Multifractal Behaviour of Respiratory Signals

In this study, to analyze the biomedical signals emerging from fractal structures in the human body, fractal analysis was used. Respiratory signals, such as airflow, mouth pressure, and lung volume, comprise a complex relationship that has not been inspected to date. Furthermore, the mechanism for which it is linked to the lung’s fractal structure has not been scrutinized to date. Thus, using a well-known method, known as multifractal detrended fluctuation analysis (MF-DFA), this study aims to determine both mono- and multi-fractal property of respiratory signals ,. The real signals were analyzed using the MF-DFA algorithm. Moreover, for different scales, generalized Hurst exponent values were calculated. The results demonstrated that respiratory signals are fractional Brown motion-type signals, whereas fractal properties demonstrate less intersubject change. Moreover, in addition to both airflow and lung volume, respiratory signals and sounds are multifractal signals. In conclusion, the presence of the lung’s long-memory property is the primary reason of multifractality.

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1. P. Castiglioni, G. Parati, A. Civijian, L. Quintin and M. Di Rienzo, "Local Scale Exponents of Blood Pressure and Heart Rate Variability by Detrended Fluctuation Analysis", IEEE Trans Biomed Eng, vol. 56, no. 3, pp. 675-684, 2009.

2. D. Abasolo, R. Horneo, J. Escudero and P. Espino, "A study on the Possible Usefulness of Detrended Fluctuation Analysis of the Electroencephalogram Background Activity in Alzheimer’s disease", IEEE Trans Biomed Eng, vol. 55, no.9, pp. 2171-2179, 2008.

3. S. Chatterjee, S. Pratiher, R. Bose, "Multifractal Detrended Fluctuation Analysis Based Novel Feature Extraction Technique for Autometed Detection of Focal and Non-Focal Electroencephalogram Signals", IET Sci Meas Technol, vol. 11, no. 8, pp. 1014-1021, 2017.

4. S. P. Chakravarty, S. Chakraborty, "Fractal analysis related to tumour growth in lungs: a review", 2017 Fourth International Conference on Image Information Processing (ICIIP), India, 2017, pp. 422-425.

5. J. Gnitecki, Z. Moussavi, "The fractality of lung sounds: a comparison of three waveform fractal dimension algorithms", Chaos Solitons Fractals, vol. 26, pp. 1065-1072, 2005.

6. C. M. Ionescu, W. Kosinski, R. De Keyser, "Viscoelasticity and fractal structure in a model of human lungs", Arch Mech, vol. 97, pp. 21- 48, 2010.

7. K. L. Uahabi and M. Atounti, "New approach to the calculation of fractal dimension of the lungs", Annals Unive. Craiova, Mathe and Comp. Scie, vol. 44, no. 1, pp. 78-86, 2017.

8. A. Rizal, R. Hidayat and H. A. Nugroho, "Fractal Dimension for lung sound classification in multiscale scheme", J Comp. Scie, vol. 14, no. 8, pp. 1081-1096, 2018.

9. J. Gnitecki, Z. Moussavi, H. Pasterkamp, "Classification of lung sounds during bronchial provocation using waveform fractal dimensions", 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, USA, 2004, pp. 1-4.

10. L. J. Hadjileontiadis, I. T. Rekanos, "Detection of explosive lung and bowel Sounds by means of fractal dimension", IEEE Sig Proce Letters, vol. 10, no. 10, pp. 311-314, 2003.

11. M. Akay, E. H. Mulder, "Effects of maternal alcohol intake on fractal properties in human fetal breathing dynamics, IEEE Trans Biomed Eng, vol. 45, no. 9, pp. 1097-1102, 1998.

12. J. Gnitecki, Z. Moussavi, "Variance fractal dimension trajectory as a tool for heart sound localization in lung sounds recordings", 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, Mexico, 2003, pp. 2420- 2423.

13. J. W. Kantelhardt, S. A. Zschiegner, E. Koscielny-Bunde, S. Havlin, A. Bunde and H. E. Stanley, "Multifractal detrended fluctuation analysis of nonstationary time series", Physica A, vol. 316, pp. 87-114, 2002.

14. E. A. F. Ihlen, "Introduction to multifractal detrended fluctuation analysis in Matlab", Front Physiol, vol. 3, no. 141, pp. 1-18, 2012.

15. E. Saatci, "Correlation analysis of respiratory signals by using parallel coordinate plots", Comp Method and Prog in Biomed, vol. 153, pp. 41-51, 2018.