Geriatric Agility Detection Using Python and OpenCV

Abstract

Early and accurate detection of frailty in the older population is essential to determine early falls and loss of muscle movement. This allows early intervention as deemed fit by the healthcare providers and prolongs muscle functioning. After the Covid-19 outbreak, a large population of older people have been confined to their homes which has affected their physical health to a great extent. These effects have been magnified in the elderly largely due to extended lockdowns, travel restrictions and loss of social support. The study attempts to design a system to help elderly self-assess their frailty levels by early and precise Geriatric Agility Detection using 30 second chair stand test. Geriatric refers to medical care of older adults and Agility, referring to the ability to move freely and swiftly, is closely linked to reduction of falls in the older population.