2002Unpublished venueRequires access

On the presence of deterministic chaos in HRV signals

Ivana Đaković Radojičić, Danilo P. Mandic, D. Vulic

Open publisher page 6 citations

Abstract

The presence of deterministic chaos in the instantaneous heart rate variability (HRV) signal is investigated by the reconstruction of a multi-dimensional signal using a time-delay embedding method. Four methods (autocorrelation, mutual information, average displacement and visual attractor inspection) are used to determine the time-delay parameter. The dimensionality of the embedding is tested using the nearest-neighbour and correlation-dimension methods, including a surrogate data test for the correlation dimension. An analysis is also performed for calculating the largest Lyapunov exponents. The results obtained in the time-delay embedding process support the conclusion that the HRV series could be chaotic.

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What this paper is about

The presence of deterministic chaos in the instantaneous heart rate variability (HRV) signal is investigated by the reconstruction of a multi-dimensional signal using a time-delay embedding method. Four methods (autocorrelation, mutual information, average displacement and visual attractor inspection) are used to determine the time-delay parameter. The dimensionality of the embedding is tested using the nearest-neighbour and correlation-dimension methods, including a surrogate data test for the correlation dimension. An analysis is also performed for calculating the largest Lyapunov exponents. The results obtained in the time-delay embedding process support the conclusion that the HRV series could be chaotic.

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Available abstract

The presence of deterministic chaos in the instantaneous heart rate variability (HRV) signal is investigated by the reconstruction of a multi-dimensional signal using a time-delay embedding method. Four methods (autocorrelation, mutual information, average displacement and visual attractor inspection) are used to determine the time-delay parameter. The dimensionality of the embedding is tested using the nearest-neighbour and correlation-dimension methods, including a surrogate data test for the correlation dimension. An analysis is also performed for calculating the largest Lyapunov exponents. The results obtained in the time-delay embedding process support the conclusion that the HRV series could be chaotic.

Key concepts: Correlation dimension, Autocorrelation, Surrogate data, Attractor, Lyapunov exponent, Dimension (graph theory), Embedding, Series (stratigraphy)

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