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Fractal Analysis and the Effect of Aging on the Heart Rate and Breathing Frequency Relationship

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Part of the Communications in Computer and Information Science book series (CCIS,volume 260)

Abstract

Simultaneous observation of the Electrocardiogram (ECG) and respiratory cycle over long period has been proven clinically useful. Classical methods of analysing time-series, such as time and frequency domain analysis have been widely used in the area of physiological signal analysis. However, such characteristics as mean, standard deviation or location of peaks in the frequency domain are not capable of finding nonlinear relationship between signals. More sophisticated properties are based on estimation of multifractal spectrum. This spectrum is capable of confirming the existence of nonlinear relationships in analysed signals. In this study we estimated the spectrum of scale exponents for heartbeat dynamics and respiration dynamics to investigate the cardiorespiratory relationship under supine resting condition between young and elderly people. Using two border and one peak scale exponents selected from each spectrum we constructed 3-dimensonal feature space. The distance and the angle of a line connecting features estimated from heartbeat and respiratory dynamics for each patient were calculated and compared in both age group. Analysing the distances and angles we found that in the case of elderly people there is a degradation of long-range dependency in heartbeat dynamics that leads to a large difference between dynamics of respiratory and heartbeat dynamics. On the other hand in the case of young people there is no significant difference between heartbeat and respiratory dynamics, which implies a possibility of existence of a nonlinear relationship between cardiac and respiratory systems in young people.

Keywords

  • heartbeat
  • respiration
  • dynamics
  • fractal

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Bucaoto, W., Kim, H.J., Lenskiy, A. (2011). Fractal Analysis and the Effect of Aging on the Heart Rate and Breathing Frequency Relationship. In: Kim, Th., Adeli, H., Ramos, C., Kang, BH. (eds) Signal Processing, Image Processing and Pattern Recognition. SIP 2011. Communications in Computer and Information Science, vol 260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27183-0_46

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  • DOI: https://doi.org/10.1007/978-3-642-27183-0_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27182-3

  • Online ISBN: 978-3-642-27183-0

  • eBook Packages: Computer ScienceComputer Science (R0)