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Department of Biological and Medical Sciences
Stress induced by driving has been revealed to increase the chances of cardiovascular complications and is involved or related to traffic accidents. In order to develop strategies to avoid health problems during driving we aimed to evaluate the acute effects of auditory stimulation with music on heart rate variability (HRV) during driving in congested urban traffic. This is a prospective cross-sectional randomized controlled pilot study conducted with five healthy women. Subjects were evaluated on two different random days, whose order of execution was established through a randomization process. In the music protocol the volunteers were exposed to music for the entire 20 min of traffic while in the control protocol the subjects performed the same procedures but were not exposed to any music. We noted that all Higuchi fractal dimension parameters except Kmax 10, Kmax 130 and Kmax 140 were reduced between pre-driving in the control protocol vs. driving in the control protocol. The same changes were noted between pre-driving in the music protocol vs. driving in the control protocol. In conclusion, musical auditory stimulation improved nonlinear HRV changes induced by driving.
Cortical auditory evoked potentials (CAEP) throughout a language task is beneficial during psychophysiological evaluation to advance identification of language disorders. So as to better comprehend human communication and to provide additional elements for neuropsychological examinations we aimed to (1) examine the influence of language tasks on cortical auditory processing and vagal control of heart rate and (2) to verify a possible association between the parasympathetic cardiac regulation and cortical auditory processing in language tasks. This study was completed with 49 women. The subjects were separated into two groups: (1) phonological language tasks (N = 21) and (2) semantic (N = 21) language tasks. Heart rate variability (HRV) and CAEP were evaluated before and after the tests. HRV reduced (small effect size) and P3 wave latency increased after the phonological task. Identical variables were significantly correlated after the phonological task and linear regression indicated significant interaction between pNN50 (percentage of adjacent RR intervals with a difference of duration greater than 50 milliseconds) and P3 latency (16.9%). In conclusion, phonological language tasks slightly reduced parasympathetic control of HR and increased cognitive effort. The association between HRV and CAEP are anticipated to be involved in this mechanism.
Numerous studies have investigated the connection between autonomic control of heart rate (HR) and auditory stimulus. Yet, the literature lacks evidence of a close association between auditory brainstem processing and HR autonomic control. We aimed to evaluate and verify the relationship between auditory brainstem response (ABR) and HR variability (HRV) in healthy women. Forty‑six healthy female subjects, between the ages of 18 and 30 years old participated in the study. They were subjected to an audiometry examination, followed by rest for 10 minutes for HR recording. Next, ABR evaluation was completed discretely in both ears, with I, III and V wave components. Linear regression revealed that the root‑mean square of differences between adjacent normal RR intervals (RMSSD) and the triangular interpolation of RR interval (TINN) exhibited a significant association with Wave I in the right ear. These variables contributed to 28.2% (R²) of Wave I. In conclusion, there was a significant interaction between the autonomic control of HR and auditory processing in the right ear, suggesting that vagal tone interacts with the cochlear nerve.
Introduction. Heart rate variability (HRV) can be assessed from RR-intervals. These are derived from an electrocardiographic PQRST-signature and can deviate in a chaotic or irregular manner. In the past, techniques from statistical physics have allowed researchers to study such systems.Objective. This study planned to assess the heart rate dynamics in young obese subjects by nonlinear metrics to heart rate variability. Method. 86 subjects were split equally according to status. Heart rate was recorded with the subjects resting in a dorsal (prone) position for 30 minutes. The complexity of the RR-intervals was assessed by five Entropies, Detrended Fluctuation Analysis, Higuchi and Katz’s fractal dimensions Following inconclusive tests of normality we calculated the One-Way Analysis of Variance, Kruskal-Wallis, and the Effect Sizes by Cohen’s d significances. Results. It was established that Shannon, Renyi and Tsallis Entropies and the Higuchi and Katz’s fractal dimensions could significantly discriminate the two groups. The three entropies were higher in obese youths, suggesting less predictable sets of RR intervals (p<0.0001; d≈1.0). Whilst the Higuchi (p<0.003; d≈0.76) and Katz’s (p≈0.02; d≈0.57) fractal dimensions were lower in obese youths. Conclusion. As with chaotic globals an increase in response was detected by three measures of entropy in young obese. This is counter to the decreasing response detected by fractal dimensions. Chaotic globals and entropies are more dependable than fractal dimensions when assessing the responses to obesity.
