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. Author manuscript; available in PMC: 2020 Sep 1.
Published in final edited form as: Neuroimage. 2019 May 23;198:303–316. doi: 10.1016/j.neuroimage.2019.05.049

Figure 9.

Figure 9

Histogram of crosscorrelation values between plethysmogram waveforms before and after application of the deep learning filter. High quality plethysmograms are not significantly changed by the filter, but signals without a strong cardiac waveform are. “Unusable” plethysmograms were visually verified to have either no signal, extremely poor SNR, strong artifacts, or distorted cardiac waveforms. 47 of 400 runs (11.75%) were found to be unusable.