Applied Bionics and Biomechanics (Jan 2021)

An Improved EMG-Driven Neuromusculoskeletal Model for Elbow Joint Muscle Torque Estimation

  • Bingshan Hu,
  • Haoran Tao,
  • Hongrun Lu,
  • Xiangxiang Zhao,
  • Jiantao Yang,
  • Hongliu Yu

DOI
https://doi.org/10.1155/2021/1985741
Journal volume & issue
Vol. 2021

Abstract

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The accurate measurement of human joint torque is one of the research hotspots in the field of biomechanics. However, due to the complexity of human structure and muscle coordination in the process of movement, it is difficult to measure the torque of human joints in vivo directly. Based on the traditional elbow double-muscle musculoskeletal model, an improved elbow neuromusculoskeletal model is proposed to predict elbow muscle torque in this paper. The number of muscles in the improved model is more complete, and the geometric model is more in line with the physiological structure of the elbow. The simulation results show that the prediction results of the model are more accurate than those of the traditional double-muscle model. Compared with the elbow muscle torque simulated by OpenSim software, the Pearson correlation coefficient of the two shows a very strong correlation. One-way analysis of variance (ANOVA) showed no significant difference, indicating that the improved elbow neuromusculoskeletal model established in this paper can well predict elbow muscle torque.