Abstract
In this paper, we introduce an approach for measuring human gait symmetry where the input is a sequence of depth maps of subject walking on a treadmill. Body surface normals are used to describe 3D information of the walking subject in each frame. Two different schemes for embedding the temporal factor into a symmetry index are proposed. Experiments on the whole body, as well as the lower limbs, were also considered to assess the usefulness of upper body information in this task. The potential of our method was demonstrated with a dataset of 97,200 depth maps of nine different walking gaits. An ROC analysis for abnormal gait detection gave the best result () compared with other related studies. The experimental results provided by our method confirm the contribution of upper body in gait analysis as well as the reliability of approximating average gait symmetry index without explicitly considering individual gait cycles for asymmetry detection.
Highlights
Gait analysis has shown a lot of evidences demonstrating its potential to identify and diagnose early neurological and non-neurological musculoskeletal disorders
It is obvious that the segment-based index in Equation (7) was more efficient for assessing gait symmetry than the one obtained by Equation (6) where the temporal factor was embedded after performing the index estimation for each frame
This table shows that when the upper body was removed from the index estimation, the ability of gait symmetry assessment was reduced with decreasing of Area Under Curve (AUC) at corresponding positions in the table
Summary
Gait analysis has shown a lot of evidences demonstrating its potential to identify and diagnose early neurological and non-neurological musculoskeletal disorders. Gait symmetry is one of the most popular features used to perform these health-related assessments. It is a good indicator of human motion ability to identify pathology and assess recovery for people with asymmetric gait of various origins such as cerebral palsy, stroke, hip or knee arthritis and surgery or leg length discrepancy [1,2,3,4]. The objective of our method is to measure a reasonable index indicating human gait symmetry during a walk. This may work as a patient screening tool providing relevant gait information during a treatment or recovery after a surgery. The study can be considered as an exploratory examination of surface normals to assess gait asymmetry since this factor plays the principal role in our gait description
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