Abstract
Physical changes such as leg length discrepancy, the addition of a mass at the distal end of the leg, the use of a prosthetic, and stroke frequently result in an asymmetric gait. This paper presents a metric that can potentially serve as a benchmark to categorize and differentiate between multiple asymmetric bipedal gaits. The combined gait asymmetry metric (CGAM) is based on modified Mahalanobis distances, and it utilizes the asymmetries of gait parameters obtained from motion capture and force data recorded during human walking. The gait parameters that were used in this analysis represent spatio-temporal, kinematic, and kinetic parameters. This form of a consolidated metric will help researchers identify overall gait asymmetry by showing them if the overall gait symmetry is improving and avoid the case where one parameter's symmetry is improving while another is getting worse. The CGAM metric successfully served as a measure for overall symmetry with eleven different gait parameters and successfully showed differences among gait with multiple physical asymmetries. The results showed that mass at the distal end had a larger magnitude on overall gait asymmetry compared to leg length discrepancy. It also showed that the combined effects are varied based on the cancelation effect between gait parameters. The metric was also successful in delineating the differences of prosthetic gait and able-bodied gait at three different walking velocities.
Highlights
Human gait is a complex coordinated cyclic neuromuscular process that includes voluntary and involuntary aspects (Zijlstra et al, 1995)
The purpose of this study is to present a simple but versatile quantitative asymmetry metric that can be used to characterize the asymmetry of gait patterns as a whole
The literature review for this study looked at various physical changes such as leg length discrepancy (LLD), the addition of mass at the distal end of the leg, amputation, and stroke
Summary
Human gait is a complex coordinated cyclic neuromuscular process that includes voluntary and involuntary aspects (Zijlstra et al, 1995) This cyclic process is frequently impaired following central nervous system damage, such as stroke, or physical changes, such as wearing a prosthetic. Using a quantitative data driven analysis offers an unbiased evaluation of the effects of multiple physical asymmetries that affect human gait. For this experimental study, the physical changes were selected based on Comparing Asymmetries Using Consolidated Metrics the dynamic principles related to leg length and mass on a periodic system.
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