An analysis of body language of patients using artificial intelligence

• Main Authors: Abdulghafor, Rawad, Abdelmohsen, Abdelrahman, Turaev, Sherzod, Ali, Mohammed A. H., Wani, Sharyar
• Format: Article
• Published: MDPI 2022
• Subjects: QA75 Electronic computers. Computer science; RA0421 Public health. Hygiene. Preventive Medicine
• Online Access: http://eprints.um.edu.my/40261/

In recent decades, epidemic and pandemic illnesses have grown prevalent and are a regular source of concern throughout the world. The extent to which the globe has been affected by the COVID-19 epidemic is well documented. Smart technology is now widely used in medical applications, with the automated detection of status and feelings becoming a significant study area. As a result, a variety of studies have begun to focus on the automated detection of symptoms in individuals infected with a pandemic or epidemic disease by studying their body language. The recognition and interpretation of arm and leg motions, facial recognition, and body postures is still a developing field, and there is a dearth of comprehensive studies that might aid in illness diagnosis utilizing artificial intelligence techniques and technologies. This literature review is a meta review of past papers that utilized AI for body language classification through full-body tracking or facial expressions detection for various tasks such as fall detection and COVID-19 detection, it looks at different methods proposed by each paper, their significance and their results.