An Investigation into the Causal Relationship Between Photoplethysmogram and Blood Pressure

Photoplethysmogram (PPG) reflects the pulsation of the heart and is closely related to blood pressure (BP), but its generation mechanism is significantly different from that of BP. While prior research has emphasized their correlation, particularly for BP estimation from PPG, this correlation is often disrupted by individual differences, environmental factors, and signal noise, complicating the understanding of PPG-based BP estimation mechanisms. Causal inference methods have gradually gained attention in the field of physiological signal analysis and can reveal the causal relationship between variables. In this study, we aim to investigate the causal relationship between PPG and BP. We first using ensemble empirical mode decomposition to decomposed the PPG signal into frequency components and constructed counterfactual sequences via causal decomposition. We then analyze the causal relationship between these components and BP with a causal discovery algorithm DirectLiNGAM. It revealed that IMF4 and IMF5, among 10 intrinsic mode functions (IMFs), exhibited a strong causal link with BP. Validated on 164 subjects from VitalDB, BP estimation using these causally related components achieved an estimation error of 10.65 mmHg and 5.75 mmHg for SBP and DBP, respectively, outperforming estimates from the original PPG signal. This indicates that specific components of PPG rather than the original PPG signal can be better casually related with BP.