Key result
Fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques provided indices that supported the classification of age and physical activity, but not sex.
Why the study?
Wearable photoplethysmogram signals contain rich cardiovascular information beyond heart rate and oxygen saturation, but effective signal-processing methods to extract these biomarkers need evaluation.
Can fiducial point analysis and Symmetric Projection Attractor Reconstruction of photoplethysmogram signals classify individuals by age, sex, and physical activity?
Observational (n=58)
Can fiducial point analysis and Symmetric Projection Attractor Reconstruction of photoplethysmogram signals classify individuals by age, sex, and physical activity?
Advanced signal processing of photoplethysmogram waveforms using fiducial point analysis and Symmetric Projection Attractor Reconstruction can extract cardiovascular biomarkers capable of classifying age and physical activity.
May enable richer wearable PPG biomarkers; leaves open prospective validation before clinical adoption.
Introduction Photoplethysmogram signals from wearable devices typically measure heart rate and blood oxygen saturation, but contain a wealth of additional information about the cardiovascular system. In this study, we compared two signal-processing techniques: fiducial point analysis and Symmetric Projection Attractor Reconstruction, on their ability to extract new cardiovascular information from a photoplethysmogram signal. The aim was to identify fiducial point analysis and Symmetric Projection Attractor Reconstruction indices that could classify photoplethysmogram signals, according to age, sex and physical activity. Methods Three datasets were used: an in-silico dataset of simulated photoplethysmogram waves for healthy male participants (25–75 years old); an in-vivo dataset containing 10-min photoplethysmogram recordings from 57 healthy subjects at rest (18–39 or > 70 years old; 53% female); and an in-vivo dataset containing photoplethysmogram recordings collected for 4 weeks from a single subject, in daily life. The best-performing indices from the in-silico study (5/48 fiducial point analysis and 6/49 Symmetric Projection Attractor Reconstruction) were applied to the in-vivo datasets. Results Key fiducial point analysis and Symmetric Projection Attractor Reconstruction indices, which showed the greatest differences between groups, were found to be consistent across datasets. These indices were related to systolic augmentation, diastolic peak positioning and prominence, and waveform variability. Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques provided indices that supported the classification of age and physical activity, but not sex. Conclusions Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques demonstrated utility in identifying cardiovascular differences between individuals and within an individual over time. Future research should investigate the potential utility of these techniques for extracting information on fitness and disease, to support healthcare-decision making.
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Mathieu et al. (2024) conducted an observational in Healthy (n=58). Fiducial point analysis and Symmetric Projection Attractor Reconstruction was evaluated on Classification of photoplethysmogram signals according to age, sex and physical activity. Fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques provided indices that supported the classification of age and physical activity, but not sex.
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