User adaptation in Myoelectric Man-Machine Interfaces

Volume: 7, Issue: 1
Published: Jun 30, 2017
Abstract
State of the art clinical hand prostheses are controlled in a simple and limited way that allows the activation of one function at a time. More advanced laboratory approaches, based on machine learning, offer a significant increase in functionality, but their clinical impact is limited, mainly due to lack of reliability. In this study, we analyse two conceptually different machine learning approaches, focusing on their robustness and performance...
Paper Details
Title
User adaptation in Myoelectric Man-Machine Interfaces
Published Date
Jun 30, 2017
Volume
7
Issue
1
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