Fractal scaling properties of heart rate dynamics following resistance exercise training

2008 ◽  
Vol 105 (1) ◽  
pp. 109-113 ◽  
Author(s):  
Kevin S. Heffernan ◽  
Jacob J. Sosnoff ◽  
Christopher A. Fahs ◽  
Kevin K. Shinsako ◽  
Sae Young Jae ◽  
...  
Keyword(s):  
Heart Rate ◽  
Exercise Training ◽  
Resistance Exercise ◽  
Control Period ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Resistance Exercise Training ◽  
Time Control ◽  
Fractal Properties ◽  
Correlation Properties

With aging and disease, there is a breakdown of the natural fractal-like organization of heart rate (HR). Fractal-like correlation properties of HR can be assessed with detrended fluctuation analysis (DFA). A short-time scaling exponent (αs) value of 1 is associated with healthy HR dynamics, whereas values that deviate away from 1, in either direction, indicate fractal collapse. The purpose of this study was to examine the effect of resistance exercise training (RT) on fractal correlation properties of HR dynamics. Resting ECG was collected at baseline, following a 4-wk time control period and 6 wk of RT (3 days per wk) in 34 men (23 ± 1 years of age). Fractal properties of HR were assessed with DFA. There was no change in αs following either the time control period or RT (1.01 ± 0.06 to 0.98 ± 0.06 to 0.93 ± 0.04, P > 0.05). Given the potential bidirectional nature of fractal collapse, subjects were retrospectively separated into two groups (higher αs and lower αs) on the basis of the initial αs by using cluster analysis. An interaction was detected for αs following RT ( P < 0.05). There was no change in αs in either group following the time control, but αs increased following RT in the lower αs group ( n = 18; 0.73 ± 0.04 to 0.69 ± 0.04 to 0.88 ± 0.04) and αs decreased following RT in the higher αs group ( n = 16; 1.20 ± 0.04 to 1.24 ± 0.04 to 0.98 ± 0.04). In conclusion, RT improves fractal properties of HR dynamics.

Heart rate recovery and heart rate complexity following resistance exercise training and detraining in young men

2007 ◽  
Vol 293 (5) ◽  
pp. H3180-H3186 ◽  
Author(s):  
Kevin S. Heffernan ◽  
Christopher A. Fahs ◽  
Kevin K. Shinsako ◽  
Sae Young Jae ◽  
Bo Fernhall
Keyword(s):  
Heart Rate ◽  
Resistance Training ◽  
Exercise Training ◽  
Resistance Exercise ◽  
Heart Rate Recovery ◽  
Young Men ◽  
Spectral Measures ◽  
Resistance Exercise Training ◽  
Time Control ◽  
Heart Rate Complexity

The purpose of this study was to examine heart rate recovery (HRR) and linear/nonlinear heart rate variability (HRV) before and after resistance training. Fourteen young men (25.0 ± 1.1 yr of age) completed a crossover design consisting of a 4-wk time-control period, 6 wk of resistance training (3 days/wk), and 4 wk of detraining. Linear HRV was spectrally decomposed using an autoregressive approach. Nonlinear dynamics of heart rate complexity included sample entropy (SampEn) and Lempel-Ziv entropy (LZEn). HRR was calculated from a graded maximal exercise test as maximal heart rate attained during the test minus heart rate at 1 min after exercise (HRR). There was no change in SampEn, LZEn, or HRR after the time-control portion of the study ( P > 0.05). SampEn ( P < 0.05), LZEn ( P < 0.05), and HRR ( P < 0.05) increased after resistance training and returned to pretraining values after detraining. There was no change in spectral measures of HRV at any time point ( P > 0.05). These findings suggest that resistance exercise training increases heart rate complexity and HRR after exercise but has no effect on spectral measures of HRV in young healthy men. These autonomic changes regress shortly after cessation of training.

scholarly journals Correlation Properties of Heart Rate Variability during a Marathon Race in Recreational Runners: Potential Biomarker of Complex Regulation during Endurance Exercise

2021 ◽  
pp. 557-563
Author(s):  
Thomas Gronwald ◽  
Bruce Rogers ◽  
Laura Hottenrott ◽  
Olaf Hoos ◽  
Kuno Hottenrott
Keyword(s):  
Heart Rate ◽  
Dynamic Range ◽  
Lactate Concentration ◽  
Cardiovascular Responses ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Marathon Race ◽  
Potential Biomarker ◽  
Recreational Runners ◽  
Correlation Properties

