Spatiotemporal analysis of human gait, based on feet trajectories estimated by means of depth sensors
Keywords:gait analysis, gait asymmetry, healthcare, depth sensor, measurement data processing
This paper addresses a methodology for the analysis of human gait, based on the data acquired by means of depth sensors. This methodology is dedicated to healthcare-related applications and involves the identification of the phases of the gait cycle by thresholding estimates of velocities of the examined person’s feet. In order to assess its performance, a series of experiments was carried out using a reference gait-analysis system based on a pressure-distribution-measurement platform. An original method for quantifying gait asymmetry, based on a quasi-correlation between the feet trajectories, was also proposed and tested experimentally. The results of the reported experiments seem to promise a high applicability potential of the considered methodology.
Copyright (c) 2022 Jakub Wagner, Roman Z. Morawski
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).