Sex differences in linear and nonlinear heart rate variability during early recovery from supramaximal exercise

2010 ◽  
Vol 35 (S1) ◽  
pp. 439-446 ◽  
Author(s):  
Goncalo V. Mendonca ◽  
Kevin S. Heffernan ◽  
Lindy Rossow ◽  
Myriam Guerra ◽  
Fernando D. Pereira ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Low Frequency ◽  
Autonomic Response ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Supramaximal Exercise ◽  
Early Recovery ◽  
Additional Information ◽  
Linear And Nonlinear

Women demonstrate greater RR interval variability than men of similar age. Enhanced parasympathetic input into cardiac regulation appears to be not only greater in women, but also protective during periods of cardiac stress. Even though women may have a more favorable autonomic profile after exercise, little research has been conducted on this issue. This study was designed to examine the cardiac autonomic response, in both male and female participants, during the early recovery from supramaximal exercise. Twenty-five individuals, aged 20 to 33 years (13 males and 12 females), performed a 30-s Wingate test. Beat-to-beat RR series were recorded before and 5 min after exercise, with the participants in the supine position and under paced breathing. Linear (spectral analysis) and nonlinear analyses (detrended fluctuation analysis (DFA)) were performed on the same RR series. At rest, women presented lower raw low frequency (LF) power and higher normalized high frequency (HF) power. Under these conditions, the LF/HF ratio of women was also lower than that of men (p < 0.05), but there were no differences in the short-term scaling exponent (α1). Even though both sexes showed a significant modification in linear and nonlinear measures of heart rate variability (HRV) (p < 0.05), women had a greater change in LF/HF ratio and α1 than men from rest to recovery. This study demonstrates that the cardiac autonomic function of women is more affected by supramaximal exercise than that of men. Additionally, DFA did not provide additional information about sexual dimorphisms, compared with conventional spectral HRV techniques.

scholarly journals Prognostic value of heart rate variability in patients with coronary artery disease in the current treatment era

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254107
Author(s):  
Antti O. Vuoti ◽  
Mikko P. Tulppo ◽  
Olavi H. Ukkola ◽  
M. Juhani Junttila ◽  
Heikki V. Huikuri ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Low Frequency ◽  
Frequency Component ◽  
Current Treatment ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Natural Logarithm ◽  
Artery Disease ◽  
Detrended Fluctuation

Coronary artery disease (CAD) mortality has declined substantially over the past decades thanks to advancing medical and interventional/surgical treatments; therefore, the prognostic value of the heart rate variability in CAD in the current treatment era is not well established. We evaluated the prognostic significance of baseline heart rate variability in 1,757 ARTEMIS study patients with angiographically verified CAD. During an average follow-up time of 8.7 ± 2.2 years, a total of 285 (16.2%) patients died. Of the patients, 63 (3.6%) suffered sudden cardiac death or were resuscitated from sudden cardiac arrest (SCD/SCA), 60 (3.4%) experienced non-sudden cardiac death (NSCD), and death attributable to non-cardiac causes (NCD) occurred in 162 (9.2%) patients. For every 10 ms decrease in standard deviation of normal to normal intervals the risk for SCD/SCA, NSCD and NCD increased significantly: HR 1.153 (95% CI 1.075–1.236, p<0.001), HR 1.187 (95% CI 1.102–1.278, p<0.001) and HR 1.080 (95% CI 1.037–1.125, p<0.001), respectively. The natural logarithm of the low-frequency component of the power spectrum and the short-term scaling exponent of the detrended fluctuation analysis also had significant association with all modes of death (p<0.001). After relevant adjustment, standard deviation of normal-to-normal intervals retained its association with NSCD and NCD (p<0.01), the natural logarithm of the low-frequency component of the power spectrum with all modes of death (p from <0.05 to <0.01), and the short-term scaling exponent of the detrended fluctuation analysis with SCD/SCA (p<0.05) and NCD (p<0.001). In conclusion, impairment of many measures of heart rate variability predicts mortality but is not associated with any specific mode of death in patients with stable CAD during the current treatment era, limiting the clinical applicability of heart rate variability to targeting therapy.

