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.
Funder
Malaysia International Islamic University Research Management Center
United Arab Emirates University Strategic Research
Subject
Health Information Management,Health Informatics,Health Policy,Leadership and Management
Reference127 articles.
1. Iaccino, J. (2014). Left Brain—Right Brain Differences: Inquiries, Evidence, and New Approaches, Psychology Press. [1st ed.].
2. Ruthrof, H. (2015). The Body in Language, Bloomsbury Academic.
3. Molchanov, P., Gupta, S., Kim, K., and Kautz, J. (2015, January 7–12). Hand gesture recognition with 3D convolutional neural networks. Proceedings of theIEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Boston, MA, USA.
4. Pease, A. (2017). Definitive Book of Body Language, Orion Paperbacks.
5. Affective Robotics: Modelling and Testing Cultural Prototypes;Wilson;Cognit. Comput.,2014
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献