SynergyFF: A single shooting method for simulating crouch gait using muscle synergy feedforward control as a CPG

Area of Science:

• Biomechanics and Motor Control
• Computational Neuroscience
• Robotics

Background:

• Central pattern generators (CPGs) are crucial for motor patterns, potentially involving muscle synergy.
• Previous predictive simulations struggled to model specific gait pathologies like stiff-knee and crouch gait, especially with plantarflexor weakness.
• Understanding the relationship between muscle deficiencies and abnormal gaits is essential for developing effective interventions.

Purpose of the Study:

• To develop and evaluate a novel predictive simulation method for gait analysis.
• To investigate the role of muscle synergy in the central pattern generator (CPG) framework.
• To successfully simulate previously challenging abnormal gaits, such as stiff-knee and crouch gait.

Main Methods:

• A 9-degree-of-freedom musculoskeletal model with 14 Hill-type actuators was trained to walk.
• A single shooting predictive simulation method, termed SynergyFF, was developed, utilizing muscle-synergy feedforward control as the CPG.
• Controller parameters were optimized against an objective function to achieve realistic walking simulations.

Main Results:

• The SynergyFF model successfully simulated crouch gait, which was not achievable with classical reflex-based models.
• The model also accurately simulated calcaneal and stiff-knee gaits.
• Enhanced modeling of the knee flexion moment was a key factor in the success of these simulations.

Conclusions:

• The CPG framework incorporating the muscle synergy hypothesis can generate realistic simulations of abnormal gaits.
• Muscle synergy plays a critical role in the generation of crouch gait within this framework.
• These findings provide evidence supporting the existence of CPGs and the muscle synergy hypothesis in motor control.