TY - JOUR
T1 - An Analysis of Body Language of Patients Using Artificial Intelligence
AU - Abdulghafor, Rawad
AU - Abdelmohsen, Abdelrahman
AU - Turaev, Sherzod
AU - Ali, Mohammed A.H.
AU - Wani, Sharyar
N1 - Funding Information:
Acknowledgments: The authors would like to thank the Research Management Center, Malaysia International Islamic University for funding this work by Grant RMCG20-023-0023. Also, the authors would like to thank the United Arab Emirates University for funding this work under UAEU Strategic Research Grant G00003676 (Fund No.: 12R136) through Big Data Analytics Center.
Publisher Copyright:
© 2022 by the authors.
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - AI
KW - COVID-19
KW - anomaly detection
KW - body language
KW - body language analysis
KW - epidemic
KW - fall detection
KW - gesture recognition
KW - neocoronal pneumonia
KW - pandemic
UR - http://www.scopus.com/inward/record.url?scp=85144652875&partnerID=8YFLogxK
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U2 - 10.3390/healthcare10122504
DO - 10.3390/healthcare10122504
M3 - Article
AN - SCOPUS:85144652875
SN - 2227-9032
VL - 10
JO - Healthcare (Switzerland)
JF - Healthcare (Switzerland)
IS - 12
M1 - 2504
ER -
