Abstract

Aim. Previous studies have described the substantial impact of different types of noise on the linear behaviour of heart rate variability (HRV). Yet, there are limited studies about the complexity or nonlinear dynamics of HRV during exposure to traffic noise. Here, we evaluated the complexity of HRV during traffic noise exposure via six power spectra and, when adjusted by the parameters of the Multi-Taper Method (MTM).Material and methods. We analysed 31 healthy female students between 18 and 30 years old. Subjects remained at rest, seated under spontaneous breathing for 20 minutes with an earphone turned off and then the volunteers were exposed to traffic noise through an earphone for a period of 20 minutes. The traffic noise was recorded from a busy urban street and the sound involved car, bus, trucks engineers and horn sounds (71-104 dB).Results. The results stipulate that CFP3 and CFP6 are the best metrics to distinguish the two groups. The most appropriate power spectra were, Welch and MTM. Increasing the DPSS parameter of MTM increased the performance of both CFP3 and CFP6 as mathematical markers. Adaptive was the preferred type for Thomson’s nonlinear combination method.Conclusion. CFP3 with the adaptive option for MTM, and increased DPSS is designated as the best mathematical marker on the basis of five statistical tests.

Highlights

  • ANOVA1, Kruskal-Wallis & Effect Sizes We have computed the seven permutations of the three chaotic globals CFP1 to CFP7 for 31 female subjects; both controls and those exposed to traffic noise via the earphone

  • All CFP3 and CFP6 for Welch, Multi-Taper Method (MTM), Covariance, Burg, Yule-Walker and Periodogram have similar reponses. They have a p

  • With MTM and Welch power spectra there are significant results for CFP2 (p

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Summary

Objectives

We aimed to evaluate nonlinear HRV through chaotic global analysis during exposure to traffic noise

Methods
Results
Conclusion
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