Federica Semproni
Advanced Machine Learning Techniques to Analyze Video Recordings for Application in Rehabilitation Medicine.
Rel. Gabriella Olmo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2020
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Abstract
The gait function has an important impact on the quality of life of people. Nowadays numerous pathologies are the cause of a deviation from the normal gait, resulting in a great disability in the performance of the daily life activities. For this reason, the improvement of gait is one of the main focuses of rehabilitation interventions to ensure total inclusion in society and to remove every kind of barrier. Currently, motion analysis laboratories perform gait analysis using systems that exploit the tracking of infrared reflective markers positioned on anatomical landmarks of the patient. Unfortunately, these systems are cumbersome, high-cost and take a lot of hours to collect and to analyze the clinical walking data by specialized personnel.
The purpose of the thesis aims to evaluate a new marker-less approach to perform gait analysis on disabled patients by enabling low-cost, and user-friendly procedures
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