Establishing reference criteria for diagnosing normal gait patterns similarity using dynamic time warping.

Abstract

The purpose of this study was to establish reference criteria for evaluating gait pattern similarity during normal gait in research using dynamic time warping (DTW). For this purpose, the DTW algorithm was implemented using the R programming language, and DTW analyses were conducted on normal gait data collected from the ankle, knee, and hip joints via 3-dimensional motion analysis in a sample of 55 healthy participants. The final optimal warping path identified by DTW was defined as the path having the smallest cumulative perpendicular distance from the diagonal of the cost matrix. DTW analyses were categorized into three groups: (1) same lower-limb within-subject, comparing identical limbs within each participant; (2) same lower-limb between-subjects, comparing identical limbs between different participants; and (3) opposite lower-limb within-subject, comparing the left and right limbs within each participant. A generalized linear model was employed to analyze the effects of group and gender. Reference criteria for gait pattern similarity are provided as estimated marginal means and 95% confidence intervals according to group and gender for each lower-limb joint during normal gait. Given statistically significant differences among groups, the results underscore the necessity of evaluating not only whether patient gait patterns align within the normal range of healthy individuals but also the similarity between the patient's own limbs for precise rehabilitation assessment.