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An Analysis of Body Language of Patients Using Artificial Intelligence.
Abdulghafor, Rawad; Abdelmohsen, Abdelrahman; Turaev, Sherzod; Ali, Mohammed A H; Wani, Sharyar.
  • Abdulghafor R; Department of Computer Science, Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia.
  • Abdelmohsen A; Department of Computer Science, Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia.
  • Turaev S; Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain 15551, United Arab Emirates.
  • Ali MAH; Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
  • Wani S; Department of Computer Science, Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia.
Healthcare (Basel) ; 10(12)2022 Dec 10.
Article in English | MEDLINE | ID: covidwho-2154954
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Year: 2022 Document Type: Article Affiliation country: Healthcare10122504

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Year: 2022 Document Type: Article Affiliation country: Healthcare10122504