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Design and Voluntary Control of Variable Stiffness Exoskeleton Based on sEMG Driven Model
IEEE Robotics and Automation Letters, 2022Exoskeleton robots are an exciting potential solution for patients with motor dysfunction to restore their daily activities. This letter introduces a variable stiffness exoskeleton robot (VSA-EXO) with variable stiffness actuators and a voluntary control
Yanghui Zhu +3 more
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Design of SEMG Recognition System
Advanced Materials Research, 2011Surface electromyography (sEMG) is recorded from the surface of skeleton muscle by electrodes, it is the bioelectricity discharged by neuromuscular activities. This paper designed a data acquisition platform of sEMG, which contains hardware module and software module. The hardware contains electrodes, microcomputer, power and filters.
Jing Jin Xie, Lei Zuo
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Towards High Density sEMG (HD-sEMG) Acquisition Approach for Biometrics Applications
2019This is the third chapter of this book dedicated to EMG biometrics modality. The purpose is to highlight a Multi-Channel technique based on a High Density sEMG (HD-sEMG) acquisition. In fact, HD-sEMG recording systems can be used to overcome the limitation of classical bipolar and monopolar sEMG recording systems.
Al Harrach, Mariam +2 more
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IEEE Transactions on Instrumentation and Measurement, 2022
It is vital to measure muscular fatigue for human–machine interaction (HMI) and avoiding muscle impairment. This article presents a novel approach to comprehensively evaluate muscle fatigue through the fusion of mini-grid surface electromyography (sEMG),
Weichao Guo, X. Sheng, Xiangyang Zhu
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It is vital to measure muscular fatigue for human–machine interaction (HMI) and avoiding muscle impairment. This article presents a novel approach to comprehensively evaluate muscle fatigue through the fusion of mini-grid surface electromyography (sEMG),
Weichao Guo, X. Sheng, Xiangyang Zhu
semanticscholar +1 more source
Speech recognition using facial sEMG
2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2017This paper presents a study of speech recognition based on electromyographic biosignals captured from the articulatory muscles in the face using surface electrodes. This paper compares the speech recognition system for spoken English and Malay words by a group of Malay native speakers.
Mok Win Soon +4 more
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Analyzing an sEMG signal using wavelets
2009Electromyography (EMG) is an experimental technique developed with the purpose of detecting muscle movement. The technique generates a signal that is formed by impulses of muscle fibers during the movement of muscles. The generated signal is very sensitive and can therefore be influenced by several external factors altering its shape and ...
Bastiaensen, Y. +2 more
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ACS Sensors
Textile-based surface electromyography (sEMG) electrodes have emerged as a prominent tool in muscle fatigue assessment, marking a significant shift toward innovative, noninvasive methods.
M. H. Medagedara +4 more
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Textile-based surface electromyography (sEMG) electrodes have emerged as a prominent tool in muscle fatigue assessment, marking a significant shift toward innovative, noninvasive methods.
M. H. Medagedara +4 more
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Hand movement recognition from sEMG signals using Fourier decomposition method
, 2021Surface electromyogram (sEMG) provides a non-invasive way to collect EMG signals. The sEMG signals acquired from the muscles of the forearm can be used to recognize the hand grasps and gestures.
Binish Fatimah +3 more
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A comparison of neural networks algorithms for EEG and sEMG features based gait phases recognition
Biomedical Signal Processing and Control, 2021Surface electromyography (sEMG) and electroencephalogram (EEG) can be utilized to discriminate gait phases. However, the classification performance of various combination methods of the features extracted from sEMG and EEG channels for seven gait phase ...
Pengna Wei +3 more
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IEEE Sensors Journal, 2022
Surface electromyogram (sEMG) is widely used in active rehabilitation control for stroke patients. However, the accuracy of movement recognition using sEMG signals is affected by abnormal states such as muscular fatigue and muscle weakness.
Shiqi Yang, Min Li, Jiale Wang
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Surface electromyogram (sEMG) is widely used in active rehabilitation control for stroke patients. However, the accuracy of movement recognition using sEMG signals is affected by abnormal states such as muscular fatigue and muscle weakness.
Shiqi Yang, Min Li, Jiale Wang
semanticscholar +1 more source