Generalizable PPG Signal Quality Assessment Using Correlation-Derived Morphological Features
This study proposes an interpretable binary signal quality assessment (SQA) method based on morphological self-consistency using correlation analysis and machine learning that supports the robustness and practical relevance of correlation-derived morphological features for wearable PPG quality control.
Pietro Chierico, Vicente Bertomeu-González, Raúl Alcaraz et al.
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