Hypnodensity sleep metrics from fingertip photoplethysmography are better associated with daytime sleepiness and fatigue than traditional metrics from polysomnography

Clinical Snapshot

Key Findings

• P Value: p < 0.005 for N1/N3 hypnodensities vs traditional metrics; p < 0.01 for multiple PPG metrics in multivariable analysis

• Effect Size: PPG-based N1 and N3 hypnodensities showed stronger associations than traditional metrics

• Primary Outcome: Correlation between sleep metrics and patient-reported daytime fatigue and sleepiness

• Nnt Or Sensitivity: Correlation strength not quantified in abstract

• Confidence Interval: Not reported in abstract

Clinical Application

High - fingertip PPG is non-invasive, portable, and could enable home-based sleep quality monitoring Relevant to Australian sleep medicine practice; could reduce reliance on limited sleep laboratory resources and support telehealth initiatives aligned with Medicare Benefits Schedule reforms Patients with suspected or confirmed sleep-disordered breathing undergoing sleep assessment

Abstract

BACKGROUND: Traditional sleep metrics from polysomnography are often limited by the hypnogram, in which each 30-s epoch is classified into one of the five sleep stages. This oversimplifies sleep stage continuity and fragmented sleep, typical in sleep-disordered breathing (SDB). Deep learning offers more dynamic sleep modelling with a higher temporal resolution by providing probabilities for each sleep stage, known as hypnodensities. RESEARCH QUESTION AND METHODS: We investigated whether high-frequency (1/s) hypnodensities captured from nocturnal fingertip photoplethysmography (PPG) recordings better correlate with patient-reported outcomes in SDB than traditional metrics. RESULTS: Among 2,280 patients (65% male, mean age 62 years, mean apnoea-hypopnoea index (AHI) 23.5/h), we found that several PPG-derived hypnodensity metrics correlate with self-reported daytime fatigue and sleepiness. The level of correlation was better or similar compared to traditional hypnogram-based sleep metrics derived from manually scored polysomnography. Specifically, PPG-based hypnodensities for N1 and N3 sleep showed a stronger association (p < 0.005) with fatigue and sleepiness than manually scored N1 and N3 sleep. Multivariable logistic regression (adjusted for age, sex, body mass index, AHI, and total sleep time below 90% blood oxygen saturation) revealed significant associations (p < 0.01) between multiple PPG-based hypnodensity metrics and daytime sleepiness. CONCLUSION: These findings suggest that PPG-based hypnodensities improve the characterisation of sleep quality and better predict patient-reported outcomes in SDB patients. Future uses may include tracking sleep quality with fingertip pulse oximeters outside of sleep centres, potentially over multiple nights due to their simplicity.

References

1. 1.Rusanen, M., Tuyinsenge, V., Muller, S., Tamisier, R., Baillieul, S., Myllymaa, S., Kainulainen, S., Leppänen, T., Pepin, J. L., & Bailly, S. (2026). Hypnodensity sleep metrics from fingertip photoplethysmography are better associated with daytime sleepiness and fatigue than traditional metrics from polysomnography. Pulmonology. https://doi.org/10.1080/25310429.2026.2683326