ArticleJournal of neuroengineering and rehabilitation2025
Individual muscle strengths in rehabilitation outcomes of distal radius fracture.
Article in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Effect of muscle atrophy on fracture healing: insights from a tibial musculoskeletal-finite element model.Biomechanics and modeling in mechanobiology · 2026Article
- Ergonomic posture breaks enhance solute transport in cartilage: a musculoskeletal-poroelastic modelling study.European journal of applied physiology · 2026Article
- Real-time biofeedback monitoring rehabilitation of distal radius fracture.Journal of neuroengineering and rehabilitation · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDistal radius fractures (DRFs) are common fracture types and elderly patients often struggle to achieve functional recovery, which could be overcome by precise rehabilitation. This study aims to develop an innovative approach for acquiring patient-specific musculoskeletal models to provide guidelines for therapists to tailor rehabilitation plans individually.
methodA wearable EMG detector (Myo armband) and a dynamometer (KDG grip strength tester, EH101) were used to collect EMG signals and grip forces from 20 volunteers at 0, 30, 50, 70, and 100 N, which were considered low-level gripping. The collected data was used to train neural networks to predict maximum grip force from low-level grip data only. Based on a novel scaling function, personalized models were scaled from a standard musculoskeletal model and were validated by comparing their results with experiments. Sequentially, the musculoskeletal forces of two volunteers with different muscle strengths (one strong in muscle strength and the other is weak, compared to baseline) were simulated under extension exercises to investigate the impact of individual muscle strengths on rehabilitation outcomes.
resultsThe trained model predicts the maximum grip force by EMG signals well. Based on the scaling function, the corresponding personalized musculoskeletal models can simulate grip forces that align well with experiment observations. The muscle loadings were also scaled proportionally to their scaling coefficients. However, the contact forces are not linear to the scaling coefficients. The healing outcome of weak individuals shows satisfactory improvement while that of strong individuals performs ordinarily.
conclusionThis study has successfully developed a convenient approach to detect the maximum grip strength of patients and verified the feasibility of scaling the musculoskeletal models. The non-linear relationship of contract forces to the scaling coefficients indicates the complexity of the musculoskeletal system. The healing outcomes from the case studies suggest that while adequate mechanical stimuli are beneficial, excessive or inappropriate stimuli can impede the healing process.
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