►主要工作经历
2022.01至今 中国科学院宁波材料技术与工程研究所 生物医学工程研究所 “关键人才”高级工程师
2017.12-2021.12 上海交通大学机械与动力工程学院 机器人研究所 博士后/助理研究员
►科研项目
[1] 国家重点研发计划政府间国际合作重点项目，2025YFE0101504，面向光伏面板制造场景的人形机器人关键技术研究，2025/09-2028/09， 200万元，在研，子课题负责人
[2] 浙江省重点研发计划（“尖兵”“领雁”研发攻关计划），2023C03160, 先进康复诊疗设备研发-智能化神经康复系统关键技术研究与应用, 2023-01 至 2025-12, 120万元, 在研, 主持
[3] 宁波甬江人才工程-青年创新人才项目，基于电触觉反馈的智能神经假肢感知功能重建技术研究，2022A-194-G，2023-01至2027-12，100万，在研，主持
[4] 宁波市重点研发计划暨“揭榜挂帅”项目，2023Z202，经口腔入路的人机协作型智能手术机器人系统研发，2024/08-2026/08，180万元，在研，材料所负责人
[5] 中国博士后科学基金会, 博士后特别资助项目（站中）, 2020T130409, 基于电触觉反馈的神经假肢感知功能重建技术研究, 2020-05 至 2022-05, 18万元, 结题, 主持
[6] 中国博士后科学基金会, 面上项目, 2019M651504, 基于电刺激编码反馈的神经假肢感知功能重建技术研究, 2019-01 至 2020-12, 8万元, 结题, 主持
[7] 国家自然科学基金委员会, 面上项目, 52175023, 基于混合式无创脑机接口的多自由度连续运动意图解码及应用研究, 2022-01-01 至 2025-12-31, 58万元, 结题, 参与
[8] 国家自然科学基金委员会, 青年科学基金项目, 51805320, 用于神经假肢双向交互的机/电刺激编码与感知反馈通道重建研究, 2019-01-01 至 2021-12-31, 25万元, 结题, 主持
[9] 国家自然科学基金共融机器人重大研究计划集成项目“面向肢体运动功能重建的生机电一体化机器人技术”，91948302，2020/01-2024/12，1300万，结题，参与
[10] 上海市基础研究重大项目“神经信号测量、解码与神经交互基础研究”， 18JC1410400， 2018/06-2021/05，991.5万，结题，参与
[11] 国家自然科学基金重点国际合作项目“类生物体灵巧假肢及双向生机接口”， 51620105002， 2017/01-2021/12，243万，结题，参与
[12] 国家973计划项目“人体运动功能重建的生机电一体化科学基础”， 2011CB013300， 2011/11-2016/08，3333万元，结题，参与
►科研项担任权威国际期刊和会议审稿人
IEEE Transactions Biomedical Engineering / IEEE Transactions on Neural Systems and Rehabilitation Engineering / IEEE Journal of Biomedical and Health Informatics / IEEE Transactions Neural Networks and Learning Systems / IEEE Transactions on Cybernetics / IEEE Transactions on Industrial Electronics / IEEE Transactions on Industrial Informatics / IEEE Transactions on Fuzzy Systems / IEEE Transactions on Human-Machine Systems / IEEE Sensors Journal / IEEE Access / IEEE SMC/EMBC/NER Conferences
Frontiers in Neuroscience / in Human Neuroscience / in Robotics and AI / in Virtual Reality / in Systems Neuroscience / in Artificial Intelligence / Aging Neuroscience
NeuroImage / Scientific Reports / iScience / Journal of NeuroEngineering and Rehabilitation / Plos One / Clinical Neurology and Neuroscience / Journal of Neural Engineering
►科研论文与专利
(Names with a “†” are equal contribution, with “*” are students under my co-supervision)
--------- Published or in press--------
Selected journal articles
[1] Feng, G†., Chai, G†*., Zhang, J*., Song, T., Shi, C., Xu, J., & Zuo, G. “Effective unilateral/bilateral robot-assisted training for upper limb motor function rehabilitation: a cross-sectional study”, Frontiers in Human Neuroscience, 2025, 19, 1571624.
[2] Lu, Y., Lin, Z., Li, Y., Lv, J., Zhang, J., Xiao, C., Liang, Y., Chen, X., Song, T., Chai, G*., & Zuo, G*. “A greedy assist-as-needed controller for end-effect upper limb rehabilitation robot based on 3-DOF potential field constraints”, Frontiers in Robotics and AI, 2024, 11, 1404814.
[3] Fang, Y., Guo, W., Chai, G., & Sheng, X. “A lightweight haptic interface for hand-to-object tasks with spatiotemporal displays”, IEEE Transactions on Industrial Electronics, 2024, 71(12), 16255-16263.
[4] Lin, Zixuan, Haowei Zheng, Yue Lu, Jiaji Zhang, Guohong Chai*, and Guokun Zuo*. "Object surface roughness/texture recognition using machine vision enables for human-machine haptic interaction." Frontiers in Computer Science, 2024, 6: 1401560.
