Purpose: This systematic review with meta-analysis was conducted to establish whether heart rate variability (HRV)-guided training enhances cardiac-vagal modulation, aerobic fitness, or endurance performance to a greater extent than predefined training while accounting for methodological factors. Methods: We searched Web of Science Core Collection, Pubmed, and Embase databases up to October 2020. A random-effects model of standardized mean difference (SMD) was estimated for each outcome measure. Chi-square and the I2 index were used to evaluate the degree of homogeneity. Results: Accounting for methodological factors, HRV-guided training was superior for enhancing vagal-related HRV indices (SMD+ = 0.50 (95% confidence interval (CI) = 0.09, 0.91)), but not resting HR (SMD+ = 0.04 (95% CI = −0.34, 0.43)). Consistently small but non-significant (p > 0.05) SMDs in favor of HRV-guided training were observed for enhancing maximal aerobic capacity (SMD+ = 0.20 (95% CI = −0.07, 0.47)), aerobic capacity at second ventilatory threshold (SMD+ = 0.26 (95% CI = −0.05, 0.57)), and endurance performance (SMD+ = 0.20 (95% CI = −0.09, 0.48)), versus predefined training. No heterogeneity was found for any of the analyzed aerobic fitness and endurance performance outcomes. Conclusion: Best methodological practices pertaining to HRV index selection, recording position, and approaches for establishing baseline reference values and daily changes (i.e., fixed or rolling HRV averages) require further study. HRV-guided training may be more effective than predefined training for maintaining and improving vagal-mediated HRV, with less likelihood of negative responses. However, if HRV-guided training is superior to predefined training for producing group-level improvements in fitness and performance, current data suggest it is only by a small margin.
1 February 2019 in Journal of Science and Medicine in Sport
The aim of this study was to investigate the training-induced effect on cardiac parasympathetic nervous system (PNS) activity, assessed by resting heart rate variability (HRV) and post-exercise heart rate recovery (HRR), in sedentary healthy people. Electronic searches were carried out in PubMed, Embase, and Web of Science. Random-effects models of between-group standardised mean difference (SMD) were estimated. Heterogeneity analyses were performed by means of the chi-square test and I2 index. Subgroup analyses and meta-regressions were performed to investigate the influence of potential moderator variables on the training-induced effect. The results showed a small increase in RMSSD (SMD+ = 0.57 [95% confidence interval (CI) = 0.23, 0.91]) and high frequency (HF) (SMD+ = 0.21 [95% CI = 0.01, 0.42]) in favour of the intervention group. Heterogeneity tests reached statistical significance for RMSSD and HF (p ≤ 0.001), and the inconsistency was moderate (I2 = 68% and 60%, respectively). We found higher training-induced effects on HF in studies that performed a shorter intervention or lower number of exercise sessions (p ≤ 0.001). Data were insufficient to investigate the effect of exercise training on HRR. Exercise training increases cardiac PNS modulation in sedentary people, while its effect on PNS tone requires future study.
Research on reliability of heart rate variability (HRV) parameters in athletes has received increasing attention. The aims of this study were to examine the inter-day reliability of short-term (5 min) and ultra-short-term (1 min) heart rate (HR), respiratory rate (RespRate) and HRV parameters, agreement between short-term and ultra-short-term parameters, and association between differences in HR, RespRate and HRV parameters in elite modern pentathletes. Electrocardiographic recordings were performed in stable measurement conditions with a week interval between tests. Relative reliability was evaluated by intra-class correlation coefficients, absolute reliability was evaluated by within-subject coefficient of variation, and agreement was evaluated using Bland–Altman (BA) plot with limits of agreement and defined a priori maximum acceptable difference. Short-term HR, RespRate, log transformed (ln) root mean square of successive normal-to-normal interval differences (lnRMSSD), ln high frequency (lnHF) and SD2/SD1 HRV indices and ultra-short-term HR, RespRate and lnRMSSD presented acceptable, satisfactory inter-day reliability. Although there were no significant differences between short-term and ultra-short-term HR, RespRate and lnRMSSD, no parameter showed acceptable differences with BA plots. Differences in time-domain and non-linear HRV parameters were more correlated with differences in HR than with differences in RespRate. Inverse results were observed for frequency-domain parameters. Short-term HR, RespRate, lnRMSSD, lnHF, and SD2/SD1 and ultra-short-term HR, RespRate and lnRMSSD could be used as reliable parameters in endurance athletes. However, practitioners should interpret changes in HRV parameters with regard to concomitant differences in HR and RespRate and caution should be taken before considering 5 min and 1 min parameters as interchangeable.
Slow-paced breathing is a clinical intervention used to increase heart rate variability (HRV). The practice is made more accessible via cost-free smartphone applications like Elite HRV. We investigated whether Elite HRV can accurately measure and augment HRV via its slow-paced breathing feature. Twenty young adults completed one counterbalanced cross-over protocol involving 10 min each of supine spontaneous (SPONT) and paced (PACED; 6 breaths·min−1) breathing while RR intervals were simultaneously recorded via a Polar H10 paired with Elite HRV and reference electrocardiography (ECG). Individual differences in HRV between devices were predominately skewed, reflecting a tendency for Elite HRV to underestimate ECG-derived values. Skewness was typically driven by a limited number of outliers as median bias values were ≤1.3 ms and relative agreement was ≥very large for time-domain parameters. Despite no significant bias and ≥large relative agreement for frequency-domain parameters, limits of agreement (LOAs) were excessively wide and tended to be wider during PACED for all HRV parameters. PACED significantly increased low-frequency power (LF) for Elite HRV and ECG, and between-condition differences showed very large relative agreement. Elite HRV-guided slow-paced breathing effectively increased LF values, but it demonstrated greater precision during SPONT and in computing time-domain HRV.
1 December 2021 in International Journal of Sports Physiology and Performance
Purpose: To track cardiac-autonomic functioning, indexed by heart-rate variability, in American college football players throughout a competitive period. Methods: Resting heart rate (RHR) and the natural logarithm root mean square of successive differences (LnRMSSD) were obtained throughout preseason and ∼3 times weekly leading up to the national championship among 8 linemen and 12 nonlinemen. Seated 1-minute recordings were performed via mobile device and standardized for time of day and proximity to training. Results: Relative to preseason, linemen exhibited suppressed LnRMSSD during camp-style preparation for the playoffs (P = .041, effect size [ES] = −1.01), the week of the national semifinal (P < .001, ES = −1.27), and the week of the national championship (P = .005, ES = −1.16). As a combined group, increases in RHR (P < .001) were observed at the same time points (nonlinemen ES = 0.48–0.59, linemen ES = 1.03–1.10). For all linemen, RHR trended upward (positive slopes, R2 = .02–.77) while LnRMSSD trended downward (negative slopes, R2 = .02–.62) throughout the season. Preseason to postseason changes in RHR (r = .50, P = .025) and LnRMSSD (r = −.68, P < .001) were associated with body mass. Conclusions: Heart-rate variability tracking revealed progressive autonomic imbalance in the lineman position group, with individual players showing suppressed values by midseason. Attenuated parasympathetic activation is a hallmark of impaired recovery and may contribute to cardiovascular maladaptations reported to occur in linemen following a competitive season. Thus, a descending pattern may serve as an easily identifiable red flag requiring attention from performance and medical staff.