Abstract
BackgroundClinical scores for evaluating walking skills with lower limb exoskeletons are often based on a single variable, such as distance walked or speed, even in cases where a host of features are measured. We investigated how to combine multiple features such that the resulting score has high discriminatory power, in particular with few patients. A new score is introduced that allows quantifying the walking ability of patients with spinal cord injury when using a powered exoskeleton.MethodsFour spinal cord injury patients were trained to walk over ground with the ReWalk™ exoskeleton. Body accelerations during use of the device were recorded by a wearable accelerometer and 4 features to evaluate walking skills were computed. The new score is the Gaussian naïve Bayes surprise, which evaluates patients relative to the features’ distribution measured in 7 expert users of the ReWalk™. We compared our score based on all the features with a standard outcome measure, which is based on number of steps only.ResultsAll 4 patients improved over the course of training, as their scores trended towards the expert users’ scores. The combined score (Gaussian naïve surprise) was considerably more discriminative than the one using only walked distance (steps). At the end of training, 3 out of 4 patients were significantly different from the experts, according to the combined score (p < .001, Wilcoxon Signed-Rank Test). In contrast, all but one patient were scored as experts when number of steps was the only feature.ConclusionIntegrating multiple features could provide a more robust metric to measure patients’ skills while they learn to walk with a robotic exoskeleton. Testing this approach with other features and more subjects remains as future work.
Highlights
Clinical scores for evaluating walking skills with lower limb exoskeletons are often based on a single variable, such as distance walked or speed, even in cases where a host of features are measured
A paradigmatic case is the ReWalkTM, which has been approved by the Food and Drug Administration to be sold to individuals with Spinal cord injury (SCI) as a take-home personal mobility device
Such training is typically delivered in a clinical setting and clinicians need a robust metric to evaluate if a patient has reached a level of ability and expertise to independently use the device at home and in the community
Summary
Clinical scores for evaluating walking skills with lower limb exoskeletons are often based on a single variable, such as distance walked or speed, even in cases where a host of features are measured. Individuals with complete SCI, who aim at taking an exoskeleton home as a personal mobility device, require an intensive training protocol to become independent users Such training is typically delivered in a clinical setting and clinicians need a robust metric to evaluate if a patient has reached a level of ability and expertise to independently use the device at home and in the community. Obtaining a robust index of the patients’ walking skills with an exoskeleton could be used to inform health insurance companies about the actual improvements in functional mobility for potential reimbursement This point is crucial as the cost of these devices is extremely high and any support funding has to be justified
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