

1. IEEE/ASME Member

2. Lead Guest Editor, Advances in Mechanical Engineering (SCI Journal)

3. Associate Editor,2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (Auckland), 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (Hong Kong)

4. Invited Reviewer for IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Neural System and Rehabilitation Engineering, Journal of NeuroEngineering and Rehabilitation, IEEE Transactions on Biomedical Engineering, etc

 

代表性论文

1. Q. Miao, M. Zhang*, J. Cao, S. Q. Xie, "Reviewing High-Level Control Techniques on Robot-Assisted Upper-Limb Rehabilitation", Advanced Robotics, 2018. 32 (24): 1253-1268.

2. Q. Miao, A. McDaid, M. Zhang*, P. Kebria, H. Li, “A Three-Stage Trajectory Determination Method of Bilateral Upper Limb Training Using Interference Analysis”, Robotics and Autonomous Systems, 2018. 105: p. 38-46.

3. M. Zhang*, S. Zhang, A. McDaid, C. Davies, Sheng Q. Xie, “Automated Objective Robot-Assisted Assessment of Wrist Passive Ranges of Motion”, Journal of Biomechanics, 2018. 73: p. 223–226.

4. Q. Miao, M. Zhang*, C. Wang, H. Li, “Towards Optimal Robot Design for Ankle Rehabilitation: The State of Art and Future Prospects”, Journal of Healthcare Engineering, 2018.

5. M. Zhang, S. Xie, X. Li, G. Zhu, W. Meng, X. Huang, A. Veale, “Adaptive Patient-Cooperative Control of a Compliant Ankle Rehabilitation Robot (CARR) with Enhanced Training Safety”, IEEE Transactions on Industrial Electronics, 2017. 65(2): p. 1398 – 1407.

6. M. Zhang, J. Cao, G. Zhu, Q. Miao, X. Zeng, S. Xie, “Reconfigurable Workspace and Torque Capacity of a Compliant Ankle Rehabilitation Robot (CARR)”, Robotics and Autonomous Systems, 2017. 98: p. 213-221.

7. M. Zhang, J. Cao, S. Xie, G. Zhu, X. Zeng, X. Huang, Q. Xu, “A Preliminary Study on Robot-Assisted Ankle Rehabilitation for the Treatment of Drop Foot”, Journal of Intelligent & Robotic Systems, 2017.

8. Q. Miao, M. Zhang*, S. Xie, “Design and Interaction Control of a New Bilateral Upper Limb Rehabilitation Device (BULReD)”, Journal of Healthcare Engineering, 2017.

9. M. Zhang, T.C. Davies, Y Zhang, and S. Xie, “A Robot-Driven Computational Model Based Ankle Assessment Technique with Subject-Specific Adaptation”, IEEE Transactions on Biomedical Engineering, 2016. 63(4): p. 814-21.

10. M. Zhang, T.C. Davies, Y. Zhang, and S. Xie, “A Real-Time Computational Model for Estimating Kinematics of Ankle Ligaments”, Computer Methods in Biomechanics and Biomedical Engineering, 2016. 19(8): p. 835-44.

11. M. Zhang, T.C. Davies, A. Nandakumar, and S. Xie, “A Novel Assessment Technique for Measuring Ankle Orientation and Stiffness”, Journal of Biomechanics, 2015, 48(12): p. 3527-9.

12. M. Zhang, T.C. Davies, Y. Zhang, and S. Xie, Zhang, M., et al., Reviewing effectiveness of ankle assessment techniques for use in robot-assisted therapy. Journal of Rehabilitation Research & Development, 2014. 51(4), p. 517-34.

13. M. Zhang, et al., “An Assistance-as-Needed Control Paradigm for Robot-Assisted Ankle Rehabilitation”, Rehabilitation Process and Outcome, 2014: p. 15-17.

14. M. Zhang*, T.C. Davies, and S. Xie, Effectiveness of Robot-Assisted Therapy on Ankle Rehabilitation — A Systematic Review. Journal of NeuroEngineering and Rehabilitation, 2013. 10(1): p. 30.

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