ArticleFrontiers in neurorobotics2022
A CW-CNN regression model-based real-time system for virtual hand control.
Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Facial expression recognition through muscle synergies and estimation of facial keypoint displacements through a skin-musculoskeletal model using facial sEMG signals.Frontiers in bioengineering and biotechnology · 2025Article
- Enhancing neuroprosthesis calibration: the advantage of integrating prior training over exclusive use of new data.Journal of neural engineering · 2024Article
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Authors and funding
5 authors.
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Abstract
For upper limb amputees, wearing a myoelectric prosthetic hand is the only way for them to continue normal life. Even until now, the proposal of a high-precision and natural performance real-time control system based on surface electromyography (sEMG) signals is still challenging. Researchers have proposed many strategies for motion classification or regression prediction tasks based on sEMG signals. However, most of them have been limited to offline analysis only. There are even few papers on real-time control based on deep learning models, almost all of which are about motion classification. Rare studies tried to use deep learning-based regression models in real-time control systems for multi-joint angle estimation
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Registered trials
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