Zhang, C, Ai, Q, Meng, W et al. (1 more author) (2017) A Subject-Specific EMG-Driven Musculoskeletal Model for the Estimation of Moments in Ankle Plantar-Dorsiflexion Movement. In: Lecture Notes in Computer Science. International Conference on Neural Information Processing: ICONIP 2017, 14-18 Nov 2017, Guangzhou, China. Springer, Cham , pp. 685-693. ISBN 978-3-319-70092-2
Abstract
In traditional rehabilitation process, ankle movement ability is only qualitatively estimated by its motion performance, however, its movement is actually achieved by the forces acting on the joints produced by muscles contraction. In this paper, the musculoskeletal model is introduced to provide a more physiologic method for quantitative muscle forces and muscle moments estimation during rehabilitation. This paper focuses on the modeling method of musculoskeletal model using electromyography (EMG) and angle signals for ankle plantar-dorsiflexion (P-DF) which is very important in gait rehabilitation and foot prosthesis control. Due to the skeletal morphology differences among people, a subject-specific geometry model is proposed to realize the estimation of muscle lengths and muscle contraction force arms. Based on the principle of forward and inverse dynamics, difference evolutionary (DE) algorithm is used to adjust individual parameters of the whole model, realizing subject-specific parameters optimization. Results from five healthy subjects show the inverse dynamics joint moments are well predicted with an average correlation coefficient of 94.21% and the normalized RMSE of 12.17%. The proposed model provides a good way to estimate muscle moments during movement tasks.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © Springer International Publishing AG 2017. This is an author produced version of a paper published in Lecture Notes in Computer Science. The final publication is available at Springer via 10.1007/978-3-319-70093-9_73. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | EMG signals; Musculoskeletal model; Ankle plantar-dorsiflexion; Joint moment |
Dates: |
|
Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Dec 2017 16:48 |
Last Modified: | 21 Dec 2017 21:00 |
Status: | Published |
Publisher: | Springer, Cham |
Identification Number: | 10.1007/978-3-319-70093-9_73 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:124913 |