Identifying gait quality metrics sensitive to changes in lower limb constraint

Abstract

Background Manual tuning of robotic lower limb prostheses can be time consuming for both the patient and the clinician and requires in-person visits to a clinic. An automated process for the tuning parameters of a robotic lower limb prosthesis could result in a substantial savings in healthcare resources. A critical challenge to an automated parameter tuning algorithm is the quantification of a person’s gait quality. There is not good agreement in the literature of an objective outcome measure that can rapidly assess gait quality in lower limb amputees. As a first step, we investigated the ability of four common gait quality metrics to detect differences in gait quality: Prosthetic Observational Gait Score (POGS), Gait Deviation Index (GDI), Lateral Sway, and Impulse Asymmetry. Methods We systematically applied four unilateral lower limb joint constraint conditions (baseline/no constraint, ankle constraint, knee constraint, and knee + ankle constraint) to nine able-bodied participants walking at three different speeds (0.7, 0.85 and 1.0 m/s). We calculated and compared the resulting GDI, POGS, Lateral Sway and Impulse Asymmetry scores across all conditions. We performed a 2-way ANOVA statistical analysis to compare sensitivity of the metrics to the various conditions with significance defined by an alpha-level = 0.05. Results The Lateral Sway metric distinguished three joint constraint conditions and two of the speed conditions. Both GDI and POGS were able to distinguish four out of six possible constraint-speed conditions, while Impulse Asymmetry was only able to detect differences between three of the six constraint-speed conditions. Conclusions No single gait quality metric could distinguish every condition. Accordingly, a single metric of gait quality may be inadequate for tuning a prosthesis and therefore multiple metrics and sensors may provide the best results for tuning a prosthesis to the most natural gait pattern for an individual. Compared to the more complex gait measures, Lateral Sway performed well as a simple metric that might easily be operationalized into a real-time parameter tuning controller.