Published Paper Details:

Healthcare technology has advanced beyond human endeavors and is used in the human environment to help the humans raise healthy and well organized standards of our daily existence. The emergence of Human pose estimation in computer vision tracks human movement from simple visuals using commonly used low cost cameras (e.g. laptop cameras). These technologies offer a clear and exciting monitoring performance of the physiotherapeutic patients from home. A Doctor or a person could monitor and analyze movement of patients remotely. In fields like rehabilitation, healthcare and fitness there has been a recent trend toward implementing computer vision based equipment to enhance health monitoring efficiency and quality. These Computer vision based systems are designed to perform tasks such as monitoring the visuals and extracting the movements information from the videos or images. This project introduces a model of a standalone reinforced physiotherapy equipment which enhances the physiotherapeutic patients with well lit physiotherapy treatment according to the doctors prescription. The aim is to address common challenges encountered in the field of traditional rehabilitation. The research outlines the development of a standalone reinforced physiotherapy equipment which is equipped with a Raspberry Pi 4 and a web camera. We focus specifically on the physiotherapeutic patients who need treatment in the absence of the doctor or the fitness trainer. We review relevant literature, share views on future prospects to improve human health and performance and discuss perceived limitations. Keywords: Pose estimation; Reinforced Physiotherapy Equipment; rehabilitation; video based monitoring device; at-home physiotherapy participation.