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Yingchun Zhang, PhD

Assistant Affiliate Member, Research Institute
Houston Methodist


Biography

Dr. Zhang earned his Ph.D. in Electrical Engineering from Zhejiang University, China in 2004. He held a faculty appointment at the University of Minnesota, Minneapolis before joining the faculty of the University of Houston in 2012 and becoming an assistant affiliate member of Houston Methodist Research Institute in 2014. Dr. Zhang is currently an Assistant Professor in the Department of Biomedical Engineering at the University of Houston. He directs a predictive modeling and functional imaging research program focusing on clinical diagnosis technology of urogenital dysfunction and other disorders in the human body through the fusion of functional bioelectrical activity/impedance imaging, electrical stimulation and recording, advanced computational modeling and electrophysiological/biomechanical analysis. Dr. Zhang is a recipient of NIH Pathway to Independence (K99/R00) award, an IEEE senior member and serves as a reviewer for a number of peer-review scientific journals.

Description of Research

Dr. Zhang’s Predictive Modeling and Functional Imaging Lab is interested in advancing clinical diagnosis of dysfunction in the human body through the fusion of functional bioelectrical activity/property imaging, neuromodulation, advanced computational modeling and electrophysiological/biomechanical analysis with applications in investigating the mechanisms of bioelectrical activities and neural pathways in biological systems. His lab is also interested in utilizing developed functional imaging technologies to enhance human-machine-interface systems such as brain-computer-interface systems, brain-controlled devices and myoelectrically-controlled prostheses. The research in his lab involves both technology developments and experimental studies in human subjects and animals.

Areas Of Expertise

Multimodal neural imaging Predictive modeling Incontinence Rehabilitation Prostate cancer early detection
Education & Training

MS, Harbin Institute of Technology
Postdoctoral Fellowship, University of Minnesota
PhD, Zhejiang University
Publications

Single-trial EEG emotion recognition using Granger Causality/Transfer Entropy analysis
Gao, Y, Wang, X, Potter, T, Zhang, J & Zhang, Y 2020, , Journal of Neuroscience Methods, vol. 346, 108904. https://doi.org/10.1016/j.jneumeth.2020.108904

Dynamic reorganization of the cortical functional brain network in affective processing and cognitive reappraisal
Fang, F, Potter, T, Nguyen, T & Zhang, Y 2020, , International Journal of Neural Systems, vol. 30, no. 10, 2050051. https://doi.org/10.1142/S0129065720500513

Enhancing fNIRS Analysis Using EEG Rhythmic Signatures: An EEG-Informed fNIRS Analysis Study
Li, R, Zhao, C, Wang, C, Wang, J & Zhang, Y 2020, , IEEE Transactions on Biomedical Engineering, vol. 67, no. 10, 8985187, pp. 2789-2797. https://doi.org/10.1109/TBME.2020.2971679

Multi-class motor imagery EEG classification using collaborative representation-based semi-supervised extreme learning machine
She, Q, Zou, J, Luo, Z, Nguyen, T, Li, R & Zhang, Y 2020, , Medical and Biological Engineering and Computing, vol. 58, no. 9, pp. 2119-2130. https://doi.org/10.1007/s11517-020-02227-4

Voiding dysfunction in old male rats associated with enlarged prostate and irregular afferent-triggered reflex responses
Zhang, C, Li, X, Boone, TB, Cruz, Y, Zhang, Y & Munoz, A 2020, , International Neurourology Journal, vol. 24, no. 3, pp. 258-269. https://doi.org/10.5213/inj.2040114.057

The effects of botulinum toxin injections on spasticity and motor performance in chronic stroke with spastic hemiplegia
Chen, YT, Zhang, C, Liu, Y, Magat, E, Verduzco-Gutierrez, M, Francisco, GE, Zhou, P, Zhang, Y & Li, S 2020, , Toxins, vol. 12, no. 8, 492. https://doi.org/10.3390/toxins12080492

Altered Muscle Networks in Post-Stroke Survivors
Houston, M, Li, R, Roh, J & Zhang, Y 2020, . in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020., 9176646, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc. pp. 3771-3774, 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canada, 7/20/20. https://doi.org/10.1109/EMBC44109.2020.9176646

