Intrinsic Frequency Analysis and Fast Algorithms

Abstract Intrinsic Frequency (IF) has recently been introduced as an ample signal processing method for analyzing carotid and aortic pulse pressure tracings. The IF method has also been introduced as an effective approach for the analysis of cardiovascular system dynamics. The physiological signific...

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Autores principales:	Peyman Tavallali, Hana Koorehdavoudi, Joanna Krupa
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1e540ef1dff347749ff3ccbf6daf8781
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spelling	oai:doaj.org-article:1e540ef1dff347749ff3ccbf6daf87812021-12-02T15:08:06ZIntrinsic Frequency Analysis and Fast Algorithms10.1038/s41598-018-22907-42045-2322https://doaj.org/article/1e540ef1dff347749ff3ccbf6daf87812018-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-22907-4https://doaj.org/toc/2045-2322Abstract Intrinsic Frequency (IF) has recently been introduced as an ample signal processing method for analyzing carotid and aortic pulse pressure tracings. The IF method has also been introduced as an effective approach for the analysis of cardiovascular system dynamics. The physiological significance, convergence and accuracy of the IF algorithm has been established in prior works. In this paper, we show that the IF method could be derived by appropriate mathematical approximations from the Navier-Stokes and elasticity equations. We further introduce a fast algorithm for the IF method based on the mathematical analysis of this method. In particular, we demonstrate that the IF algorithm can be made faster, by a factor or more than 100 times, using a proper set of initial guesses based on the topology of the problem, fast analytical solution at each point iteration, and substituting the brute force algorithm with a pattern search method. Statistically, we observe that the algorithm presented in this article complies well with its brute-force counterpart. Furthermore, we will show that on a real dataset, the fast IF method can draw correlations between the extracted intrinsic frequency features and the infusion of certain drugs.Peyman TavallaliHana KoorehdavoudiJoanna KrupaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-14 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Peyman Tavallali Hana Koorehdavoudi Joanna Krupa Intrinsic Frequency Analysis and Fast Algorithms
description	Abstract Intrinsic Frequency (IF) has recently been introduced as an ample signal processing method for analyzing carotid and aortic pulse pressure tracings. The IF method has also been introduced as an effective approach for the analysis of cardiovascular system dynamics. The physiological significance, convergence and accuracy of the IF algorithm has been established in prior works. In this paper, we show that the IF method could be derived by appropriate mathematical approximations from the Navier-Stokes and elasticity equations. We further introduce a fast algorithm for the IF method based on the mathematical analysis of this method. In particular, we demonstrate that the IF algorithm can be made faster, by a factor or more than 100 times, using a proper set of initial guesses based on the topology of the problem, fast analytical solution at each point iteration, and substituting the brute force algorithm with a pattern search method. Statistically, we observe that the algorithm presented in this article complies well with its brute-force counterpart. Furthermore, we will show that on a real dataset, the fast IF method can draw correlations between the extracted intrinsic frequency features and the infusion of certain drugs.
format	article
author	Peyman Tavallali Hana Koorehdavoudi Joanna Krupa
author_facet	Peyman Tavallali Hana Koorehdavoudi Joanna Krupa
author_sort	Peyman Tavallali
title	Intrinsic Frequency Analysis and Fast Algorithms
title_short	Intrinsic Frequency Analysis and Fast Algorithms
title_full	Intrinsic Frequency Analysis and Fast Algorithms
title_fullStr	Intrinsic Frequency Analysis and Fast Algorithms
title_full_unstemmed	Intrinsic Frequency Analysis and Fast Algorithms
title_sort	intrinsic frequency analysis and fast algorithms
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/1e540ef1dff347749ff3ccbf6daf8781
work_keys_str_mv	AT peymantavallali intrinsicfrequencyanalysisandfastalgorithms AT hanakoorehdavoudi intrinsicfrequencyanalysisandfastalgorithms AT joannakrupa intrinsicfrequencyanalysisandfastalgorithms
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Intrinsic Frequency Analysis and Fast Algorithms

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