1 Heart rate variability in the acceleration photoplethysmogram at rest and after exercise—a preliminary study Mohamed Elgendi 1,* , Socrates Dokos 2 , Derek Abbott 3 1 Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada 2 Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia 3 School of Electrical and Electronic Engineering, University of Adelaide, Adelaide, South Australia, Australia * E-mail: moe.elgendi@gmail.com Abstract There are a limited number of studies on heart rate variability (HRV) dynamics immediately after exer- cise. The electrocardiogram (ECG) may be used to measure HRV, however acquiring ECG signals from subjects undergoing exercise is not convenient. Many researchers have demonstrated that photoplethys- mogram (PPG) signals offer an alternative method to measure HRV when ECG and PPG signals are simultaneously collected. However, we investigate a different approach to potentially show that the PPG signals can measure HRV without collecting ECG signals. Moreover, we explore the extraction of the most suitable HRV-parameters from short PPG signal recordings. Our preliminary results now motivate further studies that cross check HRV parameters extracted from both ECG and PPG. In this study, PPG signals from an existing database were used to determine a range of HRV indices, including the standard deviation of heart beat interval (SDNN) and the root-mean square of the difference of successive heart beats (rMSSD). Results from this study indicate that the use of the a–a interval, derived from the ac- celeration of PPG signals, show very promising results in determining the HRV statistical indices SDNN and rMSSD over 20-second PPG recordings. Moreover, post-exercise SDNN and rMSSD indices show negative correlation with age.