戴晨赟
生物医学工程中心
职称：青年副研究员
职务：
电子邮件：chenyundai@fudan.edu.cn
办公地点：江湾校区交叉2号楼B5021室
电话：
课题组主页：





研究兴趣
学术任职
获奖情况
学习工作经历
授课情况
代表性论文或专著

生物信号处理：针对广泛的脑电、心电、肌电等电生理信号的处理；
人机系统控制算法研究：使用机器学习或深度学习实现包括手势识别、运动轨迹预测、步态识别等目标，旨在实现神经义肢、外骨骼机器人等系统的控制算法；
生物信息的身份认证系统：基于生物信息每个人的特异性，利用机器学习或深度学习算法识别不同的用户；
人机系统的迁移学习：使用机器学习或深度学习弱化个体差异，建立通用的人机系统模型；
运动中的神经信号协同机理研究；
基于电刺激的机器真实触觉感知：实现假肢外骨骼等系统的触觉感应，并利于经皮电刺激自然反馈回使用者的大脑；
硬件系统开发：神经假肢、外骨骼设计与系统开发。

现为下列期刊审稿人：
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Signal Processing
IEEE Transactions on Neural System and Rehabilitation Engineering
Journal of NeuroEngineering and Rehabilitation
Physiological Measurement
Frontiers in Neurology

人才项目：
2019年上海市浦江计划 具有真实触觉的手部智能假肢闭环回路控制的研究
2020年上海市人才项目 智能人机系统
基金项目：
2020年上海市自然科学基金基于非侵入式运动神经元解码实现智能仿生手灵巧运动控制的研究
2020年国家青年自然科学基金基于肌群间串扰消除模型实现手部智能假肢多自由度运动同步实时控制的研究

2006/09-2010/06，南京航空航天大学，电气工程及自动化，本科
2011/09-2013/05，美国伍斯特理工学院，电气及计算机工程，硕士
2013/09-2016/08，美国伍斯特理工学院，电气及计算机工程，博士
2016/09-2019/01，美国北卡罗来纳大学教堂山分校，生物医学工程，博士后
2019/02至今，复旦大学信息科学与工程学院电子工程系，青年副研究员
2020/03至今，上海市发展与改革委员会

招收对电子信息工程，尤其是对外骨骼、假肢、机器人等研究有兴趣的硕士生，要求专业背景包括，但不限于电子电气工程、计算机工程、生物医学工程、机械工程等专业。如果你想在现实中实现虚拟世界的一切，我们一起来研究吧！

