Smooth changes in the EMG patterns during gait transitions under body weight unloading

Area of Science:

• Human locomotion biomechanics
• Neuroscience of movement

Background:

• Human gait transitions typically involve abrupt changes in muscle activity.
• Different gaits are hypothesized to be controlled by distinct neuronal networks.

Purpose of the Study:

• To investigate the effect of simulated hypogravity on human gait transitions.
• To explore the underlying neural control mechanisms during gait changes under varying gravity conditions.

Main Methods:

• Electromyography (EMG) of leg muscles recorded during treadmill speed changes.
• Simulated body weight unloading to mimic different gravity levels.
• Neuromechanical modeling using a half-center oscillator model.

Main Results:

• Gait transitions were gradual, lacking abrupt EMG changes, at simulated gravity levels below 0.4 g.
• The abruptness of gait transitions at 1 g was predictable by model parameters, unlike in low gravity.
• Model parameters were similar for walking and running gaits at low gravity levels.

Conclusions:

• Hypogravity alters gait transition dynamics, leading to smoother changes between walking and running.
• Findings support a continuous shift in central pattern generator states rather than activation of separate networks for each gait.