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  戴晨赟

  长聘教轨副教授，博士生导师。戴晨赟博士于2023年加入必赢565net官网，长期致力于包括神经假肢/外骨骼、人造脊髓、医疗机器人的研究，旨在利用医疗芯片结合电子信息与生物医学技术实现对人体器官的功能替代，以实现患者康复的目的。近三年发表论文50余篇，主持国家自然科学基金2项及省部级项目2项，并获得上海海外高层次人才、浦江人才等荣誉。戴博士的研究注重产学研转化，其研究成果已转化为多款商业化假肢产品并被美国波士顿电视台追踪报道，并受华为中央研究院资助研发华为手表中的人机交互模块。此外，戴博士曾任职于上海市发展和改革委员会，推进多项政府的产学研政策改革，并撰写了上海市“十四五”规划科技先导产业发展一章。

2013年8月-2016年8月，伍斯特理工学院，工程学院，电气及计算机工程系，博士

2011年8月-2013年5月，伍斯特理工学院，工程学院，电气及计算机工程系，硕士

2006年9月-2010年6月，南京航空航天大学，自动化学院，电气工程系，本科

2016年9月-2019年1月，北卡罗来纳大学教堂山分校，医学院，生物医学工程系，博士后

2019年2月-2023年6月，复旦大学，信息科学与工程学院，生物医学工程中心，副研究员

2023年7月-今，必赢565net官网，必赢565net官网，长聘教轨副教授

2020年3月-2021年6月，上海市发展和改革委员会（全职借调），主要负责上海市战略性新兴与先导产业“十四五”规划、上海市脑机接口市级重大科技专项评审等工作

基于电子电路技术研发智能人机交互硬件系统；基于人工智能技术的用户意图识别算法；相关硬件与算法的嵌入式或上位机软件开发。课题组研究偏重产学研结合，注重实际硬件系统的临床应用，多款产品已实现商业化落地。

主要研究方向如下：

1、针对瘫痪病人的植入式人造脊髓与人造神经系统、以及外周辅助运动康复系统

2020年国家自然科学基金青年项目，主持

2019年上海市浦江人才，主持

2020年上海市自然科学基金，主持

2022年华为中央研究院项目，主持

2022年科技部2030项目，骨干

第一或通讯作者（*为通讯作者）sci论文列表：

2023年：

Fan, J., Jiang, X., Liu, X., Jia, F., Dai, C.*. (2023). Surface EMG Feature Disentanglement for Robust Hand Gesture Recognition. Expert Systems With Applications, Accepted

Guo, Y.,..., Dai, C.*, & Chen, W. (2023). sEMG-based Inter-Session Hand Gesture Recognition via Domain Adaptation with Locality Preserving and Maximum Margin. International Journal of Neural Systems, Accepted
Wu, Y., Jiang, X., Guo, Y., Zhu, H., Dai, C.*, & Chen, W. (2023). Physiological measurements for driving drowsiness: a comparative study of multi-modality feature fusion and selection. Computers in biology and medicine, 167, 107590.
Jiang, X., Fan, J., Zhu, Z., Wang, Z., Guo, Y., Liu, X., ... & Dai, C.* (2023). Cybersecurity in neural interfaces: Survey and future trends. Computers in Biology and Medicine, 107604.
Li, J., Jiang, X., Liu, X., Jia, F., & Dai, C.* (2023). Optimizing the feature set and electrode configuration of high-density electromyogram via interpretable deep forest. Biomedical Signal Processing and Control, 87, 105445.

Tan, X., Jiang, X., Lin, Z., Liu, X., Dai, C.*, & Chen, W. (2023). Extracting spatial muscle activation patterns in facial and neck muscles for silent speech recognition using high-density sEMG. IEEE Transactions on Instrumentation and Measurement, Accepted

Jiang, X., Nazarpour, K., Dai, C. * (2023). Explainable and Robust Deep Forests for EMG-Force Modeling, IEEE Journal of Biomedical and Health Informatics, Accepted.