Detrended Fluctuation Analysis of Heart Rate Variability in Noise Exposure

2014 ◽  
Vol 1044-1045 ◽  
pp. 1129-1134 ◽  
Author(s):  
Shih Tsung Chen ◽  
Li Ho Tseng ◽  
Yuan Po Lee ◽  
Hong Zhun Wu ◽  
Chia Yi Chou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Detrended Fluctuation Analysis ◽  
Low Frequency ◽  
Fluctuation Analysis ◽  
Frequency Noise ◽  
Cardiovascular Activity ◽  
Low Frequency Noise ◽  
Rr Intervals ◽  
Detrended Fluctuation

During the past two decades, most studies have employed questionnaires to characterize the effects of noise on behavior and health. Developments in physiological techniques have provided a noninvasive method for recording cardiovascular autonomic activity by using an electrocardiogram (ECG). We investigated cardiovascular activity changes in exposure to exposure to low-frequency noise for various noise intensities by using detrended fluctuation analysis (DFA) of heart rate variability (HRV). We hypothesized that distinct noise intensities would affect cardiovascular activity, which would be reflected in the HRV and DFA parameters. A total of 17 healthy volunteers participated in this study. The test intensities of noises were no noise, 70-dBC, 80-dBC, and 90-dBC. Each noise was sustained for 5 minutes and the ECG was recorded simultaneously. The cardiovascular responses were evaluated using DFA of the beat-to-beat (RR) intervals obtained from ECG signals. The results showed that the mean RR intervals variability and mean blood pressure did not substantially change relative to the noises. However, the short-term scaling exponent (α1) of the DFA of the background noise (no noise) condition was lower than the 70-dBC, 80-dBC and 90-dBC noises (P< 0.05, repeated measures analysis of variance). The α1of 90-dBC noise was significantly higher than the α1of BN condition according to a Mann–Whitney U test (P< 0.01). We concluded that exposure to low-frequency noise significantly affects the temporal correlations of HRV, but it does not influence RR intervals variability.

Scaling exponent values as an ordinary function of the ratio of very low frequency to high frequency powers in heart rate variability over various sleep stages

2016 ◽  
Vol 20 (3) ◽  
pp. 975-985 ◽  
Author(s):  
Ren-Jing Huang ◽  
Ching-Hsiang Lai ◽  
Shin-Da Lee ◽  
Wei-Che Wang ◽  
Ling-Hui Tseng ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Low Frequency ◽  
Sleep Stages ◽  
Scaling Exponent ◽  
Very Low Frequency

scholarly journals A New Detection Method Defining the Aerobic Threshold for Endurance Exercise and Training Prescription Based on Fractal Correlation Properties of Heart Rate Variability

2021 ◽  
Vol 11 ◽  
Author(s):  
Bruce Rogers ◽  
David Giles ◽  
Nick Draper ◽  
Olaf Hoos ◽  
Thomas Gronwald
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Gas Exchange ◽  
Ventilatory Threshold ◽  
Intraclass Correlation ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Low Intensity ◽  
Low Intensity Exercise ◽  
Correlation Properties

The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), a nonlinear index of heart rate variability (HRV) based on fractal correlation properties, has been shown to steadily change with increasing exercise intensity. To date, no study has specifically examined using the behavior of this index as a method for defining a low intensity exercise zone. The aim of this report is to compare both oxygen intake (VO2) and heart rate (HR) reached at the first ventilatory threshold (VT1), a well-established delimiter of low intensity exercise, to those derived from a predefined DFA a1 transitional value. Gas exchange and HRV data were obtained from 15 participants during an incremental treadmill run. Comparison of both VO2 and HR reached at VT1 defined by gas exchange (VT1 GAS) was made to those parameters derived from analysis of DFA a1 reaching a value of 0.75 (HRVT). Based on Bland Altman analysis, linear regression, intraclass correlation (ICC) and t testing, there was strong agreement between VT1 GAS and HRVT as measured by both HR and VO2. Mean VT1 GAS was reached at 39.8 ml/kg/min with a HR of 152 bpm compared to mean HRVT which was reached at 40.1 ml/kg/min with a HR of 154 bpm. Strong linear relationships were seen between test modalities, with Pearson’s r values of 0.99 (p &lt; 0.001) and.97 (p &lt; 0.001) for VO2 and HR comparisons, respectively. Intraclass correlation between VT1 GAS and HRVT was 0.99 for VO2 and 0.96 for HR. In addition, comparison of VT1 GAS and HRVT showed no differences by t testing, also supporting the method validity. In conclusion, it appears that reaching a DFA a1 value of 0.75 on an incremental treadmill test is closely associated with crossing the first ventilatory threshold. As training intensity below the first ventilatory threshold is felt to have great importance for endurance sport, utilization of DFA a1 activity may provide guidance for a valid low training zone.

scholarly journals Differences in heart rate variability and body composition in breast cancer survivors and women without cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel Escutia-Reyes ◽  
José de Jesús Garduño-García ◽  
Gerardo Emilio-López-Chávez ◽  
Ángel Gómez-Villanueva ◽  
Adriana Cristina Pliego-Carrillo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Body Composition ◽  
Cancer Survivors ◽  
Visceral Fat ◽  
Breast Cancer Survivors ◽  
Scaling Exponent ◽  
Rr Interval ◽  
Linear And Nonlinear

