ESTIMATING THE COMPLEXITY OF HEART RATE FLUCTUATIONS — AN APPROACH BASED ON COMPRESSION ENTROPY

Heart rate exhibits spontaneous fluctuations that are mainly modulated by control loops within the autonomic nervous system. Assessing the dynamics of heart rate fluctuations can provide valuable information about regulatory processes and patho-physiological behavior. In this paper heart rate fluctuations and its entropy are assessed using an algorithmic information theoretic concept applying a data compressor. First, the beat-to-beat fluctuations of heart rate are binary coded for decreases and increases, respectively. Subsequently, those symbol sequences are compressed using the LZ77 algorithm. The ratio of the length of the compressed sequences to the original length is used as an estimate of entropy. We investigated the compressibility of heart rate fluctuations in athletes before, during, and after a training camp. Heart rate time series were obtained from ECGs recorded over 30 minutes under supine resting conditions. We found a significant entropy reduction during the training camp, reflecting the effects of physical fatigue. In conclusion, the compression entropy seems to be a suitable approach to assess the complexity of heart rate fluctuations.

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Heart Rate Signal Decomposition

Methods of Information in Medicine ◽

10.1055/s-0038-1634264 ◽

2000 ◽

Vol 39 (02) ◽

pp. 200-203

Author(s):

H. Mizuta ◽

K. Yana

Keyword(s):

Blood Pressure ◽

Heart Rate ◽

Pressure Change ◽

Normal Subjects ◽

Signal Decomposition ◽

Large Individual ◽

Heart Rate Fluctuations ◽

Type Pattern ◽

Signal Cancellation ◽

Pressure Changes

Abstract:This paper proposes a method for decomposing heart rate fluctuations into background, respiratory and blood pressure oriented fluctuations. A signal cancellation scheme using the adaptive RLS algorithm has been introduced for canceling respiration and blood pressure oriented changes in the heart rate fluctuations. The computer simulation confirmed the validity of the proposed method. Then, heart rate fluctuations, instantaneous lung volume and blood pressure changes are simultaneously recorded from eight normal subjects aged 20-24 years. It was shown that after signal decomposition, the power spectrum of the heart rate showed a consistent monotonic 1/fa type pattern. The proposed method enables a clear interpretation of heart rate spectrum removing uncertain large individual variations due to the respiration and blood pressure change.

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Estimation of Heart Rate Variability Fluctuations by Wavelet Transform

International Journal of Electronics and Telecommunications ◽

10.2478/v10177-011-0054-3 ◽

2011 ◽

Vol 57 (3) ◽

pp. 395-400 ◽

Cited By ~ 5

Author(s):

Anton Popov ◽

Yevgeniy Karplyuk ◽

Volodymyr Fesechko

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Wavelet Transform ◽

Experimental Results ◽

Dyadic Wavelet ◽

Heart Rate Fluctuations ◽

Slow Heart Rate ◽

Dyadic Wavelet Transform

Estimation of Heart Rate Variability Fluctuations by Wavelet TransformTechnique for separate estimation of fast and slow fluctuations in the heart rate signal is developed. The orthogonal dyadic wavelet transform is used to separate the slow heart rate changes in approximation part of decomposition and fast changes in detail parts. Experimental results using the recordings from persons practicing Chi meditation demonstrated the applicability of estimation heart rate fluctuations with the proposed approach.

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AN ALGORITHMIC INFORMATION THEORETIC APPROACH TO THE BEHAVIOUR OF FINANCIAL MARKETS

Journal of Economic Surveys ◽

10.1111/j.1467-6419.2010.00666.x ◽

2011 ◽

Vol 25 (3) ◽

pp. 431-463 ◽

Cited By ~ 10

Author(s):

Hector Zenil ◽

Jean-Paul Delahaye

Keyword(s):

Financial Markets ◽

Theoretic Approach ◽

Information Theoretic ◽

Algorithmic Information ◽

Information Theoretic Approach

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Symmetry and Correspondence of Algorithmic Complexity over Geometric, Spatial and Topological Representations

Entropy ◽

10.3390/e20070534 ◽

2018 ◽

Vol 20 (7) ◽

pp. 534 ◽

Cited By ~ 1

Author(s):

Hector Zenil ◽

Narsis Kiani ◽

Jesper Tegnér

Keyword(s):

Algorithmic Complexity ◽

Information Theoretic ◽

Algorithmic Probability ◽

Graphs And Networks ◽

Algorithmic Information ◽

Statistical Regularities ◽

Review Study ◽

Causal Nature ◽

Definition Of

We introduce a definition of algorithmic symmetry in the context of geometric and spatial complexity able to capture mathematical aspects of different objects using as a case study polyominoes and polyhedral graphs. We review, study and apply a method for approximating the algorithmic complexity (also known as Kolmogorov–Chaitin complexity) of graphs and networks based on the concept of Algorithmic Probability (AP). AP is a concept (and method) capable of recursively enumerate all properties of computable (causal) nature beyond statistical regularities. We explore the connections of algorithmic complexity—both theoretical and numerical—with geometric properties mainly symmetry and topology from an (algorithmic) information-theoretic perspective. We show that approximations to algorithmic complexity by lossless compression and an Algorithmic Probability-based method can characterize spatial, geometric, symmetric and topological properties of mathematical objects and graphs.

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