Wu,Y,..., Dai, C.* & Chen, W. (2023). Clinical Validation of a Capacitive Electrocardiogram Cushion Utilized for Arrhythmias Monitoring. IEEE Transactions on Instrumentation and Measurement, 72, 1-13.

2022年：

Meng, L.,..., Dai, C.* & Chen, W. (2022). User-Tailored Hand Gesture Recognition System for Wearable Prosthesis and Armband Based on Surface Electromyogram. IEEE Transactions on Instrumentation and Measurement, 71, 1-16.

Meng, L.,..., Dai, C.* & Chen, W. (2022). Automatic Upper-Limb Brunnstrom Recovery Stage Evaluation via Daily Activity Monitoring. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 2589-2599.

Jiang, X., Liu, X., Fan, J., Dai, C.*, Clancy, E. A. & Chen, W. (2022). Random Channel Masks for Regularization of Least Squares-Based Finger EMG-Force Modeling to Improve Cross-Day Performance. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 2157-2167.

Jiang, X., Meng, L., Liu, X., Fan, J., Ye, X., Dai, C.* & Chen, W. (2022). Optimizing the Cross-Day Performance of Electromyogram Biometrics Decoder. IEEE Internet of Things Journal, 10(5), 4388-4402.

Jiang, X., Liu, X., Fan, J., Ye, X., Dai, C.*, Clancy, E. A. & Chen, W. (2022). Measuring Neuromuscular Electrophysiological Activities to Decode HD-sEMG Biometrics for Cross-Application Discrepant Personal Identification in Smart Environment. IEEE Transactions on Instrumentation and Measurement, 71, 1-15.

Ren, H., Zou, L., Wang, L., Lu, C., Yuan, Y., Dai, C.* and Chen, W. (2022). fNIRS-Based Dynamic Functional Connectivity Reveals the Innate Musical Sensing Brain Networks in Preterm Infants. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 1806-1816.

Jiang, X., Liu, X., Fan, J., Ye, X., Dai, C.*, Clancy, E. A., Farina, D., & Chen, W. (2022). Optimization of HD-sEMG based Cross-Day Hand Gesture Classification by Optimal Feature Extraction and Data Augmentation. IEEE Transactions on Human-Machine Systems, 52(6), 1281-1291.

Meng, L., Chen, Q., Jiang, X., Liu, X., Fan, J., Dai, C.*, & Chen, W. (2022). Evaluation of decomposition parameters for high-density surface electromyogram using fast independent component analysis algorithm. Biomedical Signal Processing and Control, 75, 103615.

Fan, J., Jiang, X., Liu, X., Zhao, X., Ye, X., Dai, C.*, Clancy, E. A., Akay, M., & Chen, W. (2022). Cancelable HD-sEMG Biometric Identification Via Deep Feature Learning. IEEE Journal of Biomedical and Health Informatics, 22(4), 1782 - 1793.

2021年：

Jiang, X., Xu, K., Liu, X., Dai, C.*, Clifton, D. A., Clancy, E. A., Akay, M., & Chen, W. (2021). Neuromuscular Password-based User Authentication. IEEE Transactions on Industrial Informatics, 17(4), 2641-2652.

Jiang, X., Liu, X., Fan, J., Ye, X., Dai, C.*, Clancy, E. A., Farina, D., & Chen, W. (2021). Enhancing IoT Security via Cancelable HD-sEMG-based Biometric Authentication Password, Encoded by Gesture. IEEE Internet of Things Journal, 8(22),16535 - 16547.

Jiang, X., Xu, K., Liu, X., Dai, C.*, Clifton, D. A., Clancy, E. A., Akay, M., & Chen, W. (2021). Cancelable HD-sEMG-based Biometrics for Cross-Application Discrepant Personal Identification. IEEE Journal of Biomedical and Health Informatics, 25(4), 1070-1079.

