  Photoplethysmographic Imaging (PPGI) allows the determination of pulse rate
variability from sequential beat-to-beat intervals (BBI) and pulse wave
velocity from spatially resolved recorded pulse waves. In either case,
sufficient temporal accuracy is essential.
  The presented work investigates the temporal accuracy of BBI estimation from
photoplethysmographic signals. Within comprehensive numerical simulation, we
systematically assess the impact of sampling rate, signal-to-noise ratio (SNR),
and beat-to-beat shape variations on the root mean square error (RMSE) between
real and estimated BBI.
  Our results show that at sampling rates beyond 14 Hz only small errors exist
when interpolation is used. For example, the average RMSE is 3 ms for a
sampling rate of 14 Hz and an SNR of 18 dB. Further increasing the sampling
rate only results in marginal improvements, e.g. more than tripling the
sampling rate to 50 Hz reduces the error by approx. 14%. The most important
finding relates to the SNR, which is shown to have a much stronger influence on
the error than the sampling rate. For example, increasing the SNR from 18 dB to
24 dB at 14 Hz sampling rate reduced the error by almost 50% to 1.5 ms. Subtle
beat-to-beat shape variations, moreover, increase the error decisively by up to
800%.
  Our results are highly relevant in three regards: first, they partially
explain different results in the literature on minimum sampling rates. Second,
they emphasize the importance to consider SNR and possibly shape variation in
investigations on the minimal sampling rate. Third, they underline the
importance of appropriate processing techniques to increase SNR. Importantly,
though our motivation is PPGI, the presented work immediately applies to
contact PPG and PPG in other settings such as wearables. To enable further
investigations, we make the scripts used in modelling and simulation freely
available.
