TY - GEN
T1 - Consistency of Muscle Synergies Extracted via Higher-Order Tensor Decomposition Towards Myoelectric Control
AU - Ebied, Ahmed
AU - Kinney-Lang, Eli
AU - Escudero, Javier
N1 - Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/5/20
Y1 - 2019/5/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85066745771&partnerID=8YFLogxK
U2 - 10.1109/NER.2019.8717076
DO - 10.1109/NER.2019.8717076
M3 - Conference contribution
AN - SCOPUS:85066745771
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 315
EP - 318
BT - 9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PB - IEEE Computer Society
T2 - 9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Y2 - 20 March 2019 through 23 March 2019
ER -