[5] Su, S., Chai, G., Xu, W., Meng, J., Sheng, X., Mouraux, A., & Zhu, X. “Neural evidence for functional roles of tactile and visual feedback in the application of myoelectric prosthesis”, Journal of neural engineering, 2023, 20(1), 016038.
[6] Wang, X., Zhang, F., Shi, C., Jiang, W., Wang, K., Wu, C., Chen, H., Wu, J., Chai, G., Shen, Q., Tao, L., Gong, S., Xu, J., Tang, M. & Zuo, G. A Modified Method of Wearable Gait Analysis for Stroke Patients Based on the Peak Width Threshold and Phase Re-Segmentation. IEEE Sensors Journal, 2024.
[7] Chai G.H., Wang H., Li G.Y., Sheng X.J. and Zhu X.Y., "Electrotactile feedback improves grip force control and enables object stiffness recognition while using a myoelectric hand", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 30, p. 1310-1320, 2022 (JCRQ2, IF: 4.528)
[8] Xu, H., Chai, G., Zhang, N., & Gu, G. “Restoring finger-specific tactile sensations with a sensory soft neuroprosthetic hand through electrotactile stimulation”, Soft Science, 2022, 2(4).
[9] Su, S., Chai, G., Meng, J., Sheng, X., Mouraux, A., & Zhu, X. “Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control”, Journal of neural engineering, 2022, 19(1), 016028.
[10] Li G.Y., Jiang S.Z., M J.J., Chai G.H., Fan Z., Hu J., Sheng X.J., Zhang D.G., Chen L., and Zhu X.Y., "Assessing differential representation of hand movements in multiple domains using stereo-electroencephalographic recordings", NeuroImage, vol.250, p. 118969, 2022.
[11] Gu G.Y., Zhang N.B., Xu H.P., Lin S.T., Yu Y., Chai G.H., Ge L. S., Sheng X.J., Zhu X.Y. and Zhao X.H. “A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback”, Nature biomedical engineering, 2021: 1-10.
[12] Li G.Y., Jiang S.Z., Paraskevopoulou S.E., Chai G. H., Wei Z.X., Liu S.J., Wang M., Xu Y., Fan Z., Wu Z. H., Chen L., Zhang D.G., Zhu X.Y., “Detection of human white matter activation and evaluation of its function in movement decoding using stereo-electroencephalography (SEEG)”, Journal of Neural Engineering, 2021, 18(4): 0460c6.
[13] Lv B., Chai G.H., Sheng X.J. and Zhu X.Y., “Evaluating user and machine learning in short- and long-term pattern recognition-based myoelectric control”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, 29, 777-785.
[14] Ye H.P., Fan Z., Chai G.H., Li G.Y., Wei Z. X., Hu J., Sheng X.J., Chen L. and Zhu X.Y., “Self-related stimuli decoding with auditory and visual modalities using stereo-electroencephalography”, Frontiers in Neuroscience, 2021, 15, 653965.
[15] Su S.Y., Chai G.H., Sheng X.J. Meng J.J. and Zhu X.Y., “Contra-lateral desynchronized alpha oscillations linearly correlate with discrimination performance of tactile acuity”, Journal of Neural Engineering, 2020, 17(4): 046041.
[16] Su S.Y., Chai G.H., Shu X.K., Sheng X.J. and Zhu X.Y., “Electrical stimulation-induced SSSEP as an objective index to evaluate the difference of tactile acuity between the left and right hand”, Journal of Neural Engineering, 2020, 17(1): 016053.
[17] Chen C., Chai G.H., Guo W.C., Sheng X.J., and Zhu X.Y., “Prediction of finger kinematics based on discharge timings of motor units: implications for intuitive control of myoelectric prosthesis”, Journal of Neural Engineering, 2019, 16: 026005.
[18] Chai G.H., Zhang D.G. and Zhu X.Y., “Developing non-somatotopic phantom finger sensation to comparable levels of somatotopic sensation through user training with electrotactile stimulation”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016, 25(5):469-480.
[19] Chai G.H., Sui X.H., Li S., He L.W. and Lan N., “Characterization of evoked tactile sensation in forearm amputees with transcutaneous electrical nerve stimulation”. Journal of Neural Engineering, 2015, 12(6): 066002.
[20] Chai G.H., Sui X.H., Li P., Liu X.X. and Lan N., “Review on tactile sensory feedback of prosthetic hands for the upper-limb amputees by sensory afferent stimulation”, J. Shanghai Jiaotong Univ. (Sci.), 2014, 19(5): 1-5.
Selected conference articles
[1] Guang Feng, Jiaji Zhang*, Guohong Chai*, Maoqin Li, Guokun Zuo, and Lei Yang. An Effective Training Strategy for Upper-limb Rehabilitation Ro-bots Based on Visual-hHaptic Feedback Using Potential Field. IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2022.
