Simultaneous Force Regression and Movement Classification of Fingers via Surface EMG within a Unified Bayesian Framework

Simultaneous Force Regression and Movement Classification of Fingers via Surface EMG within a Unified Bayesian Framework

This contribution presents a novel methodology for myolectric-based control using surface electromyographic (sEMG) signals recorded during finger movements. A multivariate Bayesian mixture of experts (MoE) model is introduced which provides a powerful method for modeling force regression at the fing...

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Bibliographic Details
Main Authors: Tara Baldacchino, William R. Jacobs, Sean R. Anderson, Keith Worden, Jennifer Rowson
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-02-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
sEMG signals
finger force regression
finger movement classification
variational Bayes
multivariate mixture of experts
prosthetic hand
Online Access:http://journal.frontiersin.org/article/10.3389/fbioe.2018.00013/full

Internet

http://journal.frontiersin.org/article/10.3389/fbioe.2018.00013/full

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