Endurance Running Training Individually Guided by HRV in Untrained Women

Heart Rate Variability Applications in Strength and Conditioning: A Narrative Review

Heart rate variability (HRV) is defined as the fluctuation of time intervals between adjacent heartbeats and is commonly used as a surrogate measure of autonomic function. HRV has become an increasingly measured variable by wearable technology for use in fitness and sport applications. However, with its increased use, a gap has arisen between the research and the application of this technology in strength and conditioning. The goal of this narrative literature review is to discuss current evidence and propose preliminary guidelines regarding the application of HRV in strength and conditioning. A literature review was conducted searching for HRV and strength and conditioning, aiming to focus on studies with time-domain measurements. Studies suggest that HRV is a helpful metric to assess training status, adaptability, and recovery after a training program. Although reduced HRV may be a sign of overreaching and/or overtraining syndrome, it may not be a sensitive marker in aerobic-trained athletes and therefore has different utilities for different athletic populations. There is likely utility to HRV-guided programming compared to predefined programming in several types of training. Evidence-based preliminary guidelines for the application of HRV in strength and conditioning are discussed. This is an evolving area of research, and more data are needed to evaluate the best practices for applying HRV in strength and conditioning.

Peak Running Velocity vs. Critical Speed: Which One Is Better to Prescribe Endurance Training to Recreational Runners?

ABSTRACT

Figueiredo, DH, Figueiredo, DH, Manoel, FA, and Machado, FA. Peak running velocity vs. critical speed: which one is better to prescribe endurance training to recreational runners? J Strength Cond Res 37(9): 1783-1788, 2023-This study aimed to evaluate the effects of 5 weeks of training prescribed by peak running velocity obtained on the track (Vpeak_TR) and their respective time limit (Tlim), as well as by critical speed (CS), on physiological and endurance performance parameters in recreational runners. Twenty-two male runners were distributed into a Vpeak_TR group (GVP) and CS group (GCS) with a predefined program, alternating moderate-intensity continuous training and high-intensity interval training. Maximum oxygen uptake (V̇O2max), and its respective velocity (vV̇O2max), Vpeak_TR, Tlim at 100% Vpeak_TR, 5-km running performance, CS, and D' (maximum distance covered above CS) were assessed at pretraining and posttraining period. There was a significant increase from pretraining to posttraining in Vpeak_TR (GVP = 4.5 ± 3.1% vs. GCS = 7.5 ± 4.2%), vV̇O2max (GVP = 3.9 ± 3.8% vs. GCS = 8.6 ± 6.7%), and mean velocity 5-km (GVP = 5.6 ± 3.3% vs. GCS = 7.3 ± 3.5%) and decrease in 5-km time (GVP = -5.1 ± 3.0% vs. GCS = -6.8 ± 3.0%). CS and V̇O2max significantly improved in GCS (9.3 ± 8.4% and 6.0 ± 6.8%, respectively), with no difference for GVP (2.8 ± 5.6% and 1.3 ± 8.4%, respectively). No differences were observed between groups for all variables. These findings give further supports to the notion that both variables obtained on the track are valid tools to prescribed training in recreational runners.

Using Arterial Pulse and Laser Doppler Analyses to Discriminate between the Cardiovascular Effects of Different Running Levels

BACKGROUND AND AIMS

Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular and blood-flow perfusion conditions among 3 groups (44 male volunteers) according to the time taken to run 3 km: Level 1, Level 2, and Level 3.

METHODS

The radial blood pressure waveform (BPW), finger photoplethygraphy (PPG), and skin-surface laser-Doppler flowmetry (LDF) signals of the subjects were measured. Frequency-domain analysis was applied to BPW and PPG signals; time- and frequency-domain analyses were applied to LDF signals.

RESULTS

Pulse waveform and LDF indices differed significantly among the three groups. These could be used to evaluate the advantageous cardiovascular effects provided by long-term endurance-running training, such as vessel relaxation (pulse waveform indices), improvement in blood supply perfusion (LDF indices), and changes in cardiovascular regulation activities (pulse and LDF variability indices). Using the relative changes in pulse-effect indices, we achieved almost perfect discrimination between Level 3 and Level 2 (AUC = 0.878). Furthermore, the present pulse waveform analysis could also be used to discriminate between the Level-1 and Level-2 groups.

