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The LET Procedure for Prosthetic Myocontrol: Towards Multi-DOF Control Using Single-DOF Activations

Nowak, Markus and Castellini, Claudio (2016) The LET Procedure for Prosthetic Myocontrol: Towards Multi-DOF Control Using Single-DOF Activations. PLoS One, 11 (9), pp. 1-20. Public Library of Science (PLoS). DOI: 10.1371/journal.pone.0161678 ISSN 1932-6203

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Abstract

Simultaneous and proportional myocontrol of dexterous hand prostheses is to a large extent still an open problem. With the advent of commercially and clinically available multi-fingered hand prostheses there are now more independent degrees of freedom (DOFs) in prostheses than can be effectively controlled using surface electromyography (sEMG), the current standard human-machine interface for hand amputees. In particular, it is uncertain, whether several DOFs can be controlled simultaneously and proportionally by exclusively calibrating the intended activation of single DOFs. The problem is currently solved by training on all required combinations. However, as the number of available DOFs grows, this approach becomes overly long and poses a high cognitive burden on the subject. In this paper we present a novel approach to overcome this problem. Multi-DOF activations are artificially modelled from single-DOF ones using a simple linear combination of sEMG signals, which are then added to the training set. This procedure, which we named LET (Linearly Enhanced Training), provides an augmented data set to any machine-learning-based intent detection system. In two experiments involving intact subjects, one offline and one online, we trained a standard machine learning approach using the full data set containing single- and multi-DOF activations as well as using the LET-augmented data set in order to evaluate the performance of the LET procedure. The results indicate that the machine trained on the latter data set obtains worse results in the offline experiment compared to the full data set. However, the online implementation enables the user to perform multi-DOF tasks with almost the same precision as single-DOF tasks without the need of explicitly training multi-DOF activations. Moreover, the parameters involved in the system are statistically uniform across subjects.

Item URL in elib:https://elib.dlr.de/106070/
Document Type:Article
Title:The LET Procedure for Prosthetic Myocontrol: Towards Multi-DOF Control Using Single-DOF Activations
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Nowak, Markusmarkus.nowak (at) dlr.dehttps://orcid.org/0000-0002-0840-5155
Castellini, ClaudioClaudio.Castellini (at) dlr.dehttps://orcid.org/0000-0002-7346-2180
Date:2016
Journal or Publication Title:PLoS One
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:11
DOI :10.1371/journal.pone.0161678
Page Range:pp. 1-20
Publisher:Public Library of Science (PLoS)
ISSN:1932-6203
Status:Published
Keywords:Prosthetics, machine learning, rehabilitation robotics, assistive robotics, electromyography, EMG
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Intelligente Mobilität
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Deposited By: Castellini, Dr. Claudio
Deposited On:04 Nov 2016 13:10
Last Modified:08 Mar 2018 18:49

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