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A novel algorithm using wavelet transforms can generate realistic HRV records for use in clinical statistics.
In the paper is described an algorithm for generating of realistic Heart Rate Variability (HRV) records. In the mathematical model are used two Gaussian distributions and wavelet transforms for generating a typical heart rate time series. The Respiratory Sinus Arrhythmia (RSA) and Mayer waves are incorporated in the proposed model. The obtained results show that the algorithm could be applied to clinical statistics based on HRV signals recorded by the patients.
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Georgieva-Tsaneva et al. (2012) studied this question.
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