dorsal/arxiv
View SchemaRecurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data
| Authors | N. Marwan, N. Wessel, U. Meyerfeldt, A. Schirdewan, J. Kurths |
|---|---|
| Categories | |
| ArXiv ID | physics/0201064 |
| URL | https://arxiv.org/abs/physics/0201064 |
| DOI | 10.1103/PhysRevE.66.026702 |
| Journal | Physical Review E, 66(2), 2002, 026702 |
Abstract
The knowledge of transitions between regular, laminar or chaotic behavior is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods which however require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart rate variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e. chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our new measures to the heart rate variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.
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"abstract": "The knowledge of transitions between regular, laminar or chaotic behavior is\nessential to understand the underlying mechanisms behind complex systems. While\nseveral linear approaches are often insufficient to describe such processes,\nthere are several nonlinear methods which however require rather long time\nobservations. To overcome these difficulties, we propose measures of complexity\nbased on vertical structures in recurrence plots and apply them to the logistic\nmap as well as to heart rate variability data. For the logistic map these\nmeasures enable us not only to detect transitions between chaotic and periodic\nstates, but also to identify laminar states, i.e. chaos-chaos transitions. The\ntraditional recurrence quantification analysis fails to detect the latter\ntransitions. Applying our new measures to the heart rate variability data, we\nare able to detect and quantify the laminar phases before a life-threatening\ncardiac arrhythmia occurs thereby facilitating a prediction of such an event.\nOur findings could be of importance for the therapy of malignant cardiac\narrhythmias.",
"arxiv_id": "physics/0201064",
"authors": [
"N. Marwan",
"N. Wessel",
"U. Meyerfeldt",
"A. Schirdewan",
"J. Kurths"
],
"categories": [
"physics.med-ph",
"nlin.CD",
"physics.data-an",
"q-bio.QM"
],
"doi": "10.1103/PhysRevE.66.026702",
"journal_ref": "Physical Review E, 66(2), 2002, 026702",
"title": "Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data",
"url": "https://arxiv.org/abs/physics/0201064"
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