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Mobile Information Systems
Volume 2018 (2018), Article ID 7381264, 10 pages
Research Article

Gait Analysis Using Computer Vision Based on Cloud Platform and Mobile Device

Department of Computing Technology, University of Alicante, Campus San Vicente del Raspeig, Alicante, Spain

Correspondence should be addressed to Mario Nieto-Hidalgo

Received 30 June 2017; Revised 31 October 2017; Accepted 12 November 2017; Published 14 January 2018

Academic Editor: Pino Caballero-Gil

Copyright © 2018 Mario Nieto-Hidalgo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Frailty and senility are syndromes that affect elderly people. The ageing process involves a decay of cognitive and motor functions which often produce an impact on the quality of life of elderly people. Some studies have linked this deterioration of cognitive and motor function to gait patterns. Thus, gait analysis can be a powerful tool to assess frailty and senility syndromes. In this paper, we propose a vision-based gait analysis approach performed on a smartphone with cloud computing assistance. Gait sequences recorded by a smartphone camera are processed by the smartphone itself to obtain spatiotemporal features. These features are uploaded onto the cloud in order to analyse and compare them to a stored database to render a diagnostic. The feature extraction method presented can work with both frontal and sagittal gait sequences although the sagittal view provides a better classification since an accuracy of 95% can be obtained.