| Autor: |
Pilarczyk, Paweł, Graff, Grzegorz, Amigó, José M., Tessmer, Katarzyna, Narkiewicz, Krzysztof, Graff, Beata |
| Předmět: |
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| Zdroj: |
Chaos; Oct2023, Vol. 33 Issue 10, p1-13, 13p |
| Abstrakt: |
We introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset of indices most suitable for our classification problem in order to build an optimal yet simple model for distinguishing between patients suffering from obstructive sleep apnea and a control group. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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