Results 211 to 220 of about 37,674 (252)
Some of the next articles are maybe not open access.
IEEE Transactions on Instrumentation and Measurement, 2022
Gesture recognition via surface electromyography (sEMG) has drawn significant attention in the field of human–computer interaction. An important factor limiting the performance of sEMG-based pattern recognition (PR) is the generalization ability which ...
Cheng Shen +5 more
semanticscholar +1 more source
Gesture recognition via surface electromyography (sEMG) has drawn significant attention in the field of human–computer interaction. An important factor limiting the performance of sEMG-based pattern recognition (PR) is the generalization ability which ...
Cheng Shen +5 more
semanticscholar +1 more source
sEMG-Based Gesture Recognition Using Temporal History
IEEE Transactions on Biomedical Engineering, 2023Surface electromyography (sEMG) patterns have been decoded using learning-based methods that determine complicated nonlinear decision boundaries. However, overlapping classes in sEMG pattern recognition still degrade the classification accuracy because they cannot be separated by the decision boundaries. We hypothesized that certain overlapping classes
Chaerin Hong, Seongsik Park, Keehoon Kim
openaire +2 more sources
sEMG-Based Gesture Recognition Using Deep Learning From Noisy Labels
IEEE journal of biomedical and health informatics, 2022Gesture 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
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 +3 more
openaire +1 more source
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 +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), 2020Gait 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 +3 more
openaire +2 more sources
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
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
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, 2015Facial 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 +4 more
openaire +2 more sources
Advances and Disturbances in sEMG-Based Intentions and Movements Recognition: A Review
IEEE Sensors Journal, 2021Surface EMG-based gestures recognition systems are helping the disable to enjoy a better life. Academic institutes and commercial companies have been developing a lot of sEMG-based prosthesis, exoskeletons and rehabilitation systems.
Hao Xu, Anbin Xiong
semanticscholar +1 more source
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 +7 more
semanticscholar +1 more source
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 +7 more
semanticscholar +1 more source
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 +3 more
semanticscholar +1 more source
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 +3 more
semanticscholar +1 more source