Key result
Regression method reconstructs target PPG waveforms from stealthily recorded signals with ~0.86 correlation.
Effect estimate: correlation coefficients >0.860
A novel regression-based method can successfully reconstruct PPG waveforms from stealthily recorded physiological signals with high correlation, highlighting potential privacy or security implications.
In this study, we propose a method to reconstruct photoplethysmogram (PPG) waveforms from other stealthily recorded physiological signals. The proposed method focuses on the frequency characteristics between two physiological signals and reconstructs the target PPG waveform using a regression model. We investigate the feasibility of the proposed method to reconstruct target PPG signals from respiratory (RSP) and PPG signals recorded at non-genuine measurement sites using the two datasets of physiological signals. The results indicate that the proposed method achieves similarities between the target PPG and reconstructed PPG signals with correlation coefficients more than 0.860.
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Hinatsu et al. (2023) studied this question. PPG waveform reconstruction method using a regression model was evaluated on Similarity between target PPG and reconstructed PPG signals (correlation coefficients >0.860). A proposed regression-based method successfully reconstructed target photoplethysmogram (PPG) waveforms from stealthily recorded physiological signals, achieving correlation coefficients >0.860.
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