Indirect Measurement of Arterial Pressure by Means of Heart Rate Variability Signals

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@InProceedings{Dolganov:2019:USBEREIT,

• author = "Anton Dolganov",
• booktitle = "2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)",
• title = "Indirect Measurement of Arterial Pressure by Means of Heart Rate Variability Signals",
• year = "2019",
• pages = "156--158",
• month = apr,
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/USBEREIT.2019.8736632",
• abstract = "The article tests possibility of the indirect arterial pressure measurement by means of heart rate variability features. DEAP computational network was used as a tool for genetic programming for symbolic regression. Preliminary results have shown that on the one hand, the error of arterial pressure prediction is rather high. On the other hand, heart rate variability features can be used to predict change of the arterial pressure with relatively low error. Perspectives and future plans were described.",
• notes = "Also known as \cite{8736632}",

}

Genetic Programming entries for Anton Dolganov

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