Background and aims. Statistical markers are valuable when assessing physiological status over periods of time and in certain disease states. We assess if type 1 diabetes mellitus promote modification in the autonomic nervous system using the main two types of algorithms to estimate a Fractal Dimension: Higuchi and Katz. Material and methods. 46 adults were divided into two equal groups. The autonomic evaluation consisted of recording heart rate variability (HRV) for 30 minutes in supine position in absence of any other stimuli. Fractal dimensions ought then able to determine which series of interbeat intervals are derived from diabetics’ or not. We then equated results to observe which assessment gave the greatest significance by One-way analysis of variance (ANOVA1), Kruskal-Wallis technique and Cohen’s d effect sizes. Results. Katz’s fractal dimension is the most robust algorithm when assisted by a cubic spline interpolation (6 Hz) to increase the number of samples in the dataset. This was categorical after two tests for normality; then, ANOVA1, Kruskal-Wallis and Cohen’s d effect sizes (p≈0.01 and Cohen’s d=0.814143–medium effect size). Conclusion. Diabetes significantly reduced the chaotic response as measured by Katz’s fractal dimension. Katz’s fractal dimension is a viable statistical marker for subjectswith type 1 diabetes mellitus.
Background: The priniciple objective here is to analyze cardiovascular dynamics in diabetic subjects by actions related to heart rate variability (HRV). The correlation of chaotic globals is vital to evaluate the probability of dynamical diseases. Methods: Fortysix adults were split equally. The autonomic evaluation consisted of recording HRV for 30 minutes in supine position without any additional stimuli. “Chaotic globals” are then able to statistically determine which series of interbeat intervals are diabetic and which are not. Two of these chaotic globals, spectral Entropy and spectral Detrended fluctuation analysis were derived from six alternative power spectra: Welch, Multi-Taper Method, Covariance, Burg, Yule-Walker and the Periodogram. We then compared results to observe which power spectra provided the greatest significance by three statistical tests: One-way analysis of variance (ANOVA1); Kruskal-Wallis technique and the multivariate technique, principal component analysis (PCA). Results: The Chaotic Forward Parameter One (CFP1) applying all three parameters is proven the most robust algorithm with Welch and MTM spectra enforced. This was proven following two tests for normality where ANOVA1 (p=0.09) and Kruskal-Wallis (p=0.03). Multivariate analysis revealed that two principal components represented 99.8% of total variance, a steep scree plot, with CFP1 the most influential parameter. Conclusion: Diabetes reduced the chaotic response.
Introduction: Fetal heart rate and its variability during the course of gestation have been extensively re-searched. The overall reduction in heart rate and increase in fetal HRV is associated with fetal growth and the increase in neural integration. The increased complexity of the demands on the cardiovascular system leads to more variation in the temporal course of the heart rate which has been shown to be refl ected in measures of complexity. The aim of this work was to investigate novel complexity measures with respect to their ability to quantify changes over gestational age in individual fetuses consistently and in a stable manner.
Methods: We examined 215 fetal magnetocardiograms (FMCG), each of 5 min duration, in 11 fetuses during the second and third trimesters (at least 10 data sets per fetus). From the FMCG we determined the fetal RR beat durations. For each 5 min time-series of RR intervals we then calculated Shannon entropy, high spectral entropy, high spectral Detrended Fluctuation Analysis, spectral Multi-Taper Method as well as the standard deviation and two commonly used complexity measures: Approximate Entropy and Sample Entropy. For each subject and HRV measure, we performed regression analysis with respect to ges tational age. The coeffi cient of determination R2 was used to es timate ‘goodness-of-fi t’, the slope of the regression indicated the strength of the individual dependency on gestational age.
Results: We found that the new complexity measures do not outperform ApEn.
Conclusion: This study has now rejected the hypothesis that the spectral complexity measures outperform those applied previously