There is only very limited data examining cardiovascular responses in real-world endurance training/competition. The present study examines the influence of a marathon race on non-linear dynamics of heart rate (HR) variability (HRV). Eleven male recreational runners performed a self-paced marathon road race on an almost flat profile. During the race, heart rate and beat-to-beat (RR) intervals were recorded continuously. Besides HRV time-domain measurements, fractal correlation properties using short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) were calculated. The mean finishing time was 3:10:22 ± 0:17:56 h:min:s with a blood lactate concentration of 4.04 ± 1.12 mmol/L at the end of the race. Comparing the beginning to the end segment of the marathon race (Begin vs. End) significant increases could be found for km split time (p < .001, d = .934) and for HR (p = .010, d = .804). Significant decreases could be found for meanRR (p = .013, d = .798) and DFA-alpha1 (p = .003, d = 1.132). DFA-alpha1 showed an appropriate dynamic range throughout the race consisting of both uncorrelated and anti-correlated values. Lactate was consistent with sustained high intensity exercise when measured at the end of the event. Despite the runners slowing after halfway, DFA-alpha1 continued to fall to values seen in the highest intensity domain during incremental exercise testing in agreement with lactate assessment. Therefore, the discrepancy between the reduced running pace with that of the decline of DFA-alpha1, demonstrate the benefit of using this dimensionless HRV index as a biomarker of internal load during exercise over the course of a marathon race.

scholarly journals Aerobic Threshold Identification in a Cardiac Disease Population Based on Correlation Properties of Heart Rate Variability

2021 ◽  
Vol 10 (18) ◽  
pp. 4075
Author(s):  
Bruce Rogers ◽  
Laurent Mourot ◽  
Thomas Gronwald
Keyword(s):  
Heart Rate ◽  
Cardiac Disease ◽  
Ventilatory Threshold ◽  
Population Based ◽  
Training Intervention ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Linear Relationships ◽  
Mean Differences ◽  
Correlation Properties

An index of heart rate (HR) variability correlation properties, the short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1) has shown potential to delineate the first ventilatory threshold (VT1). This study aims to extend this concept to a group of participants with cardiac disease. Sixteen volunteers with stable coronary disease or heart failure performed an incremental cycling ramp to exhaustion PRE and POST a 3-week training intervention. Oxygen uptake (VO2) and HR at VT1 were obtained from a metabolic cart. An ECG was processed for DFA a1 and HR. The HR variability threshold (HRVT) was defined as the VO2, HR or power where DFA a1 reached a value of 0.75. Mean VT1 was reached at 16.82 ± 5.72 mL/kg/min, HR of 91.3 ± 11.9 bpm and power of 67.8 ± 17.9 watts compared to HRVT at 18.02 ± 7.74 mL/kg/min, HR of 94.7 ± 14.2 bpm and power of 73.2 ± 25.0 watts. Linear relationships were seen between modalities, with Pearson’s r of 0.95 (VO2), 0.86 (HR) and 0.87 (power). Bland–Altman assessment showed mean differences of 1.20 mL/kg/min, 3.4 bpm and 5.4 watts. Mean peak VO2 and VT1 did not change after training intervention. However, the correlation between PRE to POST change in VO2 at VT1 with the change in VO2 at HRVT was significant (r = 0.84, p < 0.001). Reaching a DFA a1 of 0.75 was associated with the VT1 in a population with cardiac disease. VT1 change after training intervention followed that of the HRVT, confirming the relationship between these parameters.

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 Resistance exercise training improves heart rate variability in women with fibromyalgia

2007 ◽  
Vol 0 (0) ◽  
pp. 071116232005001-??? ◽  
Author(s):  
Arturo Figueroa ◽  
J. Derek Kingsley ◽  
Victor McMillan ◽  
Lynn B. Panton
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Training ◽  
Resistance Exercise ◽  
Resistance Exercise Training

scholarly journals Analysis of Fractal Correlation Properties of Heart Rate Variability during an Initial Session of Eccentric Cycling

2021 ◽  
Vol 18 (19) ◽  
pp. 10426
Author(s):  
Bruce Rogers ◽  
Thomas Gronwald ◽  
Laurent Mourot
Keyword(s):  
Heart Rate ◽  
Exercise Prescription ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Short Term ◽  
Initial Session ◽  
Correlation Properties ◽  
Detrended Fluctuation ◽  
Improve Muscle Strength ◽  
Current Report

Eccentric cycling (ECC) has attracted attention as a method to improve muscle strength and aerobic fitness in populations unable to tolerate conventional methods. However, agreement on exercise prescription targets have been problematic. The current report is an initial exploration of a potentially useful tool, a nonlinear heart rate (HR) variability (HRV) index based on the short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), which has been previously shown to correspond to exercise intensity. Eleven male volunteers performed 45 min of concentric (CON) cycling and ECC separated by 1 month. Work rates were matched for HR (~50% of the maximal HR) during the first 5 min and remained stable thereafter. HRV, HR, oxygen consumption (VO2), and cycling power were monitored and evaluated at elapsed times of 10 (T10) and 45 (T45) minutes duration. HR significantly increased between ECC T10 and ECC T45 (p = 0.003, d = 1.485), while DFA a1 significantly decreased (p = 0.004, d = 1.087). During CON, HR significantly increased (p < 0.001 d = 1.570) without significant DFA a1 change (p = 0.48, d = 0.22). Significantly higher HR was observed at T45 in ECC than in CON (p = 0.047, d = 1.059). A session of unaccustomed ECC lead to decreased values of DFA a1 at T45 in comparison to that seen with CON at similar VO2. ECC lead to altered autonomic nervous system balance as reflected by the loss of correlation properties compared to CON.

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