Assessing Walking Stability Based on Whole-Body Movement Derived from a Depth-Sensing Camera

Abstract

Stability during walking is considered a crucial aspect of assessing gait ability. The current study aimed to assess walking stability by applying principal component analysis (PCA) to decompose three-dimensional (3D) whole-body kinematic data of 104 healthy young adults (21.9 ± 3.5 years, 54 females) derived from a depth-sensing camera into a set of movement components/synergies called “principal movements” (PMs), forming together to achieve the task goal. The effect of sex as the focus area was tested on three PCA-based variables computed for each PM: the relative explained variance (rVAR) as a measure of the composition of movement structures; the largest Lyapunov exponent (LyE) as a measure of variability; and the number of zero-crossings (N) as a measure of the tightness of neuromuscular control. The results show that the sex effects appear in the specific PMs. Specifically, in PM1, resembling the swing-phase movement, females have greater LyE (p = 0.013) and N (p = 0.017) values than males. Moreover, in PM3, representing the mid-stance-phase movement, females have smaller rVAR (p = 0.020) but greater N (p = 0.008) values than males. These empirical findings suggest that the inherent sex differences in walking stability should be considered in assessing and training locomotion.

Walking Stability and Risk of Falls

“…Each PP k ( ) was normalized to an individual’s walking speed [ 23 , 37 ]. Then, the participant-specific largest Lyapunov exponent (LyE) of PP 1–5 ( t ) or PP k _LyE was used to investigate walking stability by computing the rate of divergence of close trajectories in state space (i.e., the ability of the motor system to attenuate small perturbations revealed by the divergence of the trajectories in state space) [ 10 , 16 , 23 , 38 ].…”

“…A greater PP k _LyE value indicates the inability of the motor system to reduce infinitesimal perturbations [ 13 ], resulting in a greater divergence of state space trajectories. In other words, a higher PP k _LyE value reflects a lower individual’s walking stability [ 16 , 23 ]. For statistical analysis, the current study used the average of individual PP k _LyE values calculated from three walking trials.…”

“…In order to complete any given motor activity (e.g., walking), the cooperative contribution of multi-body segments is needed, typically seen as different movement components/synergies forming together to accomplish the task goal [ 10 , 15 , 16 ]. Principal component analysis (PCA), one of the methods for reducing the number of dimensions, has widely been used on kinematic marker data to extract movement components or synergies, which have been called “principal movements” (PM), from the original, whole postural movements [ 15 , 17 ].…”

“…Regarding local dynamic stability as measured by the LyE, walking stability can be referred to as the neuromuscular system’s ability to manage infinitesimal perturbations during locomotion [ 9 , 12 , 13 , 14 ]. Therefore, the LyE applied to individual PM positions can aid in quantifying the stability of individual movement components/strategies that come together to achieve locomotion tasks [ 10 , 16 , 23 ].…”

Age and Visual Contribution Effects on Postural Control Assessed by Principal Component Analysis of Kinematic Marker Data

“…In order to determine the coordinative structure or composition of postural movements, the subject-specific relative explained variance (rVAR) of PP k or PP k _rVAR was calculated from the PP k ( ). The PP k _rVAR quantifies how much (in percent) each PM contributed to the total variance in postural positions [ 18 , 20 , 26 , 46 , 49 , 50 ]. Differences in PP k _rVAR between conditions indicate a difference in the coordinative structure of postural movements, i.e., a different contribution of individual PM k to total postural variances.…”