SCI/EI论文：
2020年:
1. Jiang, X., Xu, K., Liu, X., Dai, C. *, Clifton, D. A., Clancy, E. A., Akay, M., & Chen, W. * (2020). Cancelable HD-sEMG-based Biometrics for Cross-Application Discrepant Personal Identification. IEEE Journal of Biomedical and Health Informatics. (Accepted)
2. Fan, J., Sun, C., Chen, C., Jiang, X., Liu, X., Zhao, X., Meng, L., Dai, C., & Chen, W. (2020). EEG data augmentation: Towards class imbalance problem in sleep staging tasks. Journal of Neural Engineering.(Accepted)
3. Xu, K., Jiang, X., Dai, C., & Chen, W. (2020). Stochastic Modeling for Photoplethysmography Compression. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 5925–5928.
4. Rajotte, K. J., Wang, H., Wang, H., Dai, C., Zhu, Z., Huang, X., & Clancy, E. A. (2020). Simplified Optimal Estimation of Time-Varying Electromyogram Standard Deviation (EMGσ). 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 3122–3125.
5. Peng, S., Xu, K., Bao, S., Yuan, Y., Dai, C., & Chen, W. (2020). Flexible Electrodes based Smart Mattress for Monitoring Physiological Signals of Heart and Autonomic Nerves in A Non-Contact Way. IEEE Sensors Journal.(Accepted)
6. Xu, K., Jiang, X., Lin, S., Dai, C., & Chen, W. (2020). Stochastic Modeling based Nonlinear Bayesian Filtering for Photoplethysmography De-noising in Wearable Devices. IEEE Transactions on Industrial Informatics.(Accepted)
7. Zhang, R., Jiang, X., Dai, C., & Chen, W. (2020). Tensor-based Uncorrelated Multilinear Discriminant Analysis for Epileptic Seizure Prediction. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 541–544.
8. Chen, Y., Dai, C.*, & Chen, W. * (2020). Cross-Comparison of EMG-to-Force Methods for Multi-DoF Finger Force Prediction Using One-DoF Training. IEEE Access, 8, 13958–13968.
9. Jiang, X., Xu, K., Liu, X., Liu, D., Dai, C.*, & Chen, W.* (2020). High-Density Surface Electromyogram-based Biometrics for Personal Identification. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 728–731.
10. Jiang, X., Ren, H., Xu, K., Ye, X., Dai, C. *, Clancy, E. A., Zhang, Y., & Chen, W. * (2020). Quantifying Spatial Activation Patterns of Motor Units in Finger Extensor Muscles. IEEE Journal of Biomedical and Health Informatics.(Accepted)
11. Jiang, X., Xu, K., Liu, X., Dai, C. *, Clifton, D. A., Clancy, E. A., Akay, M., & Chen, W. * (2020). Neuromuscular Password-based User Authentication. IEEE Transactions on Industrial Informatics.(Accepted)
12. Bardizbanian, B., Zhu, Z., Li, J., Huang, X., Dai, C., Martinez-Luna, C., McDonald, B. E., Farrell, T. R., & Clancy, E. A. (2020). Efficiently Training Two-DoF Hand-Wrist EMG-Force Models. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 369–373.
2019年：
13. 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.
14. 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.
15. 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.
16. Dai, C., & Hu, X. (2019). Finger joint angle estimation based on motoneuron discharge activities. IEEE Journal of Biomedical and Health Informatics.
17. 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.
18. 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.
19. 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), **.
20. Chen, Y., Dai, C.* & Chen, W. * (2019). A Real-time EMG-controlled Functional Electrical Stimulation System for Mirror Therapy. 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1–4.
21. Chen, Y., Jiang, X., Dai, C.* & Chen, W. * (2019). New Channel Merging Methods for Multi-DoF Force Prediction of Finger Contractions. 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1–4.
22. Wang, H., Rajotte, K. J., Wang, H., Dai, C., Zhu, Z., Bhuiyan, M., Huang, X., & Clancy, E. A. (2019). Optimal Estimation of EMG Standard Deviation in Additive Measurement Noise: Model-Based Derivations and Their Implications. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(12), 2328–2335.
23. Lan, N., Niu, C. M., Hao, M., Chou, C.-H., & Dai, C. (2019). Achieving Neural Compatibility With Human Sensorimotor Control in Prosthetic and Therapeutic Devices. IEEE Transactions on Medical Robotics and Bionics, 1(3), 122–134.
2018年以前：
24. 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.
25. 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.
26. 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). https://doi.org/10.1038/s41598-017-14555-x
27. 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(MAY). https://doi.org/10.3389/fneur.2017.00202
28. Bardizbanian, B., Zhu, Z., Li, J., Dai, C., Martinez-Luna, C., Huang, X., Farrell, T., & Clancy, E. A. (2018). Calibration of Dynamic Hand-Wrist EMG-Force Models using a Minimum Number of Electrodes. 2018 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1–2.
29. Bardizbanian, B., Zhu, Z., Li, J., Dai, C., Martinez-Luna, C., Huang, X., Farrell, T., & Clancy, E. A. (n.d.). 2018 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), Temple University, Philadelphia, PA, 1 December 2018.
30. Dai, C., & Farrell, T. R. (2016). Two degrees of freedom quasi-static EMG-force at the wrist using. Studies of the Relationship between the Surface Electromyogram, Joint Torque and Impedance, 2016, 94.
31. Clancy, E. A., Dai, C., Wartenberg, M., Martinez-Luna, C., Hunt, T. R., & Farrell, T. R. (2015). A pilot study assessing ipsilateral vs. Contralateral feedback in emg-force models of the wrist for upper-limb prosthesis control. 2015 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1–8.
32. Dai, Z., Li, C., Wang, X., Shu, H., Zhang, K., & Dai, C. (2017). A new laparoscopic technique of inguinal ligament suspension for vaginal vault prolapse. International Journal of Surgery, 43, 131–136.
33. Zhu, Z., Wartenberg, M., Clancy, E. A., Dai, C., Martinez-Luna, C., & Farrell, T. R. (2017). A pilot study of two degrees of freedom dynamic EMG-force at the wrist using a minimum number of electrodes. 2017 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1–6.
34. Li, Y., Dai, C., Clancy, E. A., Christie, A., Bonato, P., & McGill, K. C. (2013). Cross-comparison between two multi-channel EMG decomposition algorithms assessed with experimental and simulated data. 2013 39th Annual Northeast Bioengineering Conference, 191–192.
35. Fylstra, B. L., Dai, C., Hu, X., & Huang, H. H. (2018). Characterizing Residual Muscle Properties in Lower Limb Amputees Using High Density EMG Decomposition: A Pilot Study. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 5974–5977.
36. Dai, C. (2016). Studies of the relationship between the surface electromyogram, joint torque and impedance.
37. Dai, C. (2013). Cross-Comparison of Three Electromyogram Decomposition Algorithms Assessed with Simulated and Experimental Data.
38. Zhu, Q., Shu, H., Du, G., Dai, Z. & Dai, C.(2018). Impact of transvaginal modified sacrospinous ligament fixation with mesh for the treatment of pelvic organ prolapse-before and after studies. International Journal of Surgery, 52, 40–43.
39. Dai, C., Li, Y., Clancy, E. A., Bonato, P., Christie, A., & McGill, K. C. (2014). Performance of three electromyogram decomposition algorithms as a function of signal to noise ratio: Assessment with experimental and simulated data. 2014 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1–6.
40. Li, C., Dai, Z., Shu, H., Zhang, K., & Dai, C. Laparoscopic Inguinal Ligament Suspension for Vaginal Vault Prolapse: Video Step-by-Step. Videoscopy, 27(6).
41. Clancy, E. A., Martinez-Luna, C., Wartenberg, M., Dai, C., & Farrell, T. R. (2017). Two degrees of freedom quasi-static EMG-force at the wrist using a minimum number of electrodes. Journal of Electromyography and Kinesiology, 34. https://doi.org/10.1016/j.jelekin.2017.03.004
42. 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.
43. Dai, C., Cao, Y., & Hu, X. (2018). Estimation of Finger Joint Angle Based on Neural Drive Extracted from High-Density Electromyography. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 4820–4823.