scholarly journals Recurrence quantification analysis of heart rate variability during continuous incremental exercise test in obese subjects

2020 ◽  
Vol 30 (3) ◽  
pp. 033135
Author(s):  
G. Zimatore ◽  
M. C. Gallotta ◽  
L. Innocenti ◽  
V. Bonavolontà ◽  
G. Ciasca ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Test ◽  
Recurrence Quantification Analysis ◽  
Incremental Exercise ◽  
Incremental Exercise Test ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Obese Subjects

scholarly journals Possible Caveats of Ultra-Short Heart Rate Variability Reliability: Insights from Recurrence Quantification Analysis

2021 ◽  
Author(s):  
Hiago Murilo Melo ◽  
Mariana Cardoso Melo ◽  
Roger Walz ◽  
Emílio Takase ◽  
Jean Faber
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Recurrence Quantification Analysis ◽  
Dynamic Information ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
The Difference ◽  
Main Components ◽  
Clinical Measures

Abstract The heart rate variability (HRV) is the difference between consecutive R-R intervals of heartbeats measured in milliseconds. HRV indices represent the role of sympathetic and parasympathetic autonomic branches. Even though HRV is considered an indirect biomarker of Autonomic Nervous System, there are not yet standardized protocols providing reliable clinical measures. One of the reasons is because HRV techniques requires long recording periods. There are attempts of decreasing the required recording, such as the strategy of ultra-short HVR recording (< one minute), which could make the utilization of the technique easier. However, there is little published about its reliability. This work proposes a method to evaluate the reliability of ultra-short HVR based in Poincare map and Recurrence Quantification Analysis, well known methods to assess nonlinear and dynamic information from a system, in order to verify the reliability of the use of ultra-short term HRV. Then, these results was compared with the classical HRV coefficients, such as rMSSD, recorded from subjects in spontaneous breathing and also, in controlled breathing protocols. As a conclusion, using the proposed methods, we were able to show the discrepancy between the segments of interest, both on mean and in variance, explained in the analysis of main components.

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

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0249504
Author(s):  
Giovanna Zimatore ◽  
Lavinia Falcioni ◽  
Maria Chiara Gallotta ◽  
Valerio Bonavolontà ◽  
Matteo Campanella ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Repeated Measures ◽  
Intraclass Correlation ◽  
Interaction Effects ◽  
Recurrence Quantification Analysis ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Fitness Levels

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.

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