Publications Repository - Gdańsk University of Technology

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.

Authors

• dr hab. Paweł Pilarczyk link open in new tab ,
• prof. dr hab. Grzegorz Graff link open in new tab ,
• Jose Amigo link open in new tab ,
• mgr inż. Katarzyna Tessmer link open in new tab ,
• Krzysztof Narkiewicz link open in new tab ,
• Krzysztof Narkiewicz,
• Beata Graff