CONCLUSIONS

The present findings contribute to the development of a noninvasive, easy-to-use, and objective evaluation technique for the cardiovascular benefits of prolonged endurance-running training.

Individually guided training prescription by heart rate variability and self-reported measure of stress tolerance in recreational runners: Effects on endurance performance

The aim of this study was to determine the effect of endurance training individually guided by objective (Heart Rate Variability-HRV) or self-report measure of stress (DALDA-questionnaire) in comparison to predefined endurance training prescription for improving endurance performance in recreational runners. After a 2-week preliminary baseline period to establish resting HRV and self-reported measure of stress, thirty-six male recreational runners were randomly assigned to HRV-guided (G_HRV; n = 12), DALDA-guided (G_D; n = 12) or predefined training (G_T; n = 12) prescription groups. Before and after 5-weeks of endurance training, participants performed a track field peak velocity (V_{peak_TF}), time limit (T_lim) at 100% of V_{peak_TF} and 5 km time-trial (5 km TT) tests. G_D lead to higher improvements in V_{peak_TF} (8.4 ± 1.8%; ES = 1.41) and 5 km TT (-12.8 ± 4.2%; ES = -1.97), than G_HRV (6.6 ± 1.5% and -8.3 ± 2.8%; ES = -1.20; 1.24) and G_T (4.9 ± 1.5% and -6.0 ± 3.3%; ES = -0.82; 0.68), respectively, with no differences for T_lim. Self-report measures of stress may be used to individualize endurance training prescription on a daily basis leading to better performance enhancement, which may be used with HRV for a holistic understanding of daily training-induce adaptations.

Designing an App to Promote Physical Exercise in Sedentary People Using a Day-to-Day Algorithm to Ensure a Healthy Self-Programmed Exercise Training

Heart rate variability (HRV) has allowed the implementation of a methodology for daily decision making called day-to-day training, which allows data to be recorded by anyone with a smartphone. The purpose of the present work was to evaluate the validity and reliability of HRV measurements with a new mobile app (Selftraining UMH) in two resting conditions. Twenty healthy people (10 male and 10 female) were measured at rest in supine and seated positions with an electrocardiogram and an application for smartphones at the same time (Selftraining UMH) using recordings obtained through an already validated chest-worn heart rate monitor (Polar H10). The Selftraining UMH app showed no significant differences compared to an electrocardiogram, neither in supine nor in sitting position (p > 0.05) and they presented almost perfect correlation levels (r ≥ 0.99). Furthermore, no significant differences were found between ultra-short (1-min) and short (5-min) length measurements. The intraclass correlation coefficient showed excellent reliability (>0.90) and the standard error of measurement remained below 5%. The Selftraining UMH smartphone app connected via Bluetooth to the Polar H10 chest strap can be used to register daily HRV recordings in healthy sedentary people.

Individualized Endurance Training Based on Recovery and Training Status in Recreational Runners

PURPOSE

Long-term development of endurance performance requires a proper balance between strain and recovery. Because responses and adaptations to training are highly individual, this study examined whether individually adjusted endurance training based on recovery and training status would lead to greater adaptations compared with a predefined program.

METHODS

Recreational runners were divided into predefined (PD; n = 14) or individualized (IND; n = 16) training groups. In IND, the training load was decreased, maintained, or increased twice a week based on nocturnal heart rate variability, perceived recovery, and heart rate-running speed index. Both groups performed 3-wk preparatory, 6-wk volume, and 6-wk interval periods. Incremental treadmill tests and 10-km running tests were performed before the preparatory period ( T0 ) and after the preparatory ( T1 ), volume ( T2 ), and interval ( T3 ) periods. The magnitude of training adaptations was defined based on the coefficient of variation between T0 and T1 tests (high >2×, low <0.5×).

RESULTS

Both groups improved ( P < 0.01) their maximal treadmill speed and 10-km time from T1 to T3 . The change in the 10-km time was greater in IND compared with PD (-6.2% ± 2.8% vs -2.9% ± 2.4%, P = 0.002). In addition, IND had more high responders (50% vs 29%) and fewer low responders (0% vs 21%) compared with PD in the change of maximal treadmill speed and 10-km performance (81% vs 23% and 13% vs 23%), respectively.