AbstractThe aim of this study was to explore cardiac autonomic changes assessed by linear and nonlinear indexes of heart rate variability (HRV) and body composition modifications in breast cancer survivors and cancer-free control women. Women who were breast cancer survivors (BCS, n = 27) and without cancer with similar characteristics (Control, n = 31) were recruited for this study. We calculated some relevant linear and nonlinear parameters of 5 min of RR interval time series such as mean RR interval (RRave), the corrected Poincaré index (cSD1/SD2), the sample entropy (SampEn), the long-term fractal scaling exponent (α2) and 2UV from symbolic dynamics. Additionally, we indirectly assessed body composition measures such as body weight, fat mass, visceral fat rating (VFR), normalized VRF (nVFR), muscle mass, metabolic age, and total body water. We found that diverse HRV indexes and only one body composition measure showed statistical differences (p < 0.05) between the BCS and Control groups. RRave: 729 (648–802) vs. 795 (713–852) ms; cSD2/SD1: 3.4 (2.7–5.0) vs. 2.9 (2.3–3.5); SampEn: 1.5 (1.3–1.8) vs. 1.7 (1.5–1.8); α2: 0.6 (0.3–0.6) vs. 0.5 (0.4–0.5); 2UV: 7.1 (4.3–11.5) vs. 10.8 (6.4–15.7) and nVFR 0.12 (0.11–0.13) vs. 0.10 (0.08–0.12) points/kg, respectively. The nVFR was strongly significantly correlated with several indexes of HRV only in the BCS group.Our findings suggest that BCS exhibit lower parasympathetic cardiac activity and changes in HRV patterns compared to Controls. A concomitant increase of visceral fat, among other factors, may contribute to cardiac autonomic disturbances and changes in HRV patterns in BCS.

scholarly journals HEART RATE VARIABILITY AND BODY COMPOSITION AS VO2MAX DETERMINANTS

2017 ◽  
Vol 23 (4) ◽  
pp. 317-321 ◽  
Author(s):  
Henry Humberto León-Ariza ◽  
Daniel Alfonso Botero-Rosas ◽  
Aura Catalina Zea-Robles
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Body Composition ◽  
Standard Error ◽  
Low Frequency ◽  
Standing Position ◽  
Fluctuation Analysis ◽  
Maximum Oxygen Consumption ◽  
Detrended Fluctuation ◽  
Cardiorespiratory Endurance

ABSTRACT Introduction: The maximum oxygen consumption (VO2max) is the gold standard in the cardiorespiratory endurance assessment. Objective: This study aimed to develop a mathematical model that contains variables to determine the VO2max of sedentary people. Methods: Twenty participants (10 men and 10 women) with a mean age of 19.8±1.77 years were included. For each participant, body composition (percentage of fat and muscle), heart rate variability (HRV) at rest (supine and standing), and VO2max were evaluated through an indirect test on a cycloergometer. A multivariate linear regression model was developed from the data obtained, and the model assumptions were verified. Results: Using the data obtained, including percentage of fat (F), percentage of muscle (M), percentage of power at very low frequency (VLF), α-value of the detrended fluctuation analysis (DFAα1), heart rate (HR) in the resting standing position, and age of the participants, a model was established for men, which was expressed as VO2max = 4.216 + (Age*0.153) + (F*0.110) - (M*0.053) - (VLF*0.649) - (DFAα1*2.441) - (HR*0.014), with R2 = 0.965 and standard error = 0.146 L/min. For women, the model was expressed as VO2max = 1.947 - (Age*0.047) + (F*0.024) + (M*0.054) + (VLF*1.949) - (DFAα1*0.424) - (HR*0.019), with R2 = 0.987 and standard error = 0.077 L/min. Conclusion: The obtained model demonstrated the influence exerted by body composition, the autonomic nervous system, and age in the prediction of VO2max.

NONLINEAR INDICES OF HEART RATE VARIABILITY FOR DIFFERENTIATING ARRHYTHMIAS

2013 ◽  
Vol 13 (04) ◽  
pp. 1350061 ◽  
Author(s):  
N. D. ASHA ◽  
K. PAUL JOSEPH
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Normal Sinus Rhythm ◽  
Ventricular Tachyarrhythmia ◽  
Recurrence Plot ◽  
Largest Lyapunov Exponent ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Poincaré Plot ◽  
Diagonal Length

