Heart rate (HR) monitoring is essential for evaluating physiological health and identifying cardiovascular problems early. Most HR monitors need skin contact, but remote photoplethysmography (rPPG) provides a non-invasive option by analyzing subtle skin color changes through video. This method, also called video plethysmography (VPG), is beneficial for people who cannot use contact-based monitors, such as those with sensitive skin or in remote monitoring situations. VPG uses consumer-grade cameras to measure heart and breathing rates without wearable devices. This enables its use in various domains, such as sports optimization, emotional communication in human-machine interaction, and driver monitoring. However, estimating HR from video accurately is challenging due to subject movement and lighting variations. This study presents a novel approach to HR measurement using quaternion algebra, an improvement over complex numbers, to exploit the relationship between RGB camera color components effectively. Our framework aims to offer continuous HR monitoring in diverse settings, such as telemedicine, fitness, and psychological assessments.