Results 201 to 210 of about 39,692 (260)

sEMG-Based Gesture Recognition Using Deep Learning From Noisy Labels

IEEE journal of biomedical and health informatics, 2022
Gesture recognition for myoelectric prosthesis control utilizing sparse multichannel surface Electromyography (sEMG) is a challenging task, and from a Muscle-Computer Interface (MCI) standpoint, the performance is still far from optimal.
Akram Fatayer, Wenpeng Gao, Yili Fu
semanticscholar   +1 more source

A Multimodal Multilevel Converged Attention Network for Hand Gesture Recognition With Hybrid sEMG and A-Mode Ultrasound Sensing

IEEE Transactions on Cybernetics, 2022
Gesture recognition based on surface electromyography (sEMG) has been widely used in the field of human–machine interaction (HMI). However, sEMG has limitations, such as low signal-to-noise ratio and insensitivity to fine finger movements, so we consider
Sheng Wei, Yue Zhang, Honghai Liu
semanticscholar   +1 more source

Standard Deviation of sEMG

Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2013
Certain muscle activities (e.g. static muscle activities for prolonged periods of time) and resultant movement patterns may be associated with the development of cumulative trauma disorders. Currently, there is no simple, well-defined measure to discern if a muscle is performing a static or dynamic activity.
Timothy J. Duffield, S. Camille Peres, William Amonette, Paul Ritchey   +3 more
openaire   +1 more source

Continuous human gait tracking using sEMG signals

2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020
Gait can reflect human biological status during walking, which can be used for disease detect, identity verification or robot control, etc. Traditionally, gait analysis only classifies a gait cycle into a few discrete stages. In this paper, human gait will be decoded continuously using surface electromography (sEMG).
Dezhen, Xiong, Daohui, Zhang, Xingang, Zhao, Yiwen, Zhao   +3 more
openaire   +2 more sources

Facial Expression Recognition with sEMG Method

2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 2015
Facial expression recognition has broad application prospects in the fields of psychological study, nursing care, Human Computer Interaction as well as affective computing. The method with surface Electromyogram (sEMG), which is one of vital bio-signals, has its superiority in several aspects such as high temporal resolution and data processing ...
Tenhunen Aarne Hannu Kristian, Rahmani Amir, Jiang Mingzhe, Liljeberg Pasi Kristian, Westerlund Tomi Vesa Juhani   +4 more
openaire   +2 more sources

A sEMG Recording System

Key Engineering Materials, 2014
The sEMG (surface electromyographic) plays a significant role in the rehabilitation medicine, particularly in exoskeleton robotic treatment. A sEMG recording system using STM32F407 DISCOVERY development board and Labview software, combined with multiple signal acquisition sensors was proposed in this paper. The UC/OS-II operating system was embedded in
Yong Sheng Gao, Jie Bai, Sheng Xin Wang, Jie Zhao, Xiao Yan Li   +4 more
openaire   +1 more source

Optimization of HD-sEMG-Based Cross-Day Hand Gesture Classification by Optimal Feature Extraction and Data Augmentation

IEEE Transactions on Human-Machine Systems, 2022
Human–machine interaction requires accurate recognition of human intentions (e.g., via hand gestures). Here, we assessed the cross-day robustness of widely used hand gesture classification techniques applied to high-density surface electromyogram (HD ...
Xinyu Jiang, Xiangyu Liu, Jiahao Fan, Xinming Ye, C. Dai, E. Clancy, D. Farina, W. Chen   +7 more
semanticscholar   +1 more source

Improving the Robustness and Adaptability of sEMG-Based Pattern Recognition Using Deep Domain Adaptation

IEEE journal of biomedical and health informatics, 2022
The pattern recognition (PR) based on surface electromyography (sEMG) could improve the quality of daily life of amputees. However, the lack of robustness and adaptability hinders its practical application.
Ping Shi, Xinran Zhang, Wei Li, Hongliu Yu   +3 more
semanticscholar   +1 more source

INDEPENDENT COMPONENT APPROACH TO THE ANALYSIS OF HAND GESTURE sEMG AND FACIAL sEMG

Biomedical Engineering: Applications, Basis and Communications, 2008
Independent component analysis algorithm, a recently developed multivariate statistical data analysis technique, has been successfully used for signal extraction in the field of biomedical and statistical signal processing. This paper reviews the concept of ICA and demonstrates its usefulness and limitations in the context of surface electromyogram ...
Naik, Ganesh R. (R19010), Kumar, Dinesh K., Arjunan, Sridhar P., Palaniswami, Marimuthu   +3 more
openaire   +2 more sources

sEMG-based technology for silent voice recognition

Computers in Biology and Medicine, 2023
Silent speech recognition (SSR) is a system that implements speech communication when a sound signal is not available using surface electromyography (sEMG)-based speech recognition. Researchers have used surface electrodes to record the electrically-activated potential of human articulation muscles to recognize speech content. SSR can be used for pilot-
Wei Li, Jianping Yuan, Lu Zhang, Jie Cui, Xiaodong Wang, Hua Li   +5 more
openaire   +2 more sources