康复机器人、可穿戴技术、步态分析与康复

1.海外博士后引才专项，120万，主持，2025.01-2027.12
2.泰山学者青年专家项目，NO.tsqn202408040，75万，主持，2025.01-2027.12
3. 山东省优秀青年科学基金项目（海外）, 2024HWYQ-019, 多源异构融合的人机共融步态分析与康复一体化研究，60万元，主持，2024.1-2026.12
4.国家自然科学基金青年科学基金，62403281，基于时序序列的直推式深度学习步态分析研究，30万元，主持，2025.1-2027.12
5.国家重点研发计划“智能机器人”重点专项子课题, 2023YFB4706102，多体位变换照护康复一体化支撑平台创成，15万元，主持，2023.12-2026.11

海外博士后引才专项入选者、山东省优海外优青、泰山学者青年专家
全国创新创业优秀博士后、美国斯蒂文斯卓越博士
山东省创新创业优秀博士（后），2024

1. Ti. Huang, Z. Huo, W. Wang, B. Li, M. Li, and H. Zhang. “Design and Evaluation of a Wearable Electrical Stimulation System for Cardiovascular Regulation During and After 400-m Sprinting,” IEEE Internet of Things Journal. 2026 May 15, 13(10), 22564–22573.
2. J. Wang, Z. Guan, T. Liang, Z. Ding, X. Ma, Y. Li, R. Song and H. Zhang. “Multi-task Learning for Gait Phase and Gait Cycle Percentage Prediction with Wearable Sensors in Frail Older Adults,” IEEE Journal of Biomedical and Health Informatics. 2025 Dec.
3. X. Li, H. Liu, A. Shangguan and H. Zhang. “How few channels suffice? A hierarchical validation framework for minimal-channel wearable sEMG in upper-limb rehabilitation gesture recognition,” Journal of NeuroEngineering and Rehabilitation. 2026 June.
4. Z. Guan, J. Cai, J. Wang, Y. Li, R. Song, D. Zanotto, S.K. Agrawal and H. Zhang. “Accuracy and precision of wearable-derived gait parameters: How these affect the performance of models for fall prediction in the elderly,” IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2025 Oct, 33, 4255-4266.
5. J. Cai, Z. Guan, J. Wang, Z. Ding, Y. Li, R. Song and H. Zhang. “Impact of gait parameters and their variability on fall risk assessment accuracy using wearable sensor,” IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2025 May, 33, 1996-2003.
6. H. Zhang, C. Wu, Y. Huang, R. Song, D. Zanotto and S.K. Agrawal. “Fall Risk Prediction Using Instrumented Footwear in Institutionalized Older Adults,” IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2024 Dec, 32, 4260-4269.
7.H. Zhang, T. Duong, A. Rao, P. Mazzoni, S. Agrawal, Y. Guo and D. Zanotto. “Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities,” IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2022 Jau, 30, 124-134.
8.H. Zhang, Y. Guo and D. Zanotto. “Accurate Ambulatory Gait Analysis in Walking and Running Using Machine Learning Models,” IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2020 Jau,28, 191- 202.
9. H. Zhang, S. Li, Q. Zhao, A. Rao, Y. Guo and D. Zanotto. “Reinforcement Learning-Based Adaptive Biofeedback Engine for Overground Walking Speed Training,” IEEE Robotics and Automation Letters, 2022 June, 7 (3), 8487-8494.
​10. H. Zhang, D. Zanotto and S.K. Agrawal. “Estimating CoP Trajectories and Kinematic Gait Parameters in Walking and Running Using Instrumented Insoles,” IEEE Robotics and Automation Letters. 2017 June, 2 (4), 2159-2165.

Clinical Neurology and Neuroscience, 编委
Biomedical Engineering and Biomechanics，编委
Healthcare and Rehabilitation，客座编辑（Lead）
Technologies，客座编辑
Healthcare and Rehabilitation，青年编委
Robot Learning，青年编委
Artificial Intelligence and Autonomous Systems，青年编委
中国康复医学会智能康复专委会，常务委员
中国自动化学会学生工作委员会，委员
山东生物医学工程学会医体融合专业委员会，委员