A Robust Parameterization of Human Gait Patterns Across Phase-Shifting Perturbations.

Area of Science:

• Biomechanics
• Robotics
• Human Motor Control

Background:

• Accurate quantification of human gait phase is difficult, especially with perturbations.
• Bipedal robots utilize mechanical phase variables for gait control, inspiring similar approaches for humans.
• Existing phase variable candidates lack robust validation for human gait analysis.

Purpose of the Study:

• To analytically derive an ideal, robust mechanical phase variable for human gait.
• To test the efficacy of the derived hip phase angle against time and other variables.
• To assess the hip phase angle's ability to represent gait perturbations and interlimb coordination.

Main Methods:

• Analytical derivation of a novel hip phase angle.
• Experimental perturbation of human gait using a motion platform.
• Statistical correlation analysis of joint trajectories and gait phase variables.

Main Results:

• The derived hip phase angle is provably monotonic and bounded throughout the gait cycle.
• Human joint trajectories correlated significantly higher (0.95+) with the hip phase angle than with time or alternative variables.
• The hip phase angle demonstrated superior parameterization of transient gait errors and interlimb phasing.

Conclusions:

• The hip phase angle offers a robust and accurate mechanical representation of human gait phase.
• This variable holds significant potential for advanced human gait analysis and control systems.
• Synchronization of ipsilateral hip phase angles during double support explains interlimb phasing effectively.