Nathaniel T Berry1, Emily Bechke1, Lenka H Shriver2, Susan D Calkins3, Susan P Keane4, Lilly Shanahan5, Laurie Wideman1. 1. Department of Kinesiology, The University of North Carolina at Greensboro, Greensboro, NC, United States. 2. Department of Nutrition, The University of North Carolina at Greensboro, Greensboro, NC, United States. 3. Department of Human Development and Family Studies, The University of North Carolina at Greensboro, Greensboro, NC, United States. 4. Department of Psychology, The University of North Carolina at Greensboro, Greensboro, NC, United States. 5. Department of Psychology, University of Zurich, Zurich, Switzerland.
Abstract
INTRODUCTION: Resting heart rate (HRrest), heart rate variability (HRV), and HR recovery (HRR) from exercise provide valuable information about cardiac autonomic control. RR-intervals during acute recovery from exercise (RRrec) are commonly excluded from HRV analyses due to issues of non-stationarity. However, the variability and complexity within these trends may provide valuable information about changes in HR dynamics. PURPOSE: Assess the complexity of RRrec and determine what physiologic and demographic information are associated with differences in these indices in young adults. METHODS: RR-intervals were collected throughout maximal treadmill exercise and recovery in young adults (n = 92). The first 5 min of RRrec were (1) analyzed with previously reported methods that use 3-interval lengths for comparison and (2) detrended using both differencing(diff) and polynomial regression(res). The standard deviation of the normal interval (SDNN), root mean square of successive differences (rMSSD), root mean square (RMS) of the residual of regression, and sample entropy (SampEn) were calculated. Repeated measures analysis of covariance (ANCOVA) tested for differences in these indices for each of the methodological approaches, controlling for race, body fat, peak oxygen uptake (VO2p eak), and resting HR (HRrest). Statistical significance was set at p < 0.05. RESULTS: VO2p eak and HRrest were significantly correlated with traditional measures of HRR and the variability surrounding RRrec. SampEndiff and SampEnres were correlated with VO2p eak but not HRrest or HRR. The residual-method provided a significantly (p = 0.04) lower mean standard error (MSE) (0.064 ± 0.042) compared to the differencing-method (0.100 ± 0.033). CONCLUSIONS: Complexity analysis of RRrec provides unique information about cardiac autonomic regulation immediately following the cessation of exercise when compared to traditional measures of HRR and both HRrest and VO2peak influence these results.
INTRODUCTION: Resting heart rate (HRrest), heart rate variability (HRV), and HR recovery (HRR) from exercise provide valuable information about cardiac autonomic control. RR-intervals during acute recovery from exercise (RRrec) are commonly excluded from HRV analyses due to issues of non-stationarity. However, the variability and complexity within these trends may provide valuable information about changes in HR dynamics. PURPOSE: Assess the complexity of RRrec and determine what physiologic and demographic information are associated with differences in these indices in young adults. METHODS: RR-intervals were collected throughout maximal treadmill exercise and recovery in young adults (n = 92). The first 5 min of RRrec were (1) analyzed with previously reported methods that use 3-interval lengths for comparison and (2) detrended using both differencing(diff) and polynomial regression(res). The standard deviation of the normal interval (SDNN), root mean square of successive differences (rMSSD), root mean square (RMS) of the residual of regression, and sample entropy (SampEn) were calculated. Repeated measures analysis of covariance (ANCOVA) tested for differences in these indices for each of the methodological approaches, controlling for race, body fat, peak oxygen uptake (VO2p eak), and resting HR (HRrest). Statistical significance was set at p < 0.05. RESULTS: VO2p eak and HRrest were significantly correlated with traditional measures of HRR and the variability surrounding RRrec. SampEndiff and SampEnres were correlated with VO2p eak but not HRrest or HRR. The residual-method provided a significantly (p = 0.04) lower mean standard error (MSE) (0.064 ± 0.042) compared to the differencing-method (0.100 ± 0.033). CONCLUSIONS: Complexity analysis of RRrec provides unique information about cardiac autonomic regulation immediately following the cessation of exercise when compared to traditional measures of HRR and both HRrest and VO2peak influence these results.
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