Advancements in Understanding Spasticity: A Neuromusculoskeletal Modeling Perspective.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Science

Background:

• Spasticity, resulting from upper motor neuron lesions, presents diagnostic challenges due to its complex neural and mechanical components.
• Current assessment tools, such as the Modified Ashworth and Tardieu Scales, offer limited, subjective insights into spasticity's dynamic nature.
• Neuromusculoskeletal (NMS) modeling provides a quantitative, objective approach by integrating biomechanical and reflex properties.

Purpose of the Study:

• To conduct a scoping review of advancements in NMS modeling for spasticity assessment.
• To compare different modeling approaches (mechanical, neurological, integrated) and their clinical applications.
• To identify barriers and future directions for translating NMS modeling into clinical practice.

Main Methods:

• Systematic literature search for studies on NMS modeling of spasticity.
• Categorization of models based on mechanical, neurological, or integrated approaches.
• Analysis of model applications in neurological conditions (e.g., cerebral palsy, stroke).

Main Results:

• NMS modeling offers objective, quantitative data on spasticity, surpassing traditional scales.
• Integrated models combining biomechanics and neural dynamics show promise for comprehensive assessment.
• Applications demonstrated in cerebral palsy and stroke, highlighting potential for personalized treatment.

Conclusions:

• NMS modeling represents a significant advancement for objective spasticity assessment and personalized treatment strategies.
• Overcoming computational and regulatory hurdles is crucial for clinical adoption.
• Future research should focus on real-time simulations and machine learning integration for enhanced clinical utility.