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Chen Chen
Shanghai Jiao Tong University
Motor unitComputer visionKinematicsComputer scienceControl theory
7Publications
1H-index
3Citations
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Publications 10
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OBJECTIVE: Estimation of the discharge pattern of motor units by electromyography (EMG) decomposition has been applied for neurophysiologic investigations, clinical diagnosis, and human-machine interfacing. However, most of the methods for EMG decomposition are currently applied offline. Here, we propose an approach for high-density surface EMG decomposition in real-time. METHODS: A real-time decomposition scheme including two sessions, offline training and online decomposition, is proposed base...
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#1Yang Yu (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 4 authors...
Abstract Human machine interface (HMI) based on surface electromyography (sEMG) promises to provide an intuitive and noninvasive way to interact with peripheral equipments, such as prostheses, exoskeletons, and robots. Most recently, advances in machine learning, especially in deep learning algorithms, present the capabilities in constructing complicated mapping functions. In this study, we construct a stacked autoencoder-based deep neural network (SAE-DNN) to continuously estimate multiple degr...
1 CitationsSource
#1Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Yang Yu (SJTU: Shanghai Jiao Tong University)H-Index: 1
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 7 authors...
Abstract Objective Methods for surface electromyographic (EMG) signal decomposition have been developed in the past decade, to extract neural information transferred from the spinal cord to muscles. Here, we characterize the accuracy in the identification of motor unit activities during hand postures from high-density EMG signals and we propose a mapping approach between these neural signals and hand gestures. Methods High-density EMG signals were recorded during 11 hand gesture tasks from 11 ab...
Source
#1Guangye Li (NYSDOH: New York State Department of Health)H-Index: 1
#1Guangye LiH-Index: 3
Last. Dingguo ZhangH-Index: 20
view all 8 authors...
Objectives: The precise localization of intracranial electrodes is a fundamental step relevant to the analysis of intracranial electroencephalography (iEEG) recordings in various fields. With the increasing developments of the iEEG studies in human neuroscience, higher requirements have been posed on the localization process, resulting in urgent demands for more integrated, easy-operation and versatile tools for electrodes localization and visualization. Towards addressing this need, we develop ...
1 CitationsSource
#1Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Shihan Ma (SJTU: Shanghai Jiao Tong University)
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 4 authors...
The aim of the study was to apply the real-time surface electromyography (EMG) decomposition to the continuous estimation of grasp kinematics. A real-time decomposition scheme based on the convolutional compensation kernel algorithm was proposed. High-density surface EMG signals and grasp kinematics were recorded concurrently from five able-bodied subject. The electro-mechanical delay between identified motor unit activities and grasp kinematics was characterized and utilized to optimize the mul...
Source
Jul 1, 2019 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Shihan Ma (SJTU: Shanghai Jiao Tong University)
#2Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 5 authors...
Motor unit (MU) global firing rate is widely applied in physiological and clinical investigation. Currently it still remains difficult to measure the MU global firing rate from sEMG. In this study, we propose a new feature of maximum power ampiltude (MPA) from sEMG power spectrum. Based on an analysis of mathematical model and simulated signals, MPA was demonstrated to be highly correlated with the MU global firing rate. The performance of MPA was comparable with features based on sEMG amplitude...
Source
#1Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Guohong Chai (SJTU: Shanghai Jiao Tong University)H-Index: 4
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 6 authors...
OBJECTIVE: The aim of the study was to characterize the accuracy in the identification of motor unit discharges during natural movements using high-density electromyography (EMG) signals and to investigate their correlation with finger kinematics. APPROACH: High-density EMG signals of forearm muscles and finger joint angles were recorded concurrently during hand movements of ten able-bodied subjects. EMG signals were decomposed into motor unit spike trains (MUSTs) with a blind-source separation ...
3 CitationsSource
#1Yang Yu (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 4 authors...
The continuous estimation of kinematics or kinetics from electromyography (EMG) signals is essential for intuitive control of prostheses and other human-machine interfaces based on bioelectrical signals. In this preliminary study, we concentrate on the continuous estimation of wrist torques under isometric contraction of three separate degrees-of-freedom (D-oFs) with a stack-autoencoder based deep neural network. With this kind of deep neural network, features used for regression could be extrac...
Source
#1Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Yang Yu (SJTU: Shanghai Jiao Tong University)H-Index: 1
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 5 authors...
The aim of this study was to characterize the accuracy in the identification of motor unit discharges and to estimate wrist kinematics from motor unit behaviors. High-density electromyography (EMG) of forearm muscles and wrist torques in three degrees-of-freedom (DoFs) were recorded concurrently during wrist movements of 8 able-bodied subjects. The EMG signals were decomposed into motor unit spike trains (MUSTs) with a blind-source separation algorithm. Two methods based on principal component a...
Source
#1Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Tao Xie (SJTU: Shanghai Jiao Tong University)H-Index: 2
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 5 authors...
This study investigated the arm movements effect on the relationship between surface electromyography (EMG) signals and grasping force. An experiment was conducted with four static arm conditions and two dynamic arm conditions. Six able-bodied subjects participated in the experiment. Surface EMG signals were acquired from five forearm muscles to build a multiple linear regression model. Subjects were instructed to complete three kinds of calibration tasks to train the model and one voluntarily v...
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