Project

Heart rate estimation from face video

Goal: Implementation, improvement, and evaluation of Remote Photoplethysmography (rPPG) algorithms to measure human heart rate contactlessly using a video camera.

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Philipp V. Rouast
added 3 research items
Remote Photoplethysmography (rPPG) allows remote measurement of the heart rate using low-cost RGB imaging equipment. In this paper, we review the development of the field since its emergence in 2008, classify existing approaches for rPPG, and derive a framework that provides an overview of modular steps. Based on this framework, practitioners can use the classification to orchestrate algorithms to an rPPG approach that suits their specific needs. Researchers can use the reviewed and classified algorithms as a starting point to improve particular features of an rPPG algorithm.
As a source of valuable information about a person's affective state, heart rate data has the potential to improve both understanding and experience of human-computer interaction. Conventional methods for measuring heart rate use skin contact methods, where a measuring device must be worn by the user. In an Information Systems setting, a contactless approach without interference in the user's natural environment could prove to be advantageous. We develop an application that fulfils these conditions. The algorithm is based on remote photoplethysmography, taking advantage of the slight skin color variation that occurs periodically with the user's pulse. When evaluating this application in an Information Systems setting with various arousal levels and naturally moving subjects, we achieve an average root mean square error of 7.32 bpm for the best performing configuration. We find that a higher frame rate yields better results than a larger size of the moving measurement window. Regarding algorithm specifics, we find that a more detailed algorithm using the three RGB signals slightly outperforms a simple algorithm using only the green signal.
Heart rate measurements contain valuable information about a person’s affective state. There is a wide range of application domains for heart rate-based measures in information systems. To date, heart rate is typically measured using skin contact methods, where users must wear a measuring device. A non-contact and easy to use mobile approach, allowing heart rate measurements without interfering with the users’ natural environment, could prove to be a valuable NeuroIS tool. Hence, our two research objectives are (1) to develop an application for mobile devices that allows for non-contact, real-time heart rate measurement and (2) to evaluate this application in an IS context by benchmarking the results of our approach against established measurements. The proposed algorithm is based on non-contact photoplethysmography and hence takes advantage of slight skin color variations that occurs periodically with the user’s pulse.
Philipp V. Rouast
added a project goal
Implementation, improvement, and evaluation of Remote Photoplethysmography (rPPG) algorithms to measure human heart rate contactlessly using a video camera.