CONCLUSIONS

PD and IND induced positive training adaptations, but the individualized training seemed more beneficial in endurance performance. Moreover, IND increased the likelihood of high response and decreased the occurrence of low response to endurance training.

Heart Rate Variability-Guided Training for Improving Mortality Predictors in Patients with Coronary Artery Disease

The objective of this research was to investigate whether heart rate variability (HRV)-guided training improves mortality predictors to a greater extent than predefined training in coronary artery disease patients. Twenty-one patients were randomly allocated to the HRV-guided training group (HRV-G) or the predefined training group (PRED-G). They measured their HRV at home daily and trained three times a week for six weeks. Resting heart rate, isolated vagal-related HRV indices (i.e., RMSSD, HF, and SD₁), weekly averaged RMSSD, heart rate recovery, and maximum oxygen uptake were assessed before and after the training period. There was a statistically significant difference (p = 0.034) in the change in weekly averaged RMSSD in favor of the HRV-G, while no differences were found in the remaining analyzed variables (p > 0.050). Regardless of the training prescription method, exercise training decreased resting heart rate (p = 0.001; -4.10 [95% CI = -6.37--1.82] beats per minute (bpm)), and increased heart rate recovery at 2 min (p = 0.010; 4.33 [95% CI = 1.15-7.52] bpm) and maximum oxygen uptake (p < 0.001; 3.04 [95% CI = 1.70-4.37] mL·kg^-1·min^-1). HRV-guided training is superior to predefined training in improving vagal-related HRV when methodological factors are accounted for.

Heart rate variability-guided training in professional runners: Effects on performance and vagal modulation

PURPOSE

To analyze the training structure following a heart rate variability (HRV) -guided training or traditional training protocol, determining their effects on the cardiovascular performance of professional endurance runners, and describing the vagal modulation interaction.

METHODS

This was an 8-week cluster-randomized controlled trial. Twelve professional endurance runners were randomly assigned to an HRV-guided training group (HRV-G; n = 6) or a traditional training group (TRAD-G; n = 6). The training methodology followed by the HRV-G was determined by their daily HRV scores. Training intensities were recorded daily. HRV4Training was used to register the rMSSD every morning and during a 60-second period. Cardiovascular outcomes were obtained through an incremental treadmill test. The primary outcome was the maximal oxygen uptake (VO_2max).

RESULTS

Total training volume was significantly higher in TRAD-G, but moderate intensity training was significantly higher in HRV-G (X ± SD_Dif=1.98 ± 0.1%; P = 0.006; d = 1.22) and low intensity training in TRAD-G (X ± SD_Dif=2.03 ± 0.74%; P = 0.004; d = 1.36). The maximal velocity increased significantly in HRV-G (P = 0.027, d = 0.66), while the respiratory exchange ratio increased in TRAD-G (P = 0.017, d = 1). There was a small effect on the LnRMSSD increment (P = 0.365, d = 0.4) in HRV-G. There were statistical inter-group differences in the ∆maximal heart rate when ∆LnrMSSD was considered as a covariable (F = 7.58; P = 0.025; d = 0.487). There were significant and indirect correlations of LnRMSSD_TEST with VO_2max (r =-0.656, P = 0.02), ∆LnrMSSD with ∆VO_2max (r = -0.606, P = 0.037), and ∆LnrMSSD_CV with ∆VENT (r = -0.790, P = 0.002).

CONCLUSIONS

higher HRV scores suggest better cardiovascular adaptations due to higher training intensities, favoring HRV as a measure to optimize individualized training in professional runners.

Novel track field test to determine Vpeak, relationship with treadmill test and 10-km running performance in trained endurance runners

Objectives

The aim of this study was to determine the peak running velocity on the track field (V_{peak_TF}) based on the laboratory treadmill test (V_{peak_T}), and relate the V_peak values as well as their correlation with the 10-km running performance in trained endurance runners.

Method

Twenty male trained endurance runners (age: 29.5 ± 5.3 years; V̇O_2max: 67.5±17.6 ml · kg^-1·min^-1) performed three maximum incremental tests to determine the V_peak: one for V_{peak_T} determination and two to obtain V_{peak_TF} on the official track field (400 m), and a 10-km running performance. During the incremental tests, maximum heart rate (HR_max), maximal rating of perceived exertion (RPE_max), and peak lactate concentration (LA_peak) were determined.

