Abstract
Imaging photoplethysmography (IPPG) enables contactless physiological parameters monitoring using a regular video camera, which led to an increasing interest in video health monitoring. However, classical IPPG is unable to accurately measure heart rate over a long-distance motion. In this paper, an IPPG heart rate detection framework is proposed based on an adaptive-zoom system called adaptive-zoom IPPG (AZIPPG). It uses an automatic zoom lens to maintain the size of the sensitive area during long-distance motion. The data gathered from AZIPPG were compared with the output of blood volume pulse (BVP) devices and a classical IPPG system. The experimental results showed that AZIPPG achieved high accuracy and correlation in different environments featuring subjects engaged in static and long-distance walking. Actually, AZIPPG eliminates dramatic changes in the ROI, it also introduces image blurring. In this report, the presented theoretical and experimental results indicate that defocused image blurring dose not significantly affect the IPPG's intensity. The pulse data extracted from AZIPPG were comparable to those obtained from the PPG signal of a conventional BVP device. These findings may potentially advance progress in personal health care and telemedicine.
Highlights
Imaging photoplethysmography (IPPG), known as remote photoplethysmography, uses video sequences to measure variations in light absorption caused by blood volume pulse (BVP) to extract cardiopulmonary parameters including heart rate (HR), pulse rate variability, and respiration rate [1]–[3]
To achieve accurate extraction in this situation, we propose an IPPG heart rate detection framework based on an adaptive-zoom system called adaptive-zoom IPPG (AZIPPG)
Most commercial automatic zoom lenses are too slow to facilitate focusing in realtime, which results in image blurring
Summary
Imaging photoplethysmography (IPPG), known as remote photoplethysmography, uses video sequences to measure variations in light absorption caused by blood volume pulse (BVP) to extract cardiopulmonary parameters including heart rate (HR), pulse rate variability, and respiration rate [1]–[3]. As a result of the development of optoelectronic imaging equipment and machine vision, there is a growing interest in IPPG because it facilitates remote measurement of physiological parameters without the need for specialized hardware. Given that the amplitude of the IPPG pulse signal associated with a cardiac pulse is small, its wide application is limited due to changes in motion and lighting conditions. Many factors can cause IPPG pulse distortion, including poor performance of the imaging instrument, light source stability, and the state of the subject (stationary or motion), etc. Artefacts associated with the subject’s motion is the biggest challenge.
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