Background and Objective: Human walking is governed by the interaction between central pattern generators (CPGs), reflexes, and the vestibular system. While single-layer CPG models like the Unit Burst Generator (UBG) are commonly used in simulations, they couple oscillation frequency and amplitude, limiting control of gait velocity. This study evaluates a two-layer UBG (TLU) architecture, which decouples these properties, to determine its efficacy in producing realistic human gait and its ability to control gait velocity.

Method: A 2D musculoskeletal model (9 DOF, 18 muscles) was controlled by the UBG or TLU architecture during gait, integrated with muscle reflexes and vestibular feedback. Additionally, velocity control was assessed by optimizing specific CPG parameters to increase walking speed.

Results: Both controllers produced stable, physiologically plausible gait that aligned well with normative data. Neural analysis showed that while reflexes mainly controlled lower leg muscles, the CPG was essential for the loading response in muscles spanning the knee and hip joints. In the velocity control, the TLU model could reach higher gait velocities with fewer optimization parameters compared to the UBG.

Conclusion: The CPG effectively coordinates with muscle reflexes and vestibular feedback to produce human-like gait, complementing where the other neural control mechanisms fall short. The TLU provides a more efficient mechanism for gait modulation than the UBG by separating frequency and amplitude control.