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.
Highlights
In exercise physiology the “threshold “concept is frequently used to assess both aerobic fitness and performance
In a previous work we proposed a new non-linear method based on Recurrence Quantification Analysis (RQA) of Heart Rate Variability (HRV) time series to estimate the aerobic threshold (AerT) in obese subjects [3]
Heart rate (HR), VO2, VO2/body weight (BW), power and RER at the AerT, Anaerobic threshold (AnT) and peak of exercise using RQA and gas exchange (GE) methods for each group
Summary
In exercise physiology the “threshold “concept is frequently used to assess both aerobic fitness and performance. In a previous work we proposed a new non-linear method based on Recurrence Quantification Analysis (RQA) of Heart Rate Variability (HRV) time series to estimate the aerobic threshold (AerT) in obese subjects [3]. In this special population the AerT (or first lactate threshold according to Binder and colleagues [2]), represents a useful parameter to identify the most appropriate physical exercise intensity in order to reduce body weight (BW) and to improve physical fitness [4]. This phase is represented by a more pronounced ventilation and a further increase in carbon dioxide production in an attempt to compensate for the marked rise in lactate [1, 2, 5]
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