Results 11 to 20 of about 3,364,312 (190)

Analysis of electrode locations on limb condition effect for myoelectric pattern recognition [PDF]

Journal of NeuroEngineering and Rehabilitation
Background Gesture recognition using surface electromyography (sEMG) has garnered significant attention due to its potential for intuitive and natural control in wearable human–machine interfaces.
Hai Wang, Na Li, Xiaoyao Gao, Ning Jiang, Jiayuan He   +4 more
doaj   +4 more sources

Estimates of Classification Complexity for Myoelectric Pattern Recognition

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
Myoelectric pattern recognition (MPR) can be used for intuitive control of virtual and robotic effectors in clinical applications such as prosthetic limbs and the treatment of phantom limb pain. The conventional approach is to feed classifiers with descriptive electromyographic (EMG) features that represent the aimed movements.
Niclas Nilsson, Max Ortiz-Catalan
openaire   +2 more sources

Learning Non-Euclidean Representations With SPD Manifold for Myoelectric Pattern Recognition

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022
How to learn informative representations from Electromyography (EMG) signals is of vital importance for myoelectric control systems. Traditionally, hand-crafted features are extracted from individual EMG channels and combined together for pattern ...
Dezhen Xiong, Daohui Zhang, Xingang Zhao, Yaqi Chu, Yiwen Zhao   +4 more
doaj   +3 more sources

Pattern Recognition Myoelectric Control: Evaluating Emg Pattern Separability

, 2018
Pattern recognition based myoelectric control for upper limb prostheses has gained increasing attention in the last years as it seems to offer more intuitive control than conventional, direct control. However, for such control to be feasible, the prosthesis user needs to have sufficient control of muscle contractions to create EMG patterns suitable for
Franzke, AW; Kristoffersen, MB, Murgia, A; Sluis, CK van der; Bongers, RM, (5230223), Franzke, AW; Kristoffersen, MB, Murgia, A; Sluis, CK van der; Bongers, RM,   +1 more
openaire   +3 more sources

Investigating the Impact of Training Protocols on Myoelectric Pattern Recognition Control in Upper-Limb Amputees

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Myoelectric control schemes, pivotal in the control of prosthetic limbs, are often developed and evaluated in ideal laboratory conditions. However, these controlled environments may not fully represent the diverse challenges users face in real-world ...
Elaheh Mohammadreza, Vinicius Prado da Fonseca, Xianta Jiang   +2 more
doaj   +2 more sources

Wavelet Packet Feature Assessment for High-density Myoelectric Pattern Recognition and Channel Selection toward Stroke Rehabilitation [PDF]

Frontiers in Neurology, 2016
This study presented wavelet packet feature assessment of neural control information in paretic upper-limb muscles of stroke survivors for myoelectric pattern recognition, taking advantage of high-resolution time-frequency representations of surface ...
Dongqing Wang, Xu Zhang, Xiaoping Gao, Xiang Chen, Ping Zhou, Ping Zhou   +5 more
doaj   +2 more sources

Myoelectric Pattern Recognition Performance Enhancement Using Nonlinear Features. [PDF]

Comput Intell Neurosci, 2022
The multichannel electrode array used for electromyogram (EMG) pattern recognition provides good performance, but it has a high cost, is computationally expensive, and is inconvenient to wear. Therefore, researchers try to use as few channels as possible while maintaining improved pattern recognition performance.
Islam MJ, Ahmad S, Haque F, Ibne Reaz MB, Bhuiyan MAS, Minhad KN, Islam MR.   +6 more
europepmc   +4 more sources

A Robust Sparse Representation Based Pattern Recognition Approach for Myoelectric Control

IEEE Access, 2018
Interferences in the form of white Gaussian noise (WGN) are inevitable during long-term electromyogram (EMG) recordings. Even with the aid of advanced signal denoising techniques, such an intermittent interference is hardly detected and attenuated in the
Yanjuan Geng, Yatao Ouyang, Oluwarotimi Williams Samuel, Shixiong Chen, Xiaoqiang Lu, Chuang Lin, Guanglin Li   +6 more
doaj   +3 more sources

Improving myoelectric pattern recognition robustness to electrode shift by changing interelectrode distance and electrode configuration. [PDF]

IEEE Trans Biomed Eng, 2012
Young AJ, Hargrove LJ, Kuiken TA.
europepmc   +2 more sources

Neurostimulation artifact removal for implantable sensors improves signal clarity and decoding of motor volition

Frontiers in Human Neuroscience, 2022
As the demand for prosthetic limbs with reliable and multi-functional control increases, recent advances in myoelectric pattern recognition and implanted sensors have proven considerably advantageous.
Eric J. Earley, Eric J. Earley, Anton Berneving, Anton Berneving, Jan Zbinden, Jan Zbinden, Max Ortiz-Catalan, Max Ortiz-Catalan, Max Ortiz-Catalan, Max Ortiz-Catalan   +9 more
doaj   +1 more source