Evaluating RGB channels in remote photoplethysmography: a comparative study with contact-based PPG

Figures

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  FIGURE 1. Visualization of the data extraction to remote photoplethysmograpm (rPPG) evaluation process. DTW = dynamic time warping, r = Pearson’s correlation coefficient, RMSE = root-mean-square error, |ΔBPM| = difference in heartbeats obtained from rPPG and contact PPG.

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  FIGURE 2. Similarity of each channel with the contact PPG, measured with the r coefficient. The results are shown for the datasets LGI-PPGI, PURE, and MR-NIRP. The p-value of every combination of channels, obtained with the Friedman test followed by the post hoc Nemenyi test, is represented by the bars above the boxplots.

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  FIGURE 3. Heart rate estimation from each RGB channel with Welch’s method using the PURE and LGI-PPGI datasets, composed of different videos of 10 and 6 subjects, respectively, performing a wide range of activities. The blue signal shows better results than the red signal in PURE, but not in LGI-PPGI, where the blue signal, on average, is outperformed by the red signal. The green signal is consistently the optimal signal. Note that |ΔBPM| = absolute difference in heartbeats obtained from rPPG and contact PPG.

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  FIGURE 4. Overall performance for the red, green, and blue channels. The r, dynamic time warping (DTW), and root-mean-square error (RMSE) metrics were used. The results are shown for an average over subjects and time windows for each metric. The green channel consistently shows the best performance, followed by the blue and red channels. All the metrics are normalized to one.