Muscle Activation Estimation by Optimizing the Musculoskeletal Model for Personalized Strength and Conditioning Training
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866909502848106496 |
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| author | Wu, Xi Li, Chenzui Zou, Kehan Xi, Ning Chen, Fei |
| author_facet | Wu, Xi Li, Chenzui Zou, Kehan Xi, Ning Chen, Fei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_13760 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Muscle Activation Estimation by Optimizing the Musculoskeletal Model for Personalized Strength and Conditioning Training Wu, Xi Li, Chenzui Zou, Kehan Xi, Ning Chen, Fei Medical Physics Robotics 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. |
| title | Muscle Activation Estimation by Optimizing the Musculoskeletal Model for Personalized Strength and Conditioning Training |
| topic | Medical Physics Robotics |
| url | https://arxiv.org/abs/2502.13760 |