In this paper, we propose a stochastic model of photoplethysmographic signals that is able to synthesize an arbitrary number of other statistically equivalent signals to the one under analysis. To that end, we first preprocess the pulse signal to normalize and time-align pulses. In a second stage, we design a single-pulse model, which consists of ten parameters. In the third stage, the time evolution of this ten-parameter vector is approximated by means of two autoregressive moving average models, one for the trend and one for the residue; this model is applied after a decorrelation step which let us to process each vector component in parallel. The experiments carried out show that the model we here propose is able to maintain the main features of the original signal; this is accomplished by means of both a linear spectral analysis and also by comparing two measures obtained from a nonlinear analysis. Finally, we explore the capability of the model to: 1) track physical activity; 2) obtain statistics of clinical parameters by model sampling; and 3) recover corrupted or missing signal epochs by synthesis.

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The influence of the cartesian interpolation of ultrasound data over the final image statistical model is studied. When fully formed speckle is considered and no compression of the data is done, we show that the interpolated final image can be modeled following a Gamma distribution, which is a good approximation for the weighted sum of Rayleigh variables. The importance of taking into account the interpolation stage to statistically model ultrasound images is pointed out. The interpolation model here proposed can be easily extended to more complex distributions.

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Abstract. Ubiquitous monitoring has become a useful tool for the prevention and early diagnosis of some disorders. This kind of monitoring has been promoted last years thanks to the irruption of the smartphones, which make easier the collection and delivery of the patient's data. However, there are some problems with the quality of the acquired data. This paper presents a novel methodology in which the shape of PPG beats is recovered through a multistage full-automatic pipeline including shape modeling stage and template-based (template estimated from the surrounding beats) shape recovery through a level-set approach. To validate the proposal, a registry acquired using the camera of a Motorola MotoG has been used. Results can be qualified as promising, since the shape of damaged beats is recovered, however a more comprehensive validation must be addressed.