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The Neuromusculoskeletal Modeling Pipeline: MATLAB-based model personalization and treatment optimization
Claire V Hammond1, Spencer T Williams1, Marleny M Vega1
1Department of Mechanical Engineering, Rice University, Houston, TX, USA.
Journal of Neuroengineering and Rehabilitation
|May 18, 2025
Summary
The Neuromusculoskeletal Modeling (NMSM) Pipeline personalizes patient models for tailored treatments. This computational approach optimizes rehabilitation strategies, improving functional outcomes for individuals with neuromusculoskeletal injuries.
Area of Science:
- Computational biomechanics and musculoskeletal modeling
- Rehabilitation engineering and personalized medicine
Background:
- Neuromusculoskeletal injuries impact a significant portion of the U.S. adult population, leading to suboptimal outcomes with standardized treatments.
- Existing computational models show promise for personalized treatments but face challenges in clinical translation.
- A gap exists between fundamental research and clinical application for individualized neuromusculoskeletal rehabilitation.
Purpose of the Study:
- Introduce the Neuromusculoskeletal Modeling (NMSM) Pipeline, a software suite designed to bridge the gap between research and clinical application.
- Facilitate the computational design of individualized treatments for neuromusculoskeletal impairments using personalized models and predictive simulations.
- Demonstrate the pipeline's utility through a use case for optimizing walking function in a post-stroke individual.
Main Methods:
- The NMSM Pipeline comprises two MATLAB-based toolsets: Model Personalization and Treatment Optimization, integrated with OpenSim.
- Model Personalization tools customize joint, muscle-tendon, neural control, and foot-ground contact models.
- Treatment Optimization utilizes personalized models and optimal control methods to predict and optimize functional outcomes for various interventions.
Main Results:
- A personalized neuromusculoskeletal model was developed for a post-stroke subject using experimental walking data.
- The Treatment Optimization tool predicted that modifying muscle synergy recruitment could increase walking speed by 60% without increasing metabolic cost.
- This demonstrates the potential for predictive simulation in designing personalized rehabilitation strategies.
Conclusions:
- The NMSM Pipeline enables the development of personalized neuromusculoskeletal models for individual patients.
- Predictive simulations using the pipeline can guide the design of personalized treatments to maximize functional recovery.
- This approach holds significant promise for improving rehabilitation outcomes in individuals with neuromusculoskeletal impairments.
