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