A Review on Challenges in Telerehabilitation and Human Activity Recognition Approaches during Covid-19 Pandemic

Abstract

Impact of COVID-19 pandemic is widespread imposing limitations on the healthcare services all over the world. Due to this pandemic, governments around the world have imposed restrictions that limit individual freedom and have enforced social distance to prevent the collapse of national health care systems. In such situation, to offer medical care and rehabilitation to the patients, Telerehabilitation (TR) is a promising way of delivering healthcare facilities remotely using telecommunication and internet. Technological advancement has played the vital role to establish this TR technology to remotely assess patient’s physical condition and act accordingly during this pandemic. Likewise, Human Activity Recognition (HAR) is a key part of the recovery process for a wide variety of conditions, such as stroke, arthritis, brain injury, musculoskeletal injuries, Parkinson’s disease, and others. Different approaches of human activity recognition can be utilized to monitor the health and activity levels of such a patient effectively and TR allows to do this remotely. Therefore, in situations where conventional care is inadequate, combination of telerehabilitation and HAR approaches can be an effective means of providing treatment and these opportunities have become patently apparent during the COVID-19 outbreak. However, this new era of technical progress has significant limitations, and in this paper, our main focus is on the challenges of telerehabilitation and the various human activity recognition approaches. This study will help researchers identify a good activity detection platform for a TR system during and after COVID-19, considering TR and HAR challenges.