Pose Estimation Approach for Gait Analysis using Machine Learning
Sharon Jemimah Peace C, V. Ebenezer, Bijolin Edwin, R. Abinayaa, D Sharan, Roshini Thanka
Abstract
The purpose of the paper is to incorporate machine learning in gait analysis by solving the problems associated with the health of aged people by concentrating on the frailty and senility syndromes that affect elderly individuals with the incorporation of machine learning. Deterioration of cognitive and motor abilities is a common result of ageing and has an effect on elderly people’s quality of life. Some studies have connected these changes in gait patterns to the decline in cognitive and motor function. As a result, gait analysis is a useful tool for diagnosing senility and frailty diseases. By transferring the pose estimation data to a correct statistical analysis, gait analysis can be carried out utilizing machine learning and computer vision approaches, allowing physiotherapists to analyze and treat patients accordingly.