An Analysis of Body Language of Patients Using Artificial Intelligence

Rawad Abdulghafor, Abdelrahman Abdelmohsen, Sherzod Turaev, Mohammed A.H. Ali, Sharyar Wani

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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 languageEnglish
Article number2504
JournalHealthcare (Switzerland)
Issue number12
Publication statusPublished - Dec 2022


  • 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


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