This paper proposes a novel approach for touchless heart rate prediction using facial expression and image processing techniques. Traditional heart rate monitoring methods require physical contact, which can be uncomfortable and inconvenient for the user. In this paper, we present a non-contact heart rate monitoring method using facial expressions captured by a camera. Our proposed system uses an image processing algorithm to detect facial landmarks and track them over time to estimate changes in skin color caused by blood flow. These changes are then used to predict heart rate in real-time. The major goal of this method is to identify a person's HR by identifying colour changes in the face's skin brought on by heartbeat. Following that, the frequency is determined using Colour Magnification and the FFT technique, and heart-rate prediction follows suit. We will look into covid if the HR is higher than that of a typical person. We can start treating the patient if the test findings are positive. The proposed system has the potential to revolutionize heart rate monitoring by providing a touchless and non-invasive method for heart rate prediction. This system can be applied in various domains, including healthcare, sports, and wellness, where non-invasive heart rate monitoring is crucial for accurate diagnosis and treatment. The system's simplicity and low-cost make it an attractive alternative to traditional heart rate monitoring methods, providing a more comfortable and convenient experience for users.

Covid-19, Image processing, Machine Learning, , Fast Fourier Transform (FFT) algorithm, Color Magnification (CM) Algorithm, Facial Video, Heart Rate (HR) Detection etc.