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Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds

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Listed:
  • Giovanna Zimatore
  • Lavinia Falcioni
  • Maria Chiara Gallotta
  • Valerio Bonavolontà
  • Matteo Campanella
  • Marco De Spirito
  • Laura Guidetti
  • Carlo Baldari

Abstract

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.

Suggested Citation

  • Giovanna Zimatore & Lavinia Falcioni & Maria Chiara Gallotta & Valerio Bonavolontà & Matteo Campanella & Marco De Spirito & Laura Guidetti & Carlo Baldari, 2021. "Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-15, October.
  • Handle: RePEc:plo:pone00:0249504
    DOI: 10.1371/journal.pone.0249504
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    Cited by:

    1. Maria Chiara Gallotta & Giovanna Zimatore & Ludovica Cardinali & Lavinia Falcioni & Valerio Bonavolontà & Davide Curzi & Laura Guidetti & Carlo Baldari, 2022. "Physical Education on the Beach: An Alternative Way to Improve Primary School Children’s Skill- and Health-Related Outcomes during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(6), pages 1-13, March.
    2. Giovanna Zimatore & Maria Chiara Gallotta & Matteo Campanella & Piotr H. Skarzynski & Giuseppe Maulucci & Cassandra Serantoni & Marco De Spirito & Davide Curzi & Laura Guidetti & Carlo Baldari & Stavr, 2022. "Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review," IJERPH, MDPI, vol. 19(19), pages 1-24, October.
    3. Ping-Yen Lin & Cheng-Ting Tsai & Chang Francis Hsu & Ying-Hsiang Lee & Han-Ping Huang & Chun-Che Huang & Lawrence Yu-Min Liu & Long Hsu & Ten-Fang Yang & Po-Lin Lin, 2022. "The Autonomic Imbalance of Myocardial Ischemia during Exercise Stress Testing: Insight from Short-Term Heart Rate Variability Analysis," IJERPH, MDPI, vol. 19(22), pages 1-12, November.
    4. Ratko Peric & Zoran Nikolovski & Marco Meucci & Philippe Tadger & Carlo Ferri Marini & Francisco José Amaro-Gahete, 2022. "A Systematic Review and Meta-Analysis on the Association and Differences between Aerobic Threshold and Point of Optimal Fat Oxidation," IJERPH, MDPI, vol. 19(11), pages 1-19, May.

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