Consistency of Muscle Synergies Extracted via Higher-Order Tensor Decomposition Towards Myoelectric Control

Ahmed Ebied*, Eli Kinney-Lang, Javier Escudero

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, muscle synergies have been proposed for proportional myoelectric control. Synergies were extracted using matrix factorisation techniques (mainly non-negative matrix factorisation, NMF), which requires identification of synergies to tasks or movements. In addition, NMF methods were viable only with a task dimension of 2 degrees of freedoms (DoFs). Here, the potential use of a higher-order tensor model for myoelectric control is explored. We assess the ability of a constrained Tucker tensor decomposition (consTD) method to estimate consistent synergies when the task dimensionality is increased up to 3-DoFs. Synergies extracted from 3rd-order tensor of 1 and 3 DoFs were compared. Results showed that muscle synergies extracted via consTD were consistent with the increase of task-dimension. Hence, these results support the consideration of proportional 3-DoF myoelectric control based on tensor decompositions.

Original languageEnglish
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherIEEE Computer Society
Pages315-318
Number of pages4
ISBN (Electronic)9781538679210
DOIs
Publication statusPublished - 20 May 2019
Event9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
Duration: 20 Mar 201923 Mar 2019

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2019-March
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference9th International IEEE EMBS Conference on Neural Engineering, NER 2019
CountryUnited States
CitySan Francisco
Period20/03/1923/03/19

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