Abstract
Multiscale entropy is successfully used to measure dynamical complexity of a finite length time series of different physiological data, including the heart rate. It is shown that the multiscale entropy as a measure can be used to discriminate healthy subjects from subjects with pathological conditions. In this paper we evaluate possibility to apply multiscale entropy to shorter heart rate time series and to evaluate resources needed to implement the algorithm in C, and to assess if it is possible to run the algorithm on a specific DSP platform.
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Dragojevic, B., Boskovic, D. (2020). Evaluating MSE Applicability to Short HR Time-Series. In: Badnjevic, A., Škrbić, R., Gurbeta Pokvić, L. (eds) CMBEBIH 2019. CMBEBIH 2019. IFMBE Proceedings, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-030-17971-7_13
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DOI: https://doi.org/10.1007/978-3-030-17971-7_13
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