Estimation of Respiratory Rate Using Facial Video Analysis

The Respiratory rate (RR) is a crucial indicator of health, often used to detect respiratory and cardiac conditions. Traditional RR measurement methods can be intrusive and uncomfortable. The work explores a non-contact method for estimating RR using video analysis. By detecting facial features and analyzing intensity variations in the chin region, it demonstrate that video-based RR estimation is a feasible and effective alternative to conventional methods. The findings suggest significant potential for applications in telemedicine, remote health monitoring, and continuous patient assessment.