Quantifying changes in size of arrhythmic photoplethysmography waveforms during a Valsalva maneuver for assessing cardiac filling pressure

Harry A. Silber, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
Theingi Tiffany Win, Division of Cardiology, Kern Medical Foundation, Bakersfield, CA, United States of America.
Jennifer Monti, Division of Cardiovascular Disease, Maine Medical Center, Scarborough, ME, United States of America.
Panagis Galiatsatos, Division of Pulmonary & Critical Care, Dept. of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.

Abstract

OBJECTIVE: We previously showed that the change in amplitude of a finger photoplethysmography waveform during the Valsalva maneuver reflects cardiac filling pressure. However, the automated determination of peaks and valleys to calculate amplitude is limited in significant arrhythmias such as atrial fibrillation and premature ventricular complexes, which are common in heart failure. The purpose of this study was to assess the change in size of the waveform by calculating the change in root mean square (RMS) of the signal, thereby utilizing the entire cardiac cycle, and to compare it to change in size of peak-to-valley amplitude. APPROACH: We compared the two approaches in signals obtained from participants of a prior study who were tested prior to a clinically indicated cardiac catheterization. Correlation between the two methods was assessed in cases without, and then with, significant arrhythmias including atrial fibrillation or premature ventricular complexes. MAIN RESULTS: Calculations from the two methods of peak-valley amplitude and RMS were highly correlated with each other in signals without (0.99, p < 0.0001, n = 252) and with significant arrhythmias (0.90, p < 0.0001, n = 34). SIGNIFICANCE: RMS analysis of photoplethysmography signal size during the Valsalva maneuver is highly correlated with the method of analyzing changes in peak-valley amplitude, but does not rely on identifying peaks and valleys. The RMS method may be a more robust automated method of assessing cardiac filling pressure in patients with significant arrhythmias.