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[HTML][HTML] A review of myoelectric control for prosthetic hand manipulation
Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation.
Intuitive and intelligent myoelectric control can help amputees to regain upper limb function …
Intuitive and intelligent myoelectric control can help amputees to regain upper limb function …
[PDF][PDF] Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review
ABSTRACT A decade ago, a group of researchers from academia and industry identified a
dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis …
dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis …
Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture
recognition algorithms that can achieve high accuracy with limited complexity and latency. In …
recognition algorithms that can achieve high accuracy with limited complexity and latency. In …
Continuous motion intention prediction using sEMG for upper-limb rehabilitation: a systematic review of model-based and model-free approaches
Upper limb functional impairments persisting after stroke significantly affect patients' quality
of life. Precise adjustment of robotic assistance levels based on patients' motion intentions …
of life. Precise adjustment of robotic assistance levels based on patients' motion intentions …
Deep learning for robust decomposition of high-density surface EMG signals
Blind source separation (BSS) algorithms, such as gradient convolution kernel
compensation (gCKC), can efficiently and accurately decompose high-density surface …
compensation (gCKC), can efficiently and accurately decompose high-density surface …
Adaptive real-time identification of motor unit discharges from non-stationary high-density surface electromyographic signals
Objective: Estimation of the discharge pattern of motor units by electromyography (EMG)
decomposition has been applied for neurophysiologic investigations, clinical diagnosis, and …
decomposition has been applied for neurophysiologic investigations, clinical diagnosis, and …
A convolutional neural network to identify motor units from high-density surface electromyography signals in real time
Objectives. This paper aims to investigate the feasibility and the validity of applying deep
convolutional neural networks (CNN) to identify motor unit (MU) spike trains and estimate …
convolutional neural networks (CNN) to identify motor unit (MU) spike trains and estimate …
Simultaneous and proportional control of wrist and hand movements by decoding motor unit discharges in real time
Objective. Surface electromyography (EMG) decomposition techniques can be used to
establish human-machine interfacing (HMI), but most investigations are implemented offline …
establish human-machine interfacing (HMI), but most investigations are implemented offline …
Real-time hand gesture recognition by decoding motor unit discharges across multiple motor tasks from surface electromyography
Objective. Surface electromyography (EMG) decomposition techniques have been
developed to decode motor neuron activities non-invasively in the past decades, showing …
developed to decode motor neuron activities non-invasively in the past decades, showing …
Neural control of matched motor units during muscle shortening and lengthening at increasing velocities
Modulation of movement velocity is necessary during daily life tasks, work, and sports
activities. However, assessing motor unit behavior during muscle shortening and …
activities. However, assessing motor unit behavior during muscle shortening and …