Reliability of resting-state photoplethysmogram-based pulse rate variability in lifespan samples: Implications for cardiovascular research.

OBJECTIVE: Pulse rate variability (PRV), derived from photoplethysmography, offers a scalable approach to studying cardiac autonomic regulation. However, the reliability of PRV measures across human lifespan has not been systematically evaluated, limiting their application in cardiovascular research. Approach: Pulse wave data of 914 healthy young subjects from the Human Connectome Project (HCP) young adults were analyzed. PRV was derived from four 15-minute resting-state fMRI sessions using NeuroKit2. Test-retest reliability of 86 PRV metrics across time, frequency, and nonlinear domains was assessed using intraclass correlation coefficients (ICCs). Findings were validated in independent developmental (HCP-D; n=536; ages 5-21) and aging (HCP-A; n=652; ages 36-100+) cohorts to evaluate lifespan generalizability. Sex-specific and race-specific analyses were also performed. Main Results: We analyzed 914 healthy young adults (mean age 28.7±3.7 years; n=489, 53.5% female), of whom 75.6% self-identified as White, 13.1% as African American, and 11.3% as Other. Of 86 PRV metrics, 62 (72.1%) showed excellent reliability (ICC ≥ 0.75) across both days, with higher stability within-day than across days. Time-domain measures (e.g., Prc80NN, pNN20, MeanNN, MedianNN) and nonlinear measures (e.g., ShanEN, IALS, and PSS) were highly reliable with ICC ≥ 0.90. In the frequency domain, HFn and LFn performed best (ICC ≥ 0.85). The reliability patterns were highly consistent across developing and aging cohorts and did not significantly differ across Sex and race subgroups among highly reliable PRVs. Significance: A substantial proportion of PRV metrics showed excellent reliability across the lifespan, with broadly similar patterns across sex and racial groups, supporting their use in research settings.