An Analysis of Body Language of Patients Using Artificial Intelligence.

Area of Science:

• Medical technology and artificial intelligence (AI).
• Biomedical engineering and human-computer interaction.

Background:

• Epidemic and pandemic illnesses pose global health challenges.
• Smart technology integration in healthcare is rapidly advancing.
• Automated detection of health status and emotions is a key research area.

Purpose of the Study:

• To conduct a meta-review of existing literature on AI-driven body language classification for disease detection.
• To examine various AI methods used for analyzing full-body tracking and facial expressions.
• To assess the significance and outcomes of AI applications in identifying pandemic-related symptoms.

Main Methods:

• Systematic literature search for studies employing AI in body language analysis.
• Categorization of AI techniques for full-body and facial expression detection.
• Meta-analysis of reported results for tasks like fall detection and COVID-19 detection.

Main Results:

• AI shows promise in classifying body language for health monitoring.
• Diverse AI approaches exist for analyzing human movement and expressions.
• Studies demonstrate AI's potential in aiding disease diagnosis, including COVID-19 detection.

Conclusions:

• Further comprehensive research is needed to fully leverage AI for illness diagnosis using body language.
• AI-powered analysis of body language represents a developing field with significant potential.
• Integrating AI with full-body tracking and facial recognition can enhance epidemic and pandemic response.