[2] Wang H., Chai G., Sheng X. and Zhu X. “A programmable, multichannel, miniature stimulator for
electrotactile feedback of neural hand prostheses”, 10th International IEEE/EMBS Conference on Neural Engineering (NER).. IEEE, 2021, 1026-1029.
[3] Chai G, Josselin B., Su S., Sheng X. and Zhu X. “Electrotactile feedback with spatial and mixed coding for object identification and closed-loop control of grasping force in myoelectric prostheses”, 41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2019: 1805-1808. (EI)
[4] Su S., Chai G, Sheng X and Zhu X. “Electrical stimulation-induced SSSEP as an objective index for the evaluation of sensory ability”, 9th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2019: 908-911. (EI)
[5] Chen C., Yu Y., Chai G, Sheng X and Zhu X. “Estimating the single-DoF kinematics of wrist from motor unit behaviors”, 9th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2019: 469-472. (EI)
[6] Chai G, Zhang D, Sheng X., and Zhu X. “Evaluation of human proprioceptive matching ability in discrete grasping motions: implications for the sensory reconstruction of prosthetic hand”, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2018: 2394-2399. (SCI收录)
[7] Shu X, Chen S, Chai G, et al. Neural modulation by repetitive transcranial magnetic stimulation (rtms) for bci enhancement in stroke patients, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018: 2272-2275. (EI)
[8] Chai G.H., Li S., Sui X. H., Mei Z., He L. W., Zhong C. L., Wang J.W., Zhang D.G., Zhu X.Y., Lan, N., “Phantom finger perception evoked with transcutaneous electrical stimulation for sensory feedback of prosthetic hand”, 6th International IEEE/EMBS Conference on Neural Engineering (NER). San Diego, USA, 2013: 271-274. (EI)
[9] Liu X.X., Chai G.H., Qu H.E., Lan, N., “A sensory feedback system for prosthetic hand based on evoked tactile sensation”, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milano, Italy, 2015: 2493-2496. (EI)
[10] Li P., Chai G.H., Lan N., Sui X.H., “Effects of electrode size and spacing on sensory modalities in the phantom thumb perception area for the forearm amputees”, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milano, Italy, 2015: 3383-3386. (EI)
[11] Zhu K. H., Li P., Chai G.H., Lan N., Sui X.H., “Effects of stratum corneum and conductive gel properties on sensory afferents recruitment by 3D TENS computational modeling”, 7th International IEEE/EMBS Conference on Neural Engineering (NER), Montpellier, France, 2015: 506-509. (EI)
[12] Wang T., Li S., Chai G.H., Lan N., “Perceptual attributes of cutaneous electrical stimulation to provide sensory information for prosthetic limb”, Third International Conference on Information Science and Technology, Yangzhou,China, 2013, 978:22-25, (EI)
[13] Li S., Chai G.H., Sui X.H., Lan N., “Finite element modeling of cutaneous electrical stimulation for sensory feedback”, Chinese Journal of Biomedical Engineering, 2014, 23(4): 146-152.
代表性专利：
[1]柴国鸿，林子轩，左国坤，张佳楫，一种基于触觉反馈的表面特征识别方法、装置及系统，中国发明专利，202211603381.3. 公开实审
[2]柴国鸿，林子轩，左国坤，张佳楫，一种基于触觉反馈的双向人机交互控制系统，中国发明专利，202211603179.0 公开实审
[3]柴国鸿，宋涛，左国坤，张佳楫，一种手部外骨骼控制方法、装置及系统，中国发明专利，202310959968.6 公开实审
[4]柴国鸿，周慧琳，左国坤，张佳楫，一种基于脑电的反馈交互评估系统、方法及装置，中国发明专利，202310959968.6 公开实审
[5]柴国鸿，张佳楫，左国坤，一种融合多反馈信息的交互训练控制系统及方法，中国发明专利，202311763851.7 公开实审
[6]柴国鸿，张佳楫，左国坤，基于Unity的便携式虚拟现实康复训练系统通讯与控制软件，软件著作权，登记号：2024SR1335759 授权
[7]柴国鸿，林子轩，张佳楫，左国坤，视-触-力觉融合反馈的上肢康复训练与运动学习软件，软件著作权，登记号：2024SR1334512 授权
[8]柴国鸿，林子轩，张佳楫，左国坤，视-触-力觉融合反馈的人机感知交互力控制软件，软件著作权，登记号：2024SR1335794 授权
[9]柴国鸿，林子轩，张佳楫，左国坤，基于机器视觉的物体表面粗糙度、纹理特征识别软件，软件著作权，登记号：2023SR0878062 授权
[10]左国坤，郑皓蔚，柴国鸿，宋涛，张佳楫. 用于手部康复训练系统操作的图形用户界面，中国发明专利， ZL 2024 3 0574326.X. 授权
[11]金康，柴国鸿，张佳楫，左国坤，刘安东. 一种复健评估方法、装置、电子设备及存储介质，中国发明专利，202511921417.6. 受理
[12]朱吉富，柴国鸿，潘清，左国坤，一种脑电信号分析系统、方法、电子设备及存储介质，中国发明专利，202511962529.6 受理