Abstract
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.
Original language | English |
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Article number | 2504 |
Journal | Healthcare (Switzerland) |
Volume | 10 |
Issue number | 12 |
DOIs | |
Publication status | Published - Dec 2022 |
Keywords
- AI
- COVID-19
- anomaly detection
- body language
- body language analysis
- epidemic
- fall detection
- gesture recognition
- neocoronal pneumonia
- pandemic
ASJC Scopus subject areas
- Leadership and Management
- Health Policy
- Health Informatics
- Health Information Management