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The Poincaré plot (PP) is one of the many techniques used for ascertaining the heart rate variability, which in turn is a marker of the activity of the autonomic system. Poincaré plots are very simple to produce, but their preparation involves a few fine points. This paper describes one of them, namely the filtering of data used for the Poincaré plot. We show the correct way of filtering data, present a few results of not filtering or incorrect filtering and demonstrate how proper filtering helps extract interesting information from the data. A few algorithms for preparing Poincaré plots, filtering data and calculating PP descriptors are included. As Matlab’s programming language is the unquestionable standard for data analysis in the medical sciences, we illustrate these algorithms by snippets of code in this language.
Poznań
2005.06.22
eng
Piskorski Jarosław
computer data analysis, nonlinear dynamics, HRV, Poincaré plots
OWN
computer data analysis, nonlinear dynamics, HRV, Poincaré plots
Guzik Przemysław