研究方向包括开展神经康复工程领域的各类广泛性课题。具体研究兴趣包括智能肌电控制、基于电生理的多模态人机交互，神经肌肉控制机理和相关疾病病理，神经肌肉系统疾病的诊断、评估和治疗，先进康复辅助器械开发等。

先后参与多项国家863计划项目、国家自然科学基金项目（青年科学基金项目）【基于模式识别的肌电控制用于脑卒中上肢康复的研究（61401421）】、校级创新团队项目【肌电控制用于中风偏瘫上肢康复若干关键问题研究（WK2100230014）】和企业合作项目。发表SCI、EI收录科研论文20余篇。

• 2005 中国科学技术大学，学士，电子信息科学与技术
• 2010 中国科学技术大学，博士，生物医学工程
• 2010-2013 美国芝加哥康复学院，博士后
• 2013-至今 中国科学技术大学电子科学与技术系，副教授

• Tao W, Zhang X, Chen X, Wu D and Zhou P. Multi-scale complexity analysis of muscle coactivation during gait in children with cerebral palsy. Front. Hum. Neurosci., 9, 367 (13 pp.), 2015.
• Zhang X and Zhou P. Analysis of surface EMG baseline for detection of hidden muscle activity. J. Neural Eng., 11(1), 016011 (8 pp.), 2014.
• Zhang X, Barkhaus P, Rymer WZ and Zhou P. Machine learning for supporting diagnosis of amyotrophic lateral sclerosis using surface electromyogram. IEEE Trans. Neural Syst. Rehab. Eng., 22(1): 96-103, 2014.
• Zhang X, Li Y, Chen X, Li G, Rymer WZ and Zhou P. The effect of involuntary motor activity on myoelectric pattern recognition: a case study with chronic stroke patients. J. Neural Eng., 10(4), 046015 (11 pp.), 2013.
• Zhang X, Chen X, Barkhaus P and Zhou P. Multiscale Entropy Analysis of Different Spontaneous Motor Unit Discharge Patterns. IEEE J. Biomed. Health Inform., 17(2): 470‒476, 2013.
• Zhang X and Zhou P. Filtering of surface EMG using ensemble empirical mode decomposition. Med. Eng. Phys., 35(4): 537‒42, 2013.
• Zhang X and Zhou P. Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes. J. Electromyogr. Kinesiol., 22(6): 901‒907, 2012.
• Zhang X and Zhou P. High-density myoelectric pattern recognition toward improved stroke rehabilitation. IEEE Trans. Biomed. Eng., 59(6): 1649‒1657, 2012.
• Zhang X, Chen X, Li Y, Lantz V, Zhao Z, Wang K and Yang J. A framework for hand gesture recognition based on accelerometer and EMG sensors. IEEE Trans. Syst. Man Cybern. A Syst. Humans, 41(6): 1064‒1076, 2011.
• Lu Z, Chen X, Li Q, Zhang X and Zhou P. A hand gesture recognition framework and wearable gesture-based interaction prototype for mobile devices. IEEE Trans. Human-Machine Syst., 2014. DOI=10.1109/THMS.2014.2302794. (In Press)
• Li Y, Chen X, Zhang X, Zhou P. Several practical issues toward implementing myoelectric pattern recognition for stroke rehabilitation. Med. Eng. Phys., 2014. DOI= 10.1016/j.medengphy.2014.01.005. (In Press)
• P. Zhou, Zhang X. A novel technique for muscle onset detection using surface EMG signals without removal of ECG artifacts. Physiol. Meas., 35(1): 45‒54, 2014.
• Wang Q, Chen X, Chen R, Chen Y and Zhang X. Electromyography-based locomotion pattern recognition and personal positioning toward improved context-awareness applications. IEEE Trans. Syst. Man Cybern. Syst., 43(5): 1216‒1227, 2013.
• Li Y, Chen X, Zhang X, Wang K and Wang JZ. A sign-component-based framework for Chinese sign language recognition using accelerometer and sEMG data. IEEE Trans. Biomed. Eng., 59(10): 2695‒2704. 2012.
• Zhou P, Barkhaus PE, Zhang X, Rymer WZ. Characterizing the complexity of spontaneous motor unit patterns of amyotrophic lateral sclerosis using approximate entropy. J. Neural Eng., 8(6), 066010 (10 pp.), 2011.