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Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive
Abstract
We argue that network methods are successful in detecting nonlinear properties in the dynamics of autonomic nocturnal regulation in short-term variability. Two modes of visualization of networks constructed from RR-increments are proposed. The first is based on the handling of a state space. The state space of RR-increments can be modified by a bin size used to code a signal and by the role of a given vertex as the representation of events occurring in a signal. The second mode relies on the matrix representation of the network on the two-dimensional plane. This approach is similar to the accepted method, known as the Poincaré plot representation of time series for evaluation of heart rate variability. The methods introduced will be applied to nocturnal Holter signals recorded from healthy young people and from cardiac transplant recipients. Thus, we obtain a way to filter out the intrinsic heart rate variability from the autonomic drive and then to quantify complexity in the short-term RR-interval variability related to nocturnal rest. Changes in RR-increments in a heart deprived of autonomic control provide insight into beat-to-beat dependences in forces governing the intrinsic heart dynamics
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Authors (9)
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Danuta Makowiec
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Beata Graff
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Dorota Wejer
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Joanna Wdowczyk-Szulc
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Marta Żarczyńska-Buchowiecka
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Marcin Gruchała prof
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Zbigniew R. Struzik
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Keywords
Details
- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Title of issue:
- W: ECG time series variability analysis: engineering and medicine strony 141 - 157
- Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Makowiec D., Graff B., Kaczkowska A., Graff G., Wejer D., Wdowczyk-Szulc J., Żarczyńska-Buchowiecka M., Gruchała M., Struzik Z.: Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive// ECG Time Series Variability Analysis: Engineering and Medicine/ ed. Herbert F. Jelinek, David J. Cornforth and Ahsan H. Khandoker Boca Raton: Taylor & Francis Group, 2017, s.141-157
- DOI:
- Digital Object Identifier (open in new tab) 10.1201/9781315372921-7
- Verified by:
- Gdańsk University of Technology
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