Muscle synergy-informed neuromusculoskeletal modelling to estimate knee contact forces in children with cerebral...

Area of Science:

• Biomechanics
• Neurology
• Computational Modeling

Background:

• Cerebral palsy (CP) involves brain damage affecting muscle coordination and movement.
• Accurate estimation of joint moments and forces is crucial for tracking CP progression and planning interventions.
• Current EMG-informed models require numerous sensors, limiting clinical applicability.

Purpose of the Study:

• To develop and evaluate a muscle synergy-informed neuromusculoskeletal model for estimating joint moments and knee contact forces.
• To assess the model's efficacy using minimal electromyogram (EMG) sensors (3-4) in children with CP and typically developing (TD) children.
• To determine if this approach can simplify clinical biomechanical assessments.

Main Methods:

• Developed a novel neuromusculoskeletal model incorporating muscle synergies.
• Utilized EMG recordings from 3-4 muscles and an EMG database from TD children during walking.
• Estimated joint moments and knee contact forces in children with CP and TD children.

Main Results:

• The synergy-informed model accurately estimated knee contact forces, comparable to models using 13 EMG sensors.
• High R-squared values (0.95±0.01 for CP, 0.93±0.07 for TD) and low RMSE (0.40±0.14 BW for CP, 0.19±0.05 BW for TD) were achieved.
• The approach demonstrated effectiveness in both CP and TD children.

Conclusions:

• The muscle synergy-informed neuromusculoskeletal model enables accurate joint force estimation with minimal EMG sensors.
• This method facilitates rapid clinical evaluation of joint biomechanics in children with motor impairments.
• The approach holds potential for improving the management of cerebral palsy through accessible biomechanical analysis.