Abstract
The 1/f-like gait cycle variability, characterized by temporal changes in stride-time intervals during steady-state human walking, is a well-documented gait characteristic. Such gait fractality is apparent in healthy young adults, but tends to disappear in the elderly and patients with neurological diseases. However, mechanisms that give rise to gait fractality have yet to be fully clarified. We aimed to provide novel insights into neuro-mechanical mechanisms of gait fractality, based on a numerical simulation model of biped walking. A previously developed heel-toe footed, seven-rigid-link biped model with human-like body parameters in the sagittal plane was implemented and expanded. It has been shown that the gait model, stabilized rigidly by means of impedance control with large values of proportional (P) and derivative (D) gains for a linear feedback controller, is destabilized only in a low-dimensional eigenspace, as P and D decrease below and even far below critical values. Such low-dimensional linear instability can be compensated by impulsive, phase-dependent actions of nonlinear controllers (phase resetting and intermittent controllers), leading to the flexible walking with joint impedance in the model being as small as that in humans. Here, we added white noise to the model to examine P-value-dependent stochastic dynamics of the model for small D-values. The simulation results demonstrated that introduction of the nonlinear controllers in the model determined the fractal features of gait for a wide range of the P-values, provided that the model operates near the edge of stability. In other words, neither the model stabilized only by pure impedance control even at the edge of linear stability, nor the model stabilized by specific nonlinear controllers, but with P-values far inside the stability region, could induce gait fractality. Although only limited types of controllers were examined, we suggest that the impulsive nonlinear controllers and criticality could be major mechanisms for the genesis of gait fractality.
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Notes
Note that the trunk-inclination angle is not a part of the joint angle trajectories. One can imagine a walking toy-robot with a trunk and legs, whose joint angles change exactly in accordance with prescribed profiles. Even in this case, the toy-robot can exhibit a variety of gait dynamics, including falls, accompanied with different time-profiles in the inclination angle of the trunk of the robot.
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The authors thank Dr. Matija Milosevic for reading the manuscript.
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Fu, C., Suzuki, Y., Morasso, P. et al. Phase resetting and intermittent control at the edge of stability in a simple biped model generates 1/f-like gait cycle variability. Biol Cybern 114, 95–111 (2020). https://doi.org/10.1007/s00422-020-00816-y
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DOI: https://doi.org/10.1007/s00422-020-00816-y