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

TL;DR

This paper presents a personalized musculoskeletal model calibrated with electromyography data to accurately estimate muscle activation during exercises like bench press and deadlift, enhancing strength and conditioning training analysis.

Contribution

It introduces a novel electromyography-based optimization method for calibrating personalized musculoskeletal models, improving muscle activation estimation accuracy.

Findings

Effective calibration of the model with EMG data.

Accurate muscle activation estimation during exercises.

Potential for personalized training optimization.

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.