Can PPG Replace ECG for Early Assessment? Evidence From Clustering-Based Coherence Analysis

Photoplethysmography (PPG) offers a low-cost, accessible means of physiological monitoring, yet its potential to replace electrocardiography (ECG) for preliminary patient evaluation remains insufficiently validated. This study investigates the coherence between PPG and ECG measurements by applying a comprehensive cluster-based analysis. Eight unsupervised algorithms were employed to classify healthy subjects using either raw signals or derived cardiovascular parameters extracted independently from both modalities. The resulting clusters were compared to assess how consistently PPG reproduced the ECG-based grouping. Across algorithms, PPG-based classifications showed high agreement with ECG-driven clusters, particularly when using feature-derived representations rather than raw signals. These findings indicate that PPG can reliably capture essential cardiovascular information relevant for early assessment, supporting its use as an effective alternative when ECG is impractical or resource-intensive. The study highlights the value of clustering consistency as a validation strategy and provides evidence for the integration of PPG in preliminary screening and remote monitoring applications.