Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds.
Aims of this study were: to verify if Recurrence Quantification Analysis (RQA) of Heart Rate Variability (HRV) time series could determine both ventilatory thresholds in individuals with different fitness levels, and to assess the validity of RQA method compared to gas-exchange method (GE). The two...
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oai:doaj.org-article:a26124d26ae6448da82d6883ac3cd92d2021-12-02T20:13:48ZRecurrence quantification analysis of heart rate variability to detect both ventilatory thresholds.1932-620310.1371/journal.pone.0249504https://doaj.org/article/a26124d26ae6448da82d6883ac3cd92d2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0249504https://doaj.org/toc/1932-6203Aims of this study were: to verify if Recurrence Quantification Analysis (RQA) of Heart Rate Variability (HRV) time series could determine both ventilatory thresholds in individuals with different fitness levels, and to assess the validity of RQA method compared to gas-exchange method (GE). The two thresholds were estimated in thirty young individuals during incremental exercise on cycle-ergometer: Heart rate (HR), Oxygen consumption (VO2) and Workload were measured by the two methods (RQA and GE). Repeated measures ANOVA was used to assess main effects of methods and methods-by-groups interaction effects for HR, VO2 and Workload at aerobic (AerT) and anaerobic (AnT) thresholds. Validity of RQA at both thresholds was assessed for HR, VO2 and Workload by Ordinary Least Products (OLP) regression, Typical Percentage Error (TE), Intraclass Correlation Coefficients (ICC) and the Bland Altman plots. No methods-by-groups interaction effects were detected for HR, VO2 and Workload at AerT and AnT. The OLP analysis showed that at both thresholds RQA and GE methods had very strong correlations (r >0.8) in all variables (HR, VO2 and Workload). Slope and intercept values always included the 1 and the 0, respectively. At AerT the TE ranged from 4.02% (5.48 bpm) to 10.47% (8.53 Watts) (HR and Workload, respectively) and in all variables ICC values were excellent (≥0.85). At AnT the TE ranged from 2.53% (3.98 bpm) to 6.64% (7.81 Watts) (HR and Workload, respectively) and in all variables ICC values were excellent (≥0.90). Therefore, RQA of HRV time series is a new valid approach to determine both ventilatory thresholds in individuals with different physical fitness levels, it can be used when gas analysis is not possible or not convenient.Giovanna ZimatoreLavinia FalcioniMaria Chiara GallottaValerio BonavolontàMatteo CampanellaMarco De SpiritoLaura GuidettiCarlo BaldariPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0249504 (2021) |
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Medicine R Science Q Giovanna Zimatore Lavinia Falcioni Maria Chiara Gallotta Valerio Bonavolontà Matteo Campanella Marco De Spirito Laura Guidetti Carlo Baldari Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
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Aims of this study were: to verify if Recurrence Quantification Analysis (RQA) of Heart Rate Variability (HRV) time series could determine both ventilatory thresholds in individuals with different fitness levels, and to assess the validity of RQA method compared to gas-exchange method (GE). The two thresholds were estimated in thirty young individuals during incremental exercise on cycle-ergometer: Heart rate (HR), Oxygen consumption (VO2) and Workload were measured by the two methods (RQA and GE). Repeated measures ANOVA was used to assess main effects of methods and methods-by-groups interaction effects for HR, VO2 and Workload at aerobic (AerT) and anaerobic (AnT) thresholds. Validity of RQA at both thresholds was assessed for HR, VO2 and Workload by Ordinary Least Products (OLP) regression, Typical Percentage Error (TE), Intraclass Correlation Coefficients (ICC) and the Bland Altman plots. No methods-by-groups interaction effects were detected for HR, VO2 and Workload at AerT and AnT. The OLP analysis showed that at both thresholds RQA and GE methods had very strong correlations (r >0.8) in all variables (HR, VO2 and Workload). Slope and intercept values always included the 1 and the 0, respectively. At AerT the TE ranged from 4.02% (5.48 bpm) to 10.47% (8.53 Watts) (HR and Workload, respectively) and in all variables ICC values were excellent (≥0.85). At AnT the TE ranged from 2.53% (3.98 bpm) to 6.64% (7.81 Watts) (HR and Workload, respectively) and in all variables ICC values were excellent (≥0.90). Therefore, RQA of HRV time series is a new valid approach to determine both ventilatory thresholds in individuals with different physical fitness levels, it can be used when gas analysis is not possible or not convenient. |
format |
article |
author |
Giovanna Zimatore Lavinia Falcioni Maria Chiara Gallotta Valerio Bonavolontà Matteo Campanella Marco De Spirito Laura Guidetti Carlo Baldari |
author_facet |
Giovanna Zimatore Lavinia Falcioni Maria Chiara Gallotta Valerio Bonavolontà Matteo Campanella Marco De Spirito Laura Guidetti Carlo Baldari |
author_sort |
Giovanna Zimatore |
title |
Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
title_short |
Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
title_full |
Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
title_fullStr |
Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
title_full_unstemmed |
Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
title_sort |
recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doaj.org/article/a26124d26ae6448da82d6883ac3cd92d |
work_keys_str_mv |
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1718374724989353984 |