Integrating computer vision to prosthetic hand control with sEMG: Preliminary results in grasp classification

Integrating computer vision to prosthetic hand control with sEMG: Preliminary results in grasp classification

The myoelectric prosthesis is a promising tool to restore the hand abilities of amputees, but the classification accuracy of surface electromyography (sEMG) is not high enough for real-time application. Researchers proposed integrating sEMG signals with another feature that is not affected by amputa...

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Bibliographic Details
Main Authors: Shuo Wang, Jingjing Zheng, Ziwei Huang, Xiaoqin Zhang, Vinicius Prado da Fonseca, Bin Zheng, Xianta Jiang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Robotics and AI
Subjects:
myoelectric prosthesis
computer vision
sEMG
grasp classification
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2022.948238/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2022.948238/full

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