柴国鸿 博士，“关键人才”高级工程师
招生方向：
- 人机双向（神经）交互技术
- 生机电一体化智能系统与康复机器人
- 虚拟现实与多感觉融合神经调控技术
- 电触觉反馈与非侵入式脑电（EEG/fNIRS）评估技术
2017年博士毕业于上海交通大学，之后在上海交大机械与动力工程学院机器人研究所从事博士后研究工作，现就职于中科院宁波材料所-慈溪生物医学工程研究所（NIMTE）。近十年来一直从事生机电一体化系统与神经交互技术的科学与应用研究工作。研究领域涉及生机电一体化灵巧假肢、康复机器人系统、人机双向神经接口技术、电触觉反馈技术、虚拟现实技术及脑电/肌电信号处理等。先后在JNE, IEEE-TNSRE, NeuroImage, Nature biomedical engineering 等本领域权威国际学术期刊、国际主流学术会议发表SCI/EI论文二十余篇。主持/参与多项国家/省部级科技攻关项目。担任多个国际期刊客座编委及国际权威期刊/会议的审稿人。
►主要工作经历
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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 高级工程师
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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] 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
[2] 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
[3] 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
[4] 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
[5] 宁波市重点研发计划，经口腔入路的人机协作型智能手术机器人系统研发，2023-05 至 2026-04, 200万元, 在研, 参与
[6] 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, 在研, 参与
[7] 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
[8] 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，在研，参与
[9] 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
[10] 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
[11] 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
Journal of Neural Engineering
NeuroImage
IEEE Trans. Biomedical Engineering
IEEE Trans. Neural Sys. And Rehabilitation Engineering
IEEE Journal of Biomedical and Health Informatics
IEEE Trans. Neural Networks and Learning Systems
IEEE Transactions on Cybernetics
IEEE Trans. Fuzzy Systems
IEEE Transactions on Human-Machine Systems
IEEE Sensors Journal
IEEE SMC/EMBC/NER, et al. Conferences
IEEE Access
Scientific Reports
Frontiers in Neuroscience
Journal of Neuroengineering and Rehabilitation
Plos One
Clinical Neurology and Neuroscience
►科研成果
论文
1. Selected journal articles
[1] Chai G.H., Wang H., Li G.Y., Sheng X.J. & 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)
[2] Li G.Y., Jiang S.Z., M J.J., Chai G.H., Fan Z., Hu J., Sheng X.J., Zhang D.G., Chen L. & Zhu X.Y., "Assessing differential representation of hand movements in multiple domains using stereo-electroencephalographic recordings", NeuroImage, vol.250, p. 118969, 2022. （JCR Q1, IF: 6.556）
[3] Su, S*., Chai, G., Meng, J., Sheng, X., Mouraux, A. & Zhu, X. (2022). Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control. Journal of neural engineering, 19(1), 016028. （JCR Q2, IF: 5.379）
[4] Su, S*., Chai, G., Xu, W., Meng, J., Sheng, X., Mouraux, A. & Zhu, X. (2022). Neural evidence for functional roles of tactile and visual feedback in the application of myoelectric prosthesis. Journal of Neural Engineering. （JCR Q2, IF: 5.379）
[5] Haipeng Xu*, Guohong Chai, Ningbin Zhang & Guoying Gu. Restoring finger-specific tactile sensations with a sensory soft neuroprosthetic hand through electrotactile stimulation [J]. Soft Science, 2022,2:19
[6] 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. & Zhao X.H. “A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback”, Nature biomedical engineering, 2021: 1-10. (JCR Q1, IF: 25.7）
[7] Lv, B., Chai, G., Sheng, X., Ding, H., & Zhu, X. (2021). Evaluating user and machine learning in short-and long-term pattern recognition-based myoelectric control. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 777-785.（JCR Q2, IF: 4.528）
[8] Ye H.P.*, Fan Z., Chai G.H., Li G.Y., Wei Z. X., Chen L., Mao Y., Sheng X.J. & Zhu X.Y., “Decoding own and other name using multi-site stereo-electroencephalography”, Frontiers in Neuroscience, 2021,（JCR Q2, IF: 4.677）
[9] 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. （JCR Q2, IF: 5.379）
[10] Su S.Y.*, Chai G.H., Sheng X.J. Meng J.J. & Zhu X.Y., “Contra-lateral desynchronized alpha oscillations linearly correlate with discrimination performance of tactile acuity”, Journal of Neural Engineering, 2020, 17(4): 046041. （JCR Q2, IF: 5.379）
[11] Su S.Y.*, Chai G.H., Shu X.K., Sheng X.J. & 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.（JCR Q2, IF: 5.379）
[12] Chen C.*, Chai G.H., Guo W.C., Sheng X.J., & 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.（JCR Q2, IF: 5.379）
[13] Chai G.H., Zhang D.G. & 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 （JCR Q2, IF: 4.528）
[14] Chai G.H., Sui X.H., Li S., He L.W. & Lan N., “Characterization of evoked tactile sensation in forearm amputees with transcutaneous electrical nerve stimulation”. Journal of Neural Engineering, 2015, 12(6): 066002.（JCR Q2, IF: 5.379）
[15] Chai G.H., Sui X.H., Li P., Liu X.X. & 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.
2. Selected conference articles
[1] Guang Feng*, Jiaji Zhang†, Guohong Chai†, Maoqin Li, Guokun Zuo, & 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. & 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. & 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 & 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 & 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. & 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., Sheng, X., Jia, J., & Zhu, X. 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 compu- tational 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.
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, 申请号：202211603381.3
[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, 申请号：202211603179.0
[3] 盛鑫军，柴国鸿，郭伟超，麦熙名，丁雪聪，一种基于电刺激与肌肉信息检测的疲劳缓解装置，中国发明专利，申请号：201811367926.9，公开号：CN109550146A.
►联系方式
- Email：ghchai99@nimte.acn.cn