Multimodal fusion of EMG and vision for human grasp intent inference in prosthetic hand control

Multimodal fusion of EMG and vision for human grasp intent inference in prosthetic hand control

Objective: For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological signals such as electromyography (EMG) are prone to yielding poor inference outcomes due to motion artifacts, muscle fatig...

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Bibliographic Details
Main Authors: Mehrshad Zandigohar, Mo Han, Mohammadreza Sharif, Sezen Yağmur Günay, Mariusz P. Furmanek, Mathew Yarossi, Paolo Bonato, Cagdas Onal, Taşkın Padır, Deniz Erdoğmuş, Gunar Schirner
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Robotics and AI
Subjects:
dataset
EMG
grasp detection
neural networks
robotic prosthetic hand
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2024.1312554/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2024.1312554/full

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