As a software computer vision company, we are curious not only about art and how to combine creativity with tech.
Mikhail Kopeliovich, the computer vision engineer of SketchAR, presented his work on webcam-based heart rate evaluation at the Intelligent Systems conference — IntelliSys 2019. The event was held in London on Sept 5–6.
It was attended by researchers and engineers from more than 50 countries and various IT companies such as Google and Intel. The presented work of Mikhail Kopeliovich and Mikhail Petrushan is a detailed review of popular algorithms and methods for assessing heart rate in a video. They analyzed different combinations from these algorithms and presented the most accurate of them.
Color Signal Processing Methods for Webcam-Based Heart Rate Evaluation.
Authors(SketchAR): Mikhail Kopeliovich, Mikhail Petrushan.
Computer vision methods are widely applied in health assistance and medical diagnostics. Photoplethysmography (PPG) is one such method that can be used for contactless estimation of heart rate through the analysis of slight variations of skin color which are caused by changes in the blood volume in vessels. These changes of skin color registered by a camera are called color signal. According to recent studies, some PPG methods can be applied on video data recorded by common web-cameras with sufficient accuracy, so they are recognized as potentially applicable for long-term health monitoring in house or office conditions. In this study, we evaluate the accuracy of commonly used signal processing methods for webcam-based PPG as well as novel modifications of these methods in various combinations with preprocessing and postprocessing filtering algorithms. In particular, the Extended Fourier analysis that is based on Gaussian smoothing and temporal averaging of Fourier spectra were applied to estimate heart rate.
The paper was published in Advances in Intelligent Systems and Computing journal.
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