Self-Similarity in the Heartbeat Time Series of Healthy Cardiac Systems in Mice
Márquez, Aylin S.
Márquez, Aylin S.
Abstract
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This study examined whether fractal dynamics in physiology may explain hidden information in physiologic time series and provide new approaches to monitor cardiac disease. It was hypothesized that self-similarity, which was displayed in fractal geometry, was observed in the cardiac interbeat series. Our method used physiologic data and readings from a dynamical self-test to illustrate the output of healthy cardiac systems. These illustrations of healthy systems were compared with fractal geometry. The applications of fractals were analyzed using open-source data and algorithms such as the Detrended Fluctuation Analysis (DFA) Algorithm. It was concluded that self-similarity was displayed in the healthy heart rate, and the DFA analysis was able to detect irregularity in a disease model. This study potentially could be used to enhance understanding and predicting possible applications of fractal dynamics to a variety of biomedical problems.
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University of Wyoming Libraries