何家源，1988年1月
博士，特聘研究员，博导，华西医院/华西临床医学院，四川大学
国家高层次青年人才计划入选者
电邮：jiayuan.he@wchscu.cn
教育经历：
2010.09-2016.09 博士（机械工程），机械与动力工程学院，上海交通大学
2006.09-2010.06 学士（机械工程及自动化），机电学院，南京航空航天大学
研究方向：
神经控制接口，生机电智能系统，人机交互，生物信号检测与处理
从2012年至今，先后在国际期刊上发表SCI论文20余篇，入选国家高层次海外青年人才计划，获2020年教育部自然科学一等奖。
研究经历：
2022.02-至今 特聘研究员 华西医院，四川大学
2020.12-2022.01 助理教授（Research Assistant Professor），系统设计系，加拿大滑铁卢大学
2020.06-2020.11 副研究员（Research Associate），系统设计系，加拿大滑铁卢大学
2016.12-2020.05 博士后研究员（Postdoctoral Fellow），系统设计系，加拿大滑铁卢大学
论文发表：
一作期刊论文
[1] He J.Y., Zhang D.G., Sheng X.J., Li S.C. and Zhu X.Y., Invariant Surface EMG Feature Against Varying Contraction Level for Myoelectric Control Based on Muscle Coordination [J]. IEEE Journal of Biomedical and Health Informatics, 2015, 19(3), 874-882. (doi: 10.1109/JBHI.2014.2330356)
[2] He J.Y., Zhang D.G., Jiang N., Sheng X.J., Farina D. and Zhu X.Y., User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control [J]. Journal of Neural Engineering, 2015, 12(4), 046005. (doi: 10.1088/1741-2560/12/4/046005)
[3] He J.Y., and Zhu X.Y., Combining Improved Gray-Level Co-Occurrence Matrix with High Density for Myoelectric Control Robustness to Electrode Shift [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017, 25(9), 1539-1548. (doi: 10.1109/TNSRE.2016.2644264)
[4] He J.Y., Sheng X.J., Zhu X.Y, and Jiang N, Electrode density affects the robustness of myoelectric pattern recognition system with and without electrode shift [J]. IEEE Journal of Biomedical and Health Informatics, 2019, 23(1), 156-163. (doi: 10.1109/JBHI.2018.2805760)
[5] He J.Y., Sheng X.J., Zhu X.Y, Jiang C.Z. and Jiang N, Spatial Information Enhances Myoelectric Control Performance with Only Two Channels [J]. IEEE Transactions on Industrial Informatics,2019, 15(2), 1226-1233. (doi: 10.1109/TII.2018.2869394)
[6] He J.Y., Luo H, Jia J, Yeow J. and Jiang N, Wrist and Finger Gesture Recognition with Single-element A-mode Ultrasound signal: A Comparison with Single-channel Surface Electromyogram [J]. IEEE Transactions on Biomedical Engineering, 2018, 66(5), 1277-1284. (doi: 10.1109/TBME.2018.2872593)
[7] He J.Y., Li K, Liao X, Zhang Pin and Jiang N, Real-Time Detection of Acute Cognitive Stress Using a Convolutional Neural Network From Electrocardiographic Signal [J]. IEEE Access, 2019, 7, 42710-42717. (doi: 10.1109/ACCESS.2019.2907076)
[8] He J.Y., Sheng X.J., Zhu X.Y. and Jiang N, A Novel Framework Based on Position Verification for Robust Myoelectric Control Against Sensor Shift [J]. IEEE Sensors Journal, 2019;19(21):9859-68. (doi: 10.1109/JSEN.2019.2927325)
[9] He. J.Y and Jiang N, Biometric from Surface Electromyogram (sEMG): Feasibility of User Verification and Identification Based on Gesture Recognition [J], Frontiers in Bioengineering and Biotechnology, 2020, 8. (doi: 10.3389/fbioe.2020.00058)
[10] He J.Y., Manas J, Chang J, and Jiang N, Efficiently Correcting Armband Rotation for Myoelectric Control from Electrode Position Verification [J]. Journal of Neural Engineering, (doi.org/10.1088/1741-2552/ab8682.).Accepted.
[11] Ding L*, He J.Y*, Yao, L, Zhuang J.Y, Chen S, Wang H, Jiang N and Jia J, Mirror Visual Feedback Combining Vibrotactile Stimulation Promotes Embodiment Perception: an Electroencephalogram (EEG) Pilot Study [J], Frontiers in Bioengineering and Biotechnology, Accepted (* Equal Contribution).
[12] He J.Y., Sheng X.J., Zhu X.Y, and Jiang N, Position Identification for Robust Myoelectric Control against Electrode Shift [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, Accepted.