Results

The results showed significant difference between the V_{peak_TF} and V_{peak_T} (18.1 ± 1.2 vs. 19.2 ± 1.5 km·h^-1, respectively), as well as the total time of the tests, the distance traveled and the RPE_max determined during the tests. A high correlation was observed between the V_peak values (r = 0.94), and between V_{peak_TF} and V_{peak_T} with 10-km running performance (r = -0.95 vs. r = -0.89, respectively).

Conclusions

The good agreement and association with V_{peak_T} and high correlation with 10-km running performance demonstrate that the novel track field test is efficient for V_{peak_TF} determination.

Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11344 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (mean bias -0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (mean bias 0.20 ms, p < 0.001) and nocturnal recordings (mean bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

Heart Rate Variability-Guided Training for Enhancing Cardiac-Vagal Modulation, Aerobic Fitness, and Endurance Performance: A Methodological Systematic Review with Meta-Analysis

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.

Monitoring and adapting endurance training on the basis of heart rate variability monitored by wearable technologies: A systematic review with meta-analysis

OBJECTIVES

To systematically perform a meta-analysis of the scientific literature to determine whether the outcomes of endurance training based on heart rate variability (HRV) are more favorable than those of predefined training.

DESIGN

Systematic review and meta-analysis.

METHODS

PubMed and Web of Science were searched systematically in March of 2020 using keywords related to endurance, the ANS, and training. To compare the outcomes of HRV-guided and predefined training, Hedges' g effect size and associated 95% confidence intervals were calculated.

RESULTS

A total of 8 studies (198 participants) were identified comprising 9 interventions involving a variety of approaches. Compared to predefined training, most HRV-guided interventions included fewer moderate- and/or high-intensity training sessions. Fixed effects meta-analysis revealed a significant medium-sized positive effect of HRV-guided training on submaximal physiological parameters (g = 0.296, 95% CI 0.031 to 0.562, p = 0.028), but its effects on performance (g = 0.079, 95% CI -0.050 to 0.393, p = 0.597) and V̇O2peak (g = 0.171, 95% CI -0.213 to 0.371, p = 0.130) were small and not statistically significant. Moreover, with regards to performance, HRV-guided training was associated with fewer non-responders and more positive responders.

CONCLUSIONS

In comparison to predefined training, HRV-guided endurance training had a medium-sized effect on submaximal physiological parameters, but only a small and non-significant influence on performance and V̇O_2peak. There were fewer non-responders regarding performance with HRV-based training.

Effects of Different Training Interventions on Heart Rate Variability and Cardiovascular Health and Risk Factors in Young and Middle-Aged Adults: A Systematic Review

Introduction: Heart rate variability (HRV), the beat-to-beat variation of adjacent heartbeats, is an indicator of the function of the autonomic nervous system (ANS). Increased HRV reflects well-functioning of autonomic control mechanism and cardiovascular health. The aim of this systematic review is to provide a systematic overview of the effects of different physical training modalities on resting HRV and cardiovascular health and risk factors (i.e., baroreflex sensitivity, body fat, body mass, body mass index, blood pressure, heart rate recovery, VO₂ max, and VO₂ peak) in young and middle-aged (mean age of the studies samples up to 44 years), healthy adults.

Methods: A systematic review in accordance with the PRISMA guidelines was performed. Studies investigating the effects of different physical interventions (endurance, resistance, high-intensity, coordinative, or multimodal training) on HRV were included. Trials were considered eligible if the intervention lasted for at least 4 weeks and participants were regarded as general healthy. Five electronic databases were searched from 2005 to September 8th, 2020. The methodological quality of eligible studies was assessed by two study quality and reporting assessment scales (TESTEX and STARD_HRV). PROSPERO registration number: CRD42020206606.

Results: Of 3,991 retrieved records, 26 were considered eligible and analyzed. Twelve studies used an endurance training (of which three included high-intensity sessions), six studies resistance training, four studies coordinative training, two studies high-intensity training, and two studies used a multimodal intervention. Overall, the results showed for all types of intervention an improvement in linear and non-linear HRV parameters and cardiovascular health and risk factors. However, quality assessment revealed some methodological and reporting deficits.

