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SAPPHIRE: Stochastically acquired photoplethysmogram for heart rate inference in realistic environments

A novel method, Stochastically Acquired Photoplethysmo-gram for Heart rate Inference in Realistic Environments (SAPPHIRE), is proposed for robust remote heart rate measurement through broadband video. A set of stochastically sampled points from the cheek region is tracked and used to construct corresponding time series observations via skin erythema transforms. From these observations, a photo-plethysmogram (PPG) waveform is estimated via Bayesian minimization, with the required posterior probability inferred using a Monte Carlo approach. To mitigate the effects of noise, the contribution of each observation is weighted based on the observation's likelihood to contain relevant data. A bandpass filter is applied to the estimated PPG waveform to omit implausible heart rate frequencies, and the heart rate is estimated through frequency domain analysis. Experimental results acquired from a set of thirty videos indicate significantly improved performance in comparison to state-of-the-art methods.