Jiang, X., Ren, H., Xu, K., Ye, X., Dai, C.*, Clancy, E. A., Zhang, Y., & Chen, W. (2021). Quantifying Spatial Activation Patterns of Motor Units in Finger Extensor Muscles. IEEE Journal of Biomedical and Health Informatics, 25(3), 647-655.

Guo, Y., Liu, X., Peng, S., Jiang, X., Xu, K., Chen, C., Z. Wang, Dai, C.* & Chen, W. (2021). A Review of Wearable and Unobtrusive Sensing Technologies for Chronic Disease Management. Computers in Biology and Medicine, 104163.

Jiang, X., Liu, X., Fan, J., Ye, X., Dai, C.*, Clancy, E. A., Akay, M., & Chen, W. (2021). Open Access Dataset, Toolbox and Benchmark Processing Results of High-Density Surface Electromyogram Recordings. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 1035-1046.

Jiang, X., Bardizbanian, B., Dai, C.*, Chen, W., & Clancy, E. A. (2021). Data Management for Transfer Learning Approaches to Elbow EMG-Torque Modeling. IEEE Transactions on Biomedical Engineering, 68(8), 2592-2601.

Ren, H., Zou, L., Wang, L., Lu, C., Yuan, Y., Dai, C.* and Chen, W. (2021). Evaluation of the short-term music therapy on brain functions of preterm infants using functional Near-infrared Spectroscopy. Frontiers in Neurology, 1634.

2020年及以前：

Dai, C., & Hu, X. (2020). Finger joint angle estimation based on motoneuron discharge activities. IEEE Journal of Biomedical and Health Informatics,24(3), 760-767.

Dai, C., & Hu, X. (2019). Independent component analysis based algorithms for high-density electromyogram decomposition: Experimental evaluation of upper extremity muscles. Computers in Biology and Medicine, 108, 42–48.

Dai, C., & Hu, X. (2019). Independent component analysis based algorithms for high-density electromyogram decomposition: Systematic evaluation through simulation. Computers in Biology and Medicine, 109, 171–181.

Dai, C., Zhu, Z., Martinez-Luna, C., Hunt, T. R., Farrell, T. R., & Clancy, E. A. (2019). Two degrees of freedom, dynamic, hand-wrist EMG-force using a minimum number of electrodes. Journal of Electromyography and Kinesiology, 47, 10–18.

Dai, C., Martel, S., Martel, F., Rancourt, D., & Clancy, E. A. (2019). Single-trial estimation of quasi-static EMG-to-joint-mechanical-impedance relationship over a range of joint torques. Journal of Electromyography and Kinesiology, 45, 18–25.

Dai, C., Cao, Y., & Hu, X. (2019). Prediction of individual finger forces based on decoded motoneuron activities. Annals of Biomedical Engineering, 47(6), 1357–1368.

Dai, C., & Hu, X. (2019). Extracting and classifying spatial muscle activation patterns in forearm flexor muscles using high-density electromyogram recordings. International Journal of Neural Systems, 29(01), 1850025.

Dai, C., Zheng, Y., & Hu, X. (2018). Estimation of muscle force based on neural drive in a hemispheric stroke survivor. Frontiers in Neurology, 9, 187.

Dai, C., Shin, H., Davis, B., & Hu, X. (2017). Origins of Common Neural Inputs to Different Compartments of the Extensor Digitorum Communis Muscle. Scientific Reports, 7(1).

Dai, C., Suresh, N. L., Suresh, A. K., Rymer, W. Z., & Hu, X. (2017). Altered motor unit discharge coherence in paretic muscles of stroke survivors. Frontiers in Neurology, 8.

Dai, C., Bardizbanian, B., & Clancy, E. A. (2017) Comparison of constant-posture force-varying EMG-force dynamic models about the elbow. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(9), 1529–1538.

Dai, C., Li, Y., Christie, A., Bonato, P., McGill, K. C., & Clancy, E. A. (2015). Cross-comparison of three electromyogram decomposition algorithms assessed with experimental and simulated data. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 23(1), 32–40.