Conclusion: This systematic review highlights the benefits of different types of physical training interventions on autonomic function and health parameters in young and middle-aged, healthy adults. In conclusion, higher training intensities and frequencies are more likely to improve HRV. For future studies, we recommend adhering to the criteria of methodological standards of exercise interventions and HRV measurements and encourage the use of non-linear HRV parameters.

Cardiac-autonomic and hemodynamic responses to a hypertonic, sugar-sweetened sports beverage in physically active men

Hydration practices may confound heart rate variability (HRV) measurements when collected in the pre-training period. We aimed to determine the effects of ingesting a hypertonic, sugar-sweetened sports beverage on HRV and hemodynamic parameters in physically active young men. Fifteen subjects consumed 591 mL of Gatorade (6% carbohydrate, ∼330 mOsmol/kg), 591 mL water, or 10 mL water (control) in random order on separate days following overnight fasting. HRV and hemodynamics were evaluated in 5-min windows immediately before (T1) and 5-10 min (T2), 25-30 min (T3), 40-45 min (T4), and 55-60 min (T5) post-drinking. Root-mean square of successive differences and the standard deviation of normal RR intervals increased post-water intake at all time-points relative to T1 (P < 0.05). No increases were observed post-Gatorade intake, though small effect sizes were noted at T2 and T3 (P > 0.05, ES = 0.27-0.32). Systemic vascular resistance increased at T2 post-Gatorade intake and at T2 and T3 post-water intake (P < 0.05). No interactions were observed for blood pressure measures, stroke volume, or cardiac output. Gatorade does not evoke cardiovascular adjustments to the same magnitude as water. Practitioners should wait at least 45 min to record HRV post-Gatorade intake and >60 min post-water intake. Novelty: Equal volumes of cold water and Gatorade produce inequivalent cardiac-autonomic and hemodynamic responses. HRV responses of greater amplitude and duration were observed following intake of water versus Gatorade. Failure to account for recent fluid intake may result in misinterpretation of autonomic status.

Relationships between Workload, Heart Rate Variability, and Performance in a Recreational Endurance Runner

BACKGROUND

The association between heart rate variability (HRV), training load (TL), and performance is poorly understood.

METHODS

A middle-aged recreational female runner was monitored during a competitive 20-wk macrocycle divided into first (M1) and second mesocycle (M2) in which best performances over 10 km and 21 km were recorded. Volume (km), session rating of perceived exertion (sRPE), TL, and monotony (mean TL/SD TL) were the workload parameters recorded. The root mean square of the successive differences in R-R intervals (RMSSD), its coefficient of variation (RMSSDcv), and the RMSSD:RR ratio were the HRV parameters monitored.

RESULTS

During M2, RMSSD (p = 0.006) and RMSSD:RR (p = 0.002) were significantly increased, while RR was significantly reduced (p = 0.017). Significant correlations were identified between monotony and volume (r = 0.552; p = 0.012), RR (r = 0.447; p = 0.048), and RMSSD:RR (r = -0.458; p = 0.042). A sudden reduction in RMSSD (from 40.31 to 24.34 ms) was observed the day before the first symptoms of an influenza.

CONCLUSIONS

The current results confirm the practicality of concurrent HRV and sRPE monitoring in recreational runners, with the RMSSD:RR ratio indicative of specific adaptations. Excessive training volume may be associated to both elevated monotony and reduced RMSSD:RR. Identification of mesocycle patterns is recommended for better individualization of the periodization used.

Wearable Devices Suitable for Monitoring Twenty Four Hour Heart Rate Variability in Military Populations

Heart rate variability (HRV) measurements provide information on the autonomic nervous system and the balance between parasympathetic and sympathetic activity. A high HRV can be advantageous, reflecting the ability of the autonomic nervous system to adapt, whereas a low HRV can be indicative of fatigue, overtraining or health issues. There has been a surge in wearable devices that claim to measure HRV. Some of these include spot measurements, whilst others only record during periods of rest and/or sleep. Few are capable of continuously measuring HRV (≥24 h). We undertook a