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Muscle Activation Estimation by Optimizing the Musculoskeletal Model for Personalized Strength and Conditioning Training

Xi Wu, Chenzui Li, Kehan Zou, Ning Xi, Fei Chen

TL;DR

This study develops a whole-body musculoskeletal model for strength and conditioning training and calibrates relevant muscle parameters with an electromyography-based optimization method and estimates muscle activation to analyze the performance of exercises.

Abstract

Musculoskeletal models are pivotal in the domains of rehabilitation and resistance training to analyze muscle conditions. However, individual variability in musculoskeletal parameters and the immeasurability of some internal biomechanical variables pose significant obstacles to accurate personalized modelling. Furthermore, muscle activation estimation can be challenging due to the inherent redundancy of the musculoskeletal system, where multiple muscles drive a single joint. This study develops a whole-body musculoskeletal model for strength and conditioning training and calibrates relevant muscle parameters with an electromyography-based optimization method. By utilizing the personalized musculoskeletal model, muscle activation can be subsequently estimated to analyze the performance of exercises. Bench press and deadlift are chosen for experimental verification to affirm the efficacy of this approach.

Muscle Activation Estimation by Optimizing the Musculoskeletal Model for Personalized Strength and Conditioning Training

TL;DR

This study develops a whole-body musculoskeletal model for strength and conditioning training and calibrates relevant muscle parameters with an electromyography-based optimization method and estimates muscle activation to analyze the performance of exercises.

Abstract

Musculoskeletal models are pivotal in the domains of rehabilitation and resistance training to analyze muscle conditions. However, individual variability in musculoskeletal parameters and the immeasurability of some internal biomechanical variables pose significant obstacles to accurate personalized modelling. Furthermore, muscle activation estimation can be challenging due to the inherent redundancy of the musculoskeletal system, where multiple muscles drive a single joint. This study develops a whole-body musculoskeletal model for strength and conditioning training and calibrates relevant muscle parameters with an electromyography-based optimization method. By utilizing the personalized musculoskeletal model, muscle activation can be subsequently estimated to analyze the performance of exercises. Bench press and deadlift are chosen for experimental verification to affirm the efficacy of this approach.

Paper Structure

This paper contains 10 sections, 12 equations, 7 figures, 2 tables.

Figures (7)

  • Figure 1: Common resistance training actions and their simulation.
  • Figure 2: The overall framework scheme. Data Collection: Human information in strength and conditioning training is recorded by various sensors. Personalized Muscle Activation Estimation: A whole-body musculoskeletal model is employed to perform inverse dynamics and muscle analysis using the acquired human body information. Subject-specific muscle parameter calibration is conducted in conjunction with muscle activation distributions to obtain personalized muscle models, which are then used to estimate muscle activation on new data.
  • Figure 3: Structure of Hill-type muscle model.
  • Figure 4: Illustration of the Maximum Voluntary Isometric Contraction tests.
  • Figure 5: Optimization results of bench press and deadlift during musculoskeletal model personalization.
  • ...and 2 more figures