张智钧教授 - 生物醫學學院

张智钧教授

副教授

39439389

vckc@cuhk.edu.hk

https://scholar.google.com.hk/citations?user=0jvjVzQAAAAJ&hl=en

https://youtu.be/xAHPVTlQ4N0?t=1216

Room 322A, Lo Kwee-Seong Integrated Biomedical Sciences Building, Area 39, CUHK

Publons

ORCID

个人简介

Biography

Prof. CHEUNG Chi Kwan Vincent (張智鈞) A neuroscientist and biomedical engineer, Vincent C. K. Cheung is Associate Professor at the School of Biomedical Sciences of The Chinese University of Hong Kong (CUHK). He obtained his B. Sc. in Mathematics and Pharmacology & Therapeutics from The University of British Columbia, Ph. D. in Neuroscience and Biomedical Engineering from MIT and Harvard Medical School, and postdoctoral training from the McGovern Institute for Brain Research at MIT. Prof. Cheung’s research focuses on understanding how the central nervous system controls voluntary movement and enables motor skill learning. He is interested in translating knowledge of movement control into new rehabilitation strategies for movement disorders. To address these questions, Prof. Cheung and his team collect neurophysiological and motion data from humans and animals, explore the use of novel neural technologies, and analyse complex data sets using machine learning and AI techniques. Prof. Cheung’s research has been supported by the Hong Kong Research Grants Council, the CUHK Medicine Faculty Innovation Award, and other sponsors. His articles have appeared in Nature Communications, PNAS, Journal of Neurophysiology, and multiple IEEE journals. He was invited to speak for professional conferences, events for the general audience (e.g., TEDxCUHK), and various local radio programmes. Prof. Cheung was the Chair of the Hong Kong-Macau Chapter of the IEEE Engineering in Medicine and Biology Society (2018-19). Recipient of the Angus MacDonald Teaching Award of MIT (2006) and Teachers of the Years Award of CUHK Medicine (2021, 2022), Prof. Cheung has directed courses in neuroscience, human anatomy, and human physiology at CUHK. At present, he is the Dean of Students of CUHK’s C. W. Chu College.

研究兴趣

Neural control of movement
Motor learning, motor development, post-injury recovery
Neuro-rehabilitation
Movement disorders
Novel neural technologies
Neuroinformatics and algorithms for neural data analysis
Biomechanics
Brain stimulation and brain mapping

著作选录

Guo X, Huang S, He B, Lan C, Xie JJ, Lau KYS, Takei T, Mak ADP, Cheung RTH, Seki K, Cheung, V.C.K.*, Chan RHM* (2025) Inhibitory components in muscle synergies factorized by the rectified latent variable model from electromyographic data. IEEE Journal of Biomedical and Health Informatics, in press. DOI: 10.1109/JBHI.2024.3453603.
Huang S, Xie JJ, Lau KY, Liu R, Mak ADP*, Cheung, V.C.K.*, Chan RHM* (2024) Concerto of movement: how expertise shapes the synergistic control of upper limb muscles in complex motor tasks with varying tempo and dynamics. Journal of Neural Engineering, 21(4): 046010.
Cheung, V.C.K.*, Ha SC, Zhang-Lea JH, Chan ZY, Teng Y, Yeung G, Wu L*, Liang D, Cheung RTH* (2024) Motor patterns of patients with spinal muscular atrophy suggestive of sensory and corticospinal contributions to the development of locomotor muscle synergies. Journal of Neurophysiology, 131(2): 338-59.
Cheung, V.C.K.*, Seki, K.* (2021). Approaches to revealing the neural basis of muscle synergies: A review and a critique. Journal of Neurophysiology, 125: 1580-1597. [Invited in-depth review for acknowledging the career of Emilio Bizzi, Institute Professor Emeritus of MIT]
Cheung, V.C.K.*, Cheung, B.M.F., Zhang, J.H., Chan, Z.Y.S., Ha, S.C.W., Chen, C-Y., & Cheung, R.T.H.* (2020). Plasticity of muscle synergies through fractionation and merging during development and training of human runners. Nature Communications, 11: 4356.
Rinaldi, L., Yeung, L-F., Lam, P.C.H., Pang, M.Y.C., Tong, R.K.Y., & Cheung, V.C.K.* (2020). Adapting to the mechanical properties and active force of an exoskeleton by altering muscle synergies in chronic stroke survivors. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(10): 2203-2213.
Cheung, V.C.K.*, Zheng X-C., Cheung R.T.H., & Chan R.H.M. (2020). Modulating the structure of motor variability for skill learning through specific muscle synergies in elderlies and young adults. IEEE Open Journal of Engineering in Medicine and Biology, 1: 33-40.
Cheung, V.C.K., Niu, C.M., Li, S., Xie, Q., & Lan, N.* (2019). A Novel FES Strategy for Poststroke Rehabilitation Based on the Natural Organization of Neuromuscular Control. IEEE Reviews in Biomedical Engineering, 12, 154-167.
Devarajan, K.*, Cheung, V.C.K.* (2014). On non-negative matrix factorization algorithms for signal-dependent noise, with application to electromyography data. Neural Computation, 26, 1128-1168.
Bizzi, E.*, Cheung, V.C.K.* (2013). The neural origin of muscle synergies. Frontiers in Computational Neuroscience, 7, 51.
Cheung, V.C.K., Turolla, A., Agostini, M., Silvoni, S., Bennis, C., Kasi, P., Paganoni, S., Bonato, P., & Bizzi, E.* (2012). Muscle synergy patterns as physiological markers of motor cortical damage. Proceedings of the National Academy of Sciences, USA, 109(36), 14652-14656. [Recommended by Faculty of 1000]
Cheung, V.C.K., Piron, L., Agostini, M., Silvoni, S., Turolla, A., & Bizzi, E.*(2009). Stability of muscle synergies for voluntary actions after cortical stroke in humans. Proceedings of the National Academy of Sciences, USA, 106(46), 19563-19568.
Cheung, V.C.K.*, d’Avella, A., & Bizzi, E. (2009). Adjustments of motor pattern for load compensation via modulated activations of muscle synergies during natural behaviors. Journal of Neurophysiology, 101, 1235-1257.
Tresch, M.C.*, Cheung, V.C.K., d’Avella, A. (2006). Matrix factorization algorithms for the identification of muscle synergies: evaluation on simulated and experimental data sets. Journal of Neurophysiology, 95, 2199-2212.
Cheung V.C.K., d’Avella A*, Tresch MC, Bizzi E (2005) Central and sensory contributions to the activation and organization of muscle synergies during natural motor behaviors. Journal of Neuroscience 25(27): 6419-6434.

研究资助

RGC – Strategic Topics Grant [PC; 01-Jan-25]: “Personalized Rehabilitation Pathways to Maximal Motor Functional Return through an AI Recovery Prediction System for Diverse Stroke Survivors”.
RGC – General Research Fund [PI; 01-Jan-23]: “Neural basis of locomotor muscle synergies revealed by spinal population activity within neural manifolds”.
NSFC-RGC Joint Research Scheme [PI; 01-Jan-22]: “Decoding Diverse Motor Intentions from Macro and Micro Features of High-Density Electromyographic Signals for Naturalistic Control of Neural Prostheses”.
RGC – General Research Fund [PI; 01-Nov-21]: “Revealing the Neural Basis of Muscle Synergies in Humans through Direct Cortical Stimulation during Awake Brain Surgery”.
Croucher Summer Courses[PI; 01-Feb-19]: “Introduction to Computational Neuroscience”.
RGC – Research Impact Fund[PI; 28-Jan-19]: “A Wearable for Post-stroke Rehabilitative Multi-muscle Stimulation Inspired by the Natural Organization of Neuromuscular Control”.