[HTML][HTML] Robust myoelectric pattern recognition methods for reducing users' calibration burden: challenges and future
Myoelectric pattern recognition (MPR) has evolved into a sophisticated technology widely
employed in controlling myoelectric interface (MI) devices like prosthetic and orthotic robots …
employed in controlling myoelectric interface (MI) devices like prosthetic and orthotic robots …
[HTML][HTML] Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics
Surface electromyography (sEMG) signals have been used for advanced prosthetics control,
hand-gesture recognition (HGR), and more recently as a novel biometric trait. For these …
hand-gesture recognition (HGR), and more recently as a novel biometric trait. For these …
Improving the robustness and adaptability of sEMG-based pattern recognition using deep domain adaptation
P Shi, X Zhang, W Li, H Yu - IEEE journal of biomedical and …, 2022 - ieeexplore.ieee.org
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 …
quality of daily life of amputees. However, the lack of robustness and adaptability hinders its …
Wearable Sensors for Motion and Electrophysiological Signal Tracking in XR
Extended-reality (XR) technology is transforming digital interaction by blending virtual
elements with the physical world via portable devices. Accurate body movement recognition …
elements with the physical world via portable devices. Accurate body movement recognition …
Multiscale temporal self-attention and dynamical graph convolution hybrid network for EEG-based stereogram recognition
L Shen, M Sun, Q Li, B Li, Z Pan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Stereopsis is the ability of human beings to get the 3D perception on real scenarios. The
conventional stereopsis measurement is based on subjective judgment for stereograms …
conventional stereopsis measurement is based on subjective judgment for stereograms …
Handwritten digits recognition from sEMG: Electrodes location and feature selection
Despite hand gesture recognition is a widely investigated field, the design of myoelectric
architectures for detecting finer motor task, like the handwriting, is less studied. However …
architectures for detecting finer motor task, like the handwriting, is less studied. However …
[HTML][HTML] Serious games are not serious enough for myoelectric prosthetics
Serious games show a lot of potential for use in movement rehabilitation (eg, after a stroke,
injury to the spinal cord, or limb loss). However, the nature of this research leads to diversity …
injury to the spinal cord, or limb loss). However, the nature of this research leads to diversity …
[HTML][HTML] Optimizing the performance of convolutional neural network for enhanced gesture recognition using sEMG
Deep neural networks (DNNs) have demonstrated higher performance results when
compared to traditional approaches for implementing robust myoelectric control (MEC) …
compared to traditional approaches for implementing robust myoelectric control (MEC) …
EMG-based cross-subject silent speech recognition using conditional domain adversarial network
Y Zhang, H Cai, J Wu, L Xie, M Xu… - … on Cognitive and …, 2023 - ieeexplore.ieee.org
Machine learning techniques have achieved great success in electromyography (EMG)
decoding, but EMG-based cross-subject silent speech recognition (SSR) received less …
decoding, but EMG-based cross-subject silent speech recognition (SSR) received less …
Transfer learning on electromyography (EMG) tasks: approaches and beyond
Machine learning on electromyography (EMG) has recently achieved remarkable success
on various tasks, while such success relies heavily on the assumption that the training and …
on various tasks, while such success relies heavily on the assumption that the training and …