Adaptation mechanism of interlimb coordination in human split-belt treadmill walking through learning of foot contact timing: a robotics study

Abstract

Human walking behaviour adaptation strategies have previously been examined using split-belt treadmills, which have two parallel independently controlled belts. In such human split-belt treadmill walking, two types of adaptations have been identified: early and late. Early-type adaptations appear as rapid changes in interlimb and intralimb coordination activities when the belt speeds of the treadmill change between tied (same speed for both belts) and split-belt (different speeds for each belt) configurations. By contrast, late-type adaptations occur after the early-type adaptations as a gradual change and only involve interlimb coordination. Furthermore, interlimb coordination shows after-effects that are related to these adaptations. It has been suggested that these adaptations are governed primarily by the spinal cord and cerebellum, but the underlying mechanism remains unclear. Because various physiological findings suggest that foot contact timing is crucial to adaptive locomotion, this paper reports on the development of a two-layered control model for walking composed of spinal and cerebellar models, and on its use as the focus of our control model. The spinal model generates rhythmic motor commands using an oscillator network based on a central pattern generator and modulates the commands formulated in immediate response to foot contact, while the cerebellar model modifies motor commands through learning based on error information related to differences between the predicted and actual foot contact timings of each leg. We investigated adaptive behaviour and its mechanism by split-belt treadmill walking experiments using both computer simulations and an experimental bipedal robot. Our results showed that the robot exhibited rapid changes in interlimb and intralimb coordination that were similar to the early-type adaptations observed in humans. In addition, despite the lack of direct interlimb coordination control, gradual changes and after-effects in the interlimb coordination appeared in a manner that was similar to the late-type adaptations and after-effects observed in humans. The adaptation results of the robot were then evaluated in comparison with human split-belt treadmill walking, and the adaptation mechanism was clarified from a dynamic viewpoint.

Do kinematic metrics of walking balance adapt to perturbed optical flow?

“…First, we used moving averages (e.g., step width and length) or analyzed bins of time-averaged data (i.e., step width and length variabilities) and were thus by design limited in our temporal resolution to identify changes that may have occurred on a step by step basis. As a strength of our approach, we used moving averages to quantify time-dependent changes in step width and step length over the course of each perturbation trial separately from time-dependent changes in the magnitude of their step-to-step fluctuations (i.e., step width variability and step length variability), a common practice in studies of locomotor adaptation (Bruijn et al, 2012; Fujiki et al, 2015; Malone & Bastian, 2010; Noel et al, 2009). Indeed, our primary objective was to investigate adaptation to optical flow perturbations that may occur over the course of several minutes of walking.…”

“…We computed step lengths (SL) using the relative anterior-posterior positions of successive heel markers at 20% of the gait cycle plus the treadmill belt translation during each step. To test for adaptation in SW and SL over the trial durations, rather than step to step variations, we used a moving average with a window of 30 steps to remove short term fluctuations (Bruijn, Impe, Duysens, & Swinnen, 2012; Fujiki et al, 2015; Malone & Bastian, 2010; Noel, Fortin, & Bouyer, 2009). Using the original time series, we calculated step width and length variabilities (SWV and SLV, respectively) as the standard deviation of SW and SL over steps occurring in 60 s bins.…”

Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review

“…This shows only early adaptation when the environment changes. These figures were modified from Fujiki et al ( 2015 ).…”

“…Otoda et al ( 2009 ) modeled the stepping reflex to modulate the touchdown angle of the swing leg and introduced the adjustment of proportional control gain at the hip joint of the stance leg as the cerebellar function producing split-belt treadmill walking of a two-dimensional biped robot, although they did not use a CPG model with adaptation. In contrast, Fujiki et al ( 2015 ) incorporated a cerebellar learning model into the spinal CPG model (Figure 12B ). The CPG model was composed of simple phase oscillators with sensory reflex by local foot contact information and was used in Fujiki et al ( 2013b ) as mentioned above.…”

“… Pitching moment change due to belt-speed change (A–E) through sensory reflex and learning regarding foot contact timing. These figures were modified from Fujiki et al ( 2015 ). …”