Efficient noise-tolerant estimation of heart rate variability using single-channel photoplethysmography

The feasibility of using photoplethysmography (PPG) for estimating heart rate variability (HRV) has been the subject of many recent studies with contradicting results. Accurate measurement of cardiac cycles is more challenging in PPG than ECG due to its inherent characteristics.

We developed a PPG-only algorithm by computing a robust set of medians of the interbeat intervals between adjacent peaks, upslopes, and troughs. Abnormal intervals are detected and excluded by applying our criteria.

We tested our algorithm on a large database from high-risk ICU patients containing arrhythmias and significant amounts of artifact. The average difference between PPG-based and ECG-based parameters is <1% for pNN50, <1bpm for meanHR, <1ms for SDNN, <3ms for meanNN, and <4ms for SDSD and RMSSD.

Our performance testing shows that the pulse rate variability (PRV) parameters are comparable to the HRV parameters from simultaneous ECG recordings.