Review and Analysis of Patients' Body Language From an Artificial Intelligence Perspective

被引:4
|
作者
Turaev, Sherzod [1 ]
Al-Dabet, Saja [1 ]
Babu, Aiswarya [1 ]
Rustamov, Zahiriddin [1 ]
Rustamov, Jaloliddin [2 ]
Zaki, Nazar [1 ]
Mohamad, Mohd Saberi [2 ]
Loo, Chu Kiong [3 ]
机构
[1] United Arab Emirates Univ, Coll Informat Technol, Dept Comp Sci & Software Engn, Al Ain, U Arab Emirates
[2] United Arab Emirates Univ, Coll Med & Hlth Sci, Dept Genet & Genom, Hlth Data Sci Lab, Al Ain, U Arab Emirates
[3] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Artificial Intelligence, Kuala Lumpur 50603, Malaysia
关键词
Artificial intelligence; body language; abnormal activity; abnormal body action; abnormality detection; machine learning; data analysis; PARKINSONS-DISEASE PATIENTS; FACIAL EXPRESSION ANALYSIS; ACTIVITY RECOGNITION; EYE-MOVEMENTS; BEHAVIORAL-ANALYSIS; FALL DETECTION; CODING SYSTEM; HEALTH-CARE; GAIT; PAIN;
D O I
10.1109/ACCESS.2023.3287788
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Body language is a nonverbal communication process consisting of movements, postures, gestures, and expressions of the body or body parts. Body language expresses human feelings, thoughts, and intentions. It also reveals physical and psychological health conditions: abnormal activities inform peoples' health conditions, facial expressions indicate their emotional states and abnormal body actions convey specific diseases' external signs and symptoms. We can observe the importance of studying the body language of people with health conditions through many reports in literature written by healthcare (medical) and artificial intelligence researchers. This paper comprehensively reviews artificial intelligence-based articles that have studied patients' body language. We also conduct different descriptive and exploratory examinations of the findings using data analysis techniques, which provide more authentic domain knowledge of abnormal activities, abnormal body actions, and more precise analysis of methodologies used in machine learning tasks for studying these abnormalities. The paper's results are essential for developing intelligent automated systems that accurately evaluate patients' physical and psychological conditions, precisely identify external signs and symptoms of diseases, and adequately monitor patients' health conditions.
引用
收藏
页码:62140 / 62173
页数:34
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