Abstract: Touchless heartbeat measurement using facial video represents a cutting-edge approach to non-invasive physiological monitoring, leveraging advancements in computer vision and machine learning. Traditional methods of heartbeat detection, such as contact-based sensors, can be uncomfortable or impractical for certain use cases. By contrast, this method uses facial video to capture subtle color changes and micro-movements in a person’s face, which correlate with blood flow and heart activity. Through a series of algorithms, the video feed is processed to isolate these variations, calculate heartbeat signals, and deliver real-time measurements.

This technology has a wide range of applications, including healthcare monitoring, mental health assessment, and fitness tracking, especially in scenarios where physical contact is undesirable or unfeasible. Additionally, the method provides a solution for remote, continuous monitoring, offering potential applications in telemedicine and home healthcare. Experimental results demonstrate that touchless measurement via facial video achieves reliable accuracy under controlled lighting and minimal movement, though challenges remain in adapting the technology to diverse environments and populations. The advancement of robust and adaptive algorithms is essential to overcoming these limitations and fully realizing the potential of contactless health monitoring.

| DOI: 10.17148/IARJSET.2024.111021