GAITCLOUD-EVGS: CLOUD PLATFORM PROJECT FOR AUTOMATIC ANALYSIS OF GAIT VIDEOS (REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE, 2026)
Postural analysis is a powerful technique for assessing work-related activities. Posture and gait analysis are also important in assessing medical recovery after neurological injuries (e.g., stroke), neurodegenerative diseases (Alzheimer's, Parkinson's, etc.), or traffic or work accidents.  In this respect, the Edinburgh visual gait score (EVGS) is a widely used observational clinical tool for the qualitative assessment of human gait. Its traditional determination is based on manual analysis of video recordings by clinicians, a process that is time-consuming, susceptible to inter- and intra-evaluator variability, and strongly dependent on the quality of the available video material. In this context, the present work proposes the conceptual design of a cloud-based service for automated video-based gait analysis and EVGS computation. Within the proposed architecture, the resulting scores and reports would be delivered and visualized through a dedicated web interface.
Keywords: Cloud computing; Rehabilitation; Image analysis; Edinburgh visual gait score (EVGS); Mobile application