Monitoring of Four Vital Signs Using Video Processing Based on Machine and Deep Learning Approaches: A Review

Video Health Monitoring (VHM) received considerable significant interest due to its potential for effortless implementation and widespread use in many settings, including public spaces, smart homes, and healthcare institutions. This study looks at how VHM approaches may leverage machine learning (ML) and deep learning (DL) methods to increase the precision of vital sign monitoring. The review being conducted does a thorough analysis of the current state of VHM. This article evaluates the broader consequences of healthcare delivery and the integration of technology, identifies important barriers, and explores the inherent benefits. Furthermore, it analyzes the difficulties and limitations linked to evaluating each physiological sign. The purpose of the insights provided is to assist healthcare practitioners, researchers, and technology specialists in furthering the development and use of VHM systems.