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A Comprehensive Channel and Feature Selection Method for Myoelectric Pattern Recognition
2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM), 2021The advent of myoelectric control schemes provides promising chances for locomotion empowerment and restoration of those with disabilities. Despite substantial efforts have been made into advancing sEMG-based motion recognition, it may be a little tricky to determine appropriate muscles and features for people with muscle disorders or different muscle ...
Mengyao Li +5 more
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Pattern-recognition program for analysis of colon myoelectric and pressure data
Digestive Diseases and Sciences, 1986A pattern-recognition program was developed which emulates visual scoring of colonic myoelectric and pressure recordings. It smoothes digitized data with a moving average filter, computes difference scores between successive groups of three data points, and uses the signs of these difference scores to detect the beginning and end of waves.
R, Parker, W E, Whitehead, M M, Schuster
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High-Density Myoelectric Pattern Recognition Toward Improved Stroke Rehabilitation
IEEE Transactions on Biomedical Engineering, 2012Myoelectric pattern-recognition techniques have been developed to infer user's intention of performing different functional movements. Thus electromyogram (EMG) can be used as control signals of assisted devices for people with disabilities. Pattern-recognition-based myoelectric control systems have rarely been designed for stroke survivors.
Xu Zhang, Ping Zhou
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The Recognition Of Myoelectric Patterns For Prosthetic Limb Control
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991, 2005This paper describes a novel approach to the control of a multifunction prosthesis based on the classification of myoelectric patterns. It is shown that the myoelectric signal exhibits a deterministic structure during the initial phase of a muscle contraction.
B. Hudgins, P. Parker, R.N. Scott
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Improving myoelectric pattern recognition using invariant feature extraction
2014 IEEE International Conference on Information and Automation (ICIA), 2014The existing algorithms of myoelectric pattern recognition (MPR) are far from enough to satisfy the criteria which an ideal control system for upper extremity prostheses should fulfill. This study focuses on the criterion of short training, or possibly zero training.
Jianwei Liu +3 more
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Myoelectric Pattern Recognition for Controlling a Robotic Hand: A Feasibility Study in Stroke
IEEE Transactions on Biomedical Engineering, 2019Myoelectric pattern recognition has been successfully applied as a human-machine interface to control robotic devices such as prostheses and exoskeletons, significantly improving the dexterity of myoelectric control. This study investigates the feasibility of applying myoelectric pattern recognition for controlling a robotic hand in stroke patients ...
Xu Zhang, Ping Zhou, Raymond Kai-Yu Tong
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The effect of electrode displacements on pattern recognition based myoelectric control
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006Pattern recognition based myoelectric controllers rely on a fundamental assumption that the patterns detected under a given electrode are repeatable for a given state of muscle activation. Consequently, electrode displacements on the skins surface affect the classification accuracy of the pattern based myoelectric controller.
Levi J. Hargrove +2 more
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Improving Myoelectric Pattern Recognition Robustness to Electrode Shift by Autoencoder
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018It is evident that the electrode shift will result in a degradation of myoelectric pattern recognition classification accuracy, which is inevitable during the prosthetic socket donning and doffing. To cope with this limitation, we propose an unsupervised feature extraction method called sparse autoencoder (SAE) to extract the robust spatial structure ...
Bo Lv, Xinjun Sheng, Xiangyang Zhu
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Influence of multiple dynamic factors on the performance of myoelectric pattern recognition
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015Hand motion classification using surface Electromyogram (EMG) signals has been widely studied for the control of powered prosthetics in laboratory conditions. However, clinical applicability has been limited, as imposed by factors like electrodes shift, variations in the contraction force levels, forearm rotation angles, change of limb position and ...
Rami N. Khushaba +2 more
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Activity Recognition Based on Pattern Recognition of Myoelectric Signals for Rehabilitation
2017Limb-amputation, stroke, trauma, and some other congenital anomalies not only decrease patients’ quality of life but also cause severe psychological burdens to them. Several advanced rehabilitation technologies have been developed to help patients with limb disabilities restore their lost motor functions.
Oluwarotimi Williams Samuel +4 more
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