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Open AccessArticle

Continuous Distant Measurement of the User’s Heart Rate in Human-Computer Interaction Applications

AGH University of Science and Technology, 30 Mickiewicza Ave., 30-059 Krakow, Poland
Sensors 2019, 19(19), 4205; https://doi.org/10.3390/s19194205
Received: 9 August 2019 / Revised: 30 August 2019 / Accepted: 25 September 2019 / Published: 27 September 2019
In real world scenarios, the task of estimating heart rate (HR) using video plethysmography (VPG) methods is difficult because many factors could contaminate the pulse signal (i.e., a subjects’ movement, illumination changes). This article presents the evaluation of a VPG system designed for continuous monitoring of the user’s heart rate during typical human-computer interaction scenarios. The impact of human activities while working at the computer (i.e., reading and writing text, playing a game) on the accuracy of HR VPG measurements was examined. Three commonly used signal extraction methods were evaluated: green (G), green-red difference (GRD), blind source separation (ICA). A new method based on an excess green (ExG) image representation was proposed. Three algorithms for estimating pulse rate were used: power spectral density (PSD), autoregressive modeling (AR) and time domain analysis (TIME). In summary, depending on the scenario being studied, different combinations of signal extraction methods and the pulse estimation algorithm ensure optimal heart rate detection results. The best results were obtained for the ICA method: average RMSE = 6.1 bpm (beats per minute). The proposed ExG signal representation outperforms other methods except ICA (RMSE = 11.2 bpm compared to 14.4 bpm for G and 13.0 bmp for GRD). ExG also is the best method in terms of proposed success rate metric (sRate). View Full-Text
Keywords: video pletysmography; image processing; heart rate estimation; human-computer interaction; biomedicine; healthcare; assisted living video pletysmography; image processing; heart rate estimation; human-computer interaction; biomedicine; healthcare; assisted living
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Przybyło, J. Continuous Distant Measurement of the User’s Heart Rate in Human-Computer Interaction Applications. Sensors 2019, 19, 4205.

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