A Subject-Specific EMG-Driven Musculoskeletal Model for the Estimation of Moments in Ankle Plantar-Dorsiflexion Movement

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10637)

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.

Keywords

EMG signals Musculoskeletal model Ankle plantar-dorsiflexion Joint moment 

Notes

Acknowledgments

Research supported by The Excellent Dissertation Cultivation Funds of Wuhan University of Technology with No. 2016-YS-062 and National Natural Science Foundation of China under grants Nos. 51475342 and 61401318.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Congsheng Zhang
    • 1
    • 2
  • Qingsong Ai
    • 1
    • 2
  • Wei Meng
    • 1
    • 2
  • Jiwei Hu
    • 1
    • 2
  1. 1.School of Information EngineeringWuhan University of TechnologyWuhanChina
  2. 2.Key Laboratory of Fiber Optic Sensing Technology and Information ProcessingWuhan University of Technology, Ministry of EducationWuhanChina

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