Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate - blood pressure coupling quantified by entropy-based indices

Paweł Pilarczyk, Grzegorz Graff, José M. Amigó, Katarzyna Tessmer, Krzysztof Narkiewicz +1 more
11/4/2023
physics.med-phcs.LG

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Abstract

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 the 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.

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Cite this paper

@article{pilarczyk2023differentiating,
  title  = {Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate - blood pressure coupling quantified by entropy-based indices},
  author = {Paweł Pilarczyk and Grzegorz Graff and José M. Amigó and Katarzyna Tessmer and Krzysztof Narkiewicz and Beata Graff},
  year   = {2023},
  eprint = {2311.10752},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2311.10752v1}
}

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