Patient Wellness Watch: AI-Powered Facial Video Analysis in Hospitals

This study seeks to enhance patient monitoring in healthcare settings using AI-powered facial video analysis. The primary objective is to develop and implement an algorithm called “Chehra Algorithm,” which processes facial video data to assess patient well-being by extracting key features and analyzing facial expressions. The methodology involves capturing continuous video streams of patients’ faces, from which the system derives a matrix encapsulating vital signs, including heart rate, respiratory rate, facial expressions, and temperature. Machine learning algorithms are employed to continuously learn and adapt to individual patient behavior patterns, improving the system’s accuracy over time. The study demonstrates that integrating AI-powered facial video analysis into patient monitoring systems can significantly improve the precision of health assessments. These findings suggest that such technology can play a critical role in early detection and personalized care, ultimately enhancing patient outcomes in clinical settings.