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[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 …
A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation
Post-surgical treatments of the human throat often require continuous monitoring of diverse
vital and muscle activities. However, wireless, continuous monitoring and analysis of these …
vital and muscle activities. However, wireless, continuous monitoring and analysis of these …
Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals
M Montazerin, E Rahimian, F Naderkhani… - Scientific reports, 2023 - nature.com
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 …
A myoelectric digital twin for fast and realistic modelling in deep learning
K Maksymenko, AK Clarke, I Mendez Guerra… - Nature …, 2023 - nature.com
Muscle electrophysiology has emerged as a powerful tool to drive human machine
interfaces, with many new recent applications outside the traditional clinical domains, such …
interfaces, with many new recent applications outside the traditional clinical domains, such …
The extraction of neural strategies from the surface EMG: 2004–2024
This review follows two previous papers [Farina et al. Appl Physiol (1985) 96: 1486–1495,
2004; Farina et al. J Appl Physiol (1985) 117: 1215–1230, 2014] in which we reflected on …
2004; Farina et al. J Appl Physiol (1985) 117: 1215–1230, 2014] in which we reflected on …
FS-HGR: Few-shot learning for hand gesture recognition via electromyography
E Rahimian, S Zabihi, A Asif, D Farina… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their
widespread applications in human-machine interfaces. DNNs have been recently used for …
widespread applications in human-machine interfaces. DNNs have been recently used for …
Noninvasive neural interfacing with wearable muscle sensors: Combining convolutive blind source separation methods and deep learning techniques for neural …
Neural interfacing is essential for advancing our fundamental understanding of movement
neurophysiology and for develo** human-machine interaction systems. This can be …
neurophysiology and for develo** human-machine interaction systems. This can be …
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 …
Gait phases recognition based on lower limb sEMG signals using LDA-PSO-LSTM algorithm
S Cai, D Chen, B Fan, M Du, G Bao, G Li - Biomedical Signal Processing …, 2023 - Elsevier
Gait phases are widely used in exoskeleton movement control. Surface electromyography
(sEMG) is predictive and plays an important role in gait phase recognition. The purpose of …
(sEMG) is predictive and plays an important role in gait phase recognition. The purpose of …
Trahgr: Transformer for hand gesture recognition via electromyography
S Zabihi, E Rahimian, A Asif… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning-based Hand Gesture Recognition (HGR) via surface Electromyogram (sEMG)
signals have recently shown considerable potential for development of advanced …
signals have recently shown considerable potential for development of advanced …