Heart rate variability (HRV) is the temporal variation between sequences of consecutive heartbeats. Chaos and fractal-based measurements have been widely used for quantifying the HRV for cardiac risk stratification purposes. In this paper, five different sets of HRVs, viz., normal sinus rhythm (NSR), congestive heart failure (CHF), cardiac arrhythmia suppression trial (CAST), supra ventricular tachyarrhythmia (SVTA) and atrial fibrillation (AF), have been analysed using nonlinear parameters to fix the ranges of each parameter. Data were downloaded from the PhysioNet database with 15 sets in each case. The parameters used for analysis were Poincare plot measures: SD1, SD2 and SD12, largest Lyapunov exponent (LLE), correlation dimension (CD); recurrence plot measures: recurrence rate (REC), determinism (DET), mean diagonal length (L mean ), maximal diagonal length (L max ) and entropy (ENTR); detrended fluctuation analysis measures: scaling exponent (α) and fractal dimension (FD); sample entropy (SampEn); and approximate entropy (ApEn). Analysis of variance (ANOVA) was done for confirming the differences in parameter values between various cases. All parameters except LLE showed a significant statistical difference for different cases.

scholarly journals Autonomic dysfunction characterized by Heart Rate Variability among patients with Sepsis-related Acute Respiratory Failure

2021 ◽  
Author(s):  
Preethi Krishnan ◽  
Curtis Marshall ◽  
Philip Yang ◽  
Sivasubramanium V Bhavani ◽  
Andre Holder ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Respiratory Failure ◽  
Acute Respiratory Failure ◽  
Time Domain ◽  
Statistical Significance ◽  
Low Frequency ◽  
Multiscale Entropy ◽  
Physiological Data ◽  
Fluctuation Analysis

Abstract Rationale: To explore the association and implications of using Heart rate variability (HRV) derived from continuous bedside monitoring as a surrogate for detection of Acute Respiratory Failure (ARF) in critically ill sepsis patients. Objective: To analyze HRV measures derived from continuous physiological data captured before ARF-onset to determine whether statistically significant markers can be characterized when compared to sepsis controls. Methods: Retrospective HRV analysis of sepsis patients admitted to Emory Healthcare ICUs was performed between ARF and age and gender-matched controls. HRV measures such as time domain, frequency domain, nonlinear, and complexity measures were analyzed up to 1 hour before the onset of ARF, and a random event time in the sepsis-controls. Statistical significance was computed by the Wilcoxon Rank Sum test. Results: A total of 89 intensive care unit (ICU) patients with sepsis were included in this retrospective cohort study. Time-domain HRV measures including pNN50 (the fraction of consecutive NN intervals that differ by more than 50 ms), RMSSD (root-mean-square differences of successive NN intervals), standard deviation, interquartile range, variance, and approximate entropy for Beat-to-Beat intervals strongly distinguished ARF patients from the controls group. HRV measures for nonlinear and frequency domains were significantly altered (p<0.05) among sepsis patients with ARF compared to controls. Frequency measures such as low frequency (LF), very low frequency (VLF), high frequency (HF), and SD1/SD2 ratio nonlinear measure (SD1:SD2) also showed a significant (p<0.05) increase in the ARF group patients. Multiscale entropy complexity was lower for ARF patients compared to the control counterparts. Detrended fluctuation analysis (DFA) showed a decreasing trend in ARF patients. Conclusions: HRV was significantly impaired across sepsis patients who developed ARF when compared to sepsis controls, indicating a potential prognostic utility for earlier identification of the need for mechanical ventilation and management of patients suspected with sepsis.

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Heart Rate Variability, Homeostasis, and Brain Function

2012 ◽  
Vol 26 (4) ◽  
pp. 178-203 ◽  
Author(s):  
Francesco Riganello ◽  
Sergio Garbarino ◽  
Walter G. Sannita
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Communication Disorders ◽  
Affective States ◽  
Experimental Conditions ◽  
Cardiovascular Research ◽  
Sensory Stimuli ◽  
Additional Information ◽  
Brain Injured

Measures of heart rate variability (HRV) are major indices of the sympathovagal balance in cardiovascular research. These measures are thought to reflect complex patterns of brain activation as well and HRV is now emerging as a descriptor thought to provide information on the nervous system organization of homeostatic responses in accordance with the situational requirements. Current models of integration equate HRV to the affective states as parallel outputs of the central autonomic network, with HRV reflecting its organization of affective, physiological, “cognitive,” and behavioral elements into a homeostatic response. Clinical application is in the study of patients with psychiatric disorders, traumatic brain injury, impaired emotion-specific processing, personality, and communication disorders. HRV responses to highly emotional sensory inputs have been identified in subjects in vegetative state and in healthy or brain injured subjects processing complex sensory stimuli. In this respect, HRV measurements can provide additional information on the brain functional setup in the severely brain damaged and would provide researchers with a suitable approach in the absence of conscious behavior or whenever complex experimental conditions and data collection are impracticable, as it is the case, for example, in intensive care units.

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