Driving drowsiness detection with EEG using a modified hierarchical extreme learning machine algorithm with particle swarm optimization: A pilot study
Ma, Y, Zhang, S, Qi, D, Luo, Z, Li, R, Potter, T & Zhang, Y 2020, , Electronics (Switzerland), vol. 9, no. 5, 775. https://doi.org/10.3390/electronics9050775

An EEG-fNIRS hybridization technique in the four-class classification of alzheimer's disease
Cicalese, PA, Li, R, Ahmadi, MB, Wang, C, Francis, JT, Selvaraj, S, Schulz, PE & Zhang, Y 2020, , Journal of Neuroscience Methods, vol. 336, 108618. https://doi.org/10.1016/j.jneumeth.2020.108618

A Preliminary Study of Effects of Channel Number and Location on the Repeatability of Motor Unit Number Index (MUNIX)
Gao, F, Cao, Y, Zhang, C & Zhang, Y 2020, Frontiers in Neurology, vol. 11, 191. https://doi.org/10.3389/fneur.2020.00191

Development of Brain Structural Networks Over Age 8: A Preliminary Study Based on Diffusion Weighted Imaging
Wu, Z, Peng, Y, Selvaraj, S, Schulz, PE & Zhang, Y 2020, , Frontiers in Aging Neuroscience, vol. 12, 61. https://doi.org/10.3389/fnagi.2020.00061

Global Innervation Zone Identification with High-Density Surface Electromyography
Zhang, C, Dias, N, He, J, Zhou, P, Li, S & Zhang, Y 2020, , IEEE Transactions on Biomedical Engineering, vol. 67, no. 3, 8726155, pp. 718-725. https://doi.org/10.1109/TBME.2019.2919906

Transcutaneous innervation zone imaging from high-density surface electromyography recordings
Liu, Y, Zhang, C, Dias, N, Chen, YT, Li, S, Zhou, P & Zhang, Y 2020, , Journal of neural engineering, vol. 17, no. 1, 016070. https://doi.org/10.1088/1741-2552/ab673e

Establishing functional brain networks using a nonlinear partial directed coherence method to predict epileptic seizures
Zhang, Q, Hu, Y, Potter, T, Li, R, Quach, M & Zhang, Y 2020, , Journal of Neuroscience Methods, vol. 329, 108447. https://doi.org/10.1016/j.jneumeth.2019.108447

Deep convolutional neural network-based epileptic electroencephalogram (EEG) signal classification
Gao, Y, Gao, B, Chen, Q, Liu, J & Zhang, Y 2020, , Frontiers in Neurology, vol. 11, 375. https://doi.org/10.3389/fneur.2020.00375

Double-Criteria Active Learning for Multiclass Brain-Computer Interfaces
She, Q, Chen, K, Luo, Z, Nguyen, T, Potter, T & Zhang, Y 2020, , Computational Intelligence and Neuroscience, vol. 2020, 3287589. https://doi.org/10.1155/2020/3287589

Functional Network Alterations in Patients with Amnestic Mild Cognitive Impairment Characterized Using Functional Near-Infrared Spectroscopy
Li, R, Rui, G, Zhao, C, Wang, C, Fang, F & Zhang, Y 2020, , IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 1, 8922610, pp. 123-132. https://doi.org/10.1109/TNSRE.2019.2956464

The influence of common component on myoelectric pattern recognition
Yao, B, Peng, Y, Zhang, X, Zhang, Y, Zhou, P & Pu, J 2020, , Journal of International Medical Research, vol. 48, no. 3. https://doi.org/10.1177/0300060520903617

High-density surface electromyographic assessment of pelvic floor hypertonicity in IC/BPS patients: a pilot study
Dias, N, Zhang, C, Smith, CP, Lai, HH & Zhang, Y 2020, , International Urogynecology Journal. https://doi.org/10.1007/s00192-020-04467-2

Improve computational efficiency and estimation accuracy of multi-channel surface EMG decomposition via dimensionality reduction
Ning, Y, Dias, N, Li, X, Jie, J, Li, J & Zhang, Y 2019, , Computers in Biology and Medicine, vol. 112, 103372. https://doi.org/10.1016/j.compbiomed.2019.103372