Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes
Cardiac signals have complex structures representing a combination of simpler structures. In this paper, we develop a new data analytic tool that can extract the complex structures of cardiac signals using the framework of multi-chaotic analysis, which is based on the <i>p</i>-norm for c...
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MDPI AG
2021-01-01
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| Online Access: | https://www.mdpi.com/1099-4300/23/1/112 |
| _version_ | 1797410928999792640 |
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| author | Oleg Gorshkov Hernando Ombao |
| author_facet | Oleg Gorshkov Hernando Ombao |
| author_sort | Oleg Gorshkov |
| collection | DOAJ |
| description | Cardiac signals have complex structures representing a combination of simpler structures. In this paper, we develop a new data analytic tool that can extract the complex structures of cardiac signals using the framework of multi-chaotic analysis, which is based on the <i>p</i>-norm for calculating the largest Lyapunov exponent (<i>LLE</i>). Appling the <i>p</i>-norm is useful for deriving the spectrum of the generalized largest Lyapunov exponents (<i>GLLE</i>), which is characterized by the width of the spectrum (which we denote by <i>W</i>). This quantity measures the degree of multi-chaos of the process and can potentially be used to discriminate between different classes of cardiac signals. We propose the joint use of the <i>GLLE</i> and spectrum width to investigate the multi-chaotic behavior of inter-beat (R-R) intervals of cardiac signals recorded from 54 healthy subjects (hs), 44 subjects diagnosed with congestive heart failure (chf), and 25 subjects diagnosed with atrial fibrillation (af). With the proposed approach, we build a regression model for the diagnosis of pathology. Multi-chaotic analysis showed a good performance, allowing the underlying dynamics of the system that generates the heart beat to be examined and expert systems to be built for the diagnosis of cardiac pathologies. |
| first_indexed | 2024-03-09T04:37:33Z |
| format | Article |
| id | doaj.art-f5a59f7b8df04a30a6a3add057a47a07 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T04:37:33Z |
| publishDate | 2021-01-01 |
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| record_format | Article |
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| spelling | doaj.art-f5a59f7b8df04a30a6a3add057a47a072023-12-03T13:26:29ZengMDPI AGEntropy1099-43002021-01-0123111210.3390/e23010112Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological ClassesOleg Gorshkov0Hernando Ombao1Statistics Program, King Abdullah University of Science and Technology, Thuwal 23955, Saudi ArabiaStatistics Program, King Abdullah University of Science and Technology, Thuwal 23955, Saudi ArabiaCardiac signals have complex structures representing a combination of simpler structures. In this paper, we develop a new data analytic tool that can extract the complex structures of cardiac signals using the framework of multi-chaotic analysis, which is based on the <i>p</i>-norm for calculating the largest Lyapunov exponent (<i>LLE</i>). Appling the <i>p</i>-norm is useful for deriving the spectrum of the generalized largest Lyapunov exponents (<i>GLLE</i>), which is characterized by the width of the spectrum (which we denote by <i>W</i>). This quantity measures the degree of multi-chaos of the process and can potentially be used to discriminate between different classes of cardiac signals. We propose the joint use of the <i>GLLE</i> and spectrum width to investigate the multi-chaotic behavior of inter-beat (R-R) intervals of cardiac signals recorded from 54 healthy subjects (hs), 44 subjects diagnosed with congestive heart failure (chf), and 25 subjects diagnosed with atrial fibrillation (af). With the proposed approach, we build a regression model for the diagnosis of pathology. Multi-chaotic analysis showed a good performance, allowing the underlying dynamics of the system that generates the heart beat to be examined and expert systems to be built for the diagnosis of cardiac pathologies.https://www.mdpi.com/1099-4300/23/1/112Lyapunov exponentchaosR-R interval time serieslogistic regression model |
| spellingShingle | Oleg Gorshkov Hernando Ombao Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes Entropy Lyapunov exponent chaos R-R interval time series logistic regression model |
| title | Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes |
| title_full | Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes |
| title_fullStr | Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes |
| title_full_unstemmed | Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes |
| title_short | Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes |
| title_sort | multi chaotic analysis of inter beat r r intervals in cardiac signals for discrimination between normal and pathological classes |
| topic | Lyapunov exponent chaos R-R interval time series logistic regression model |
| url | https://www.mdpi.com/1099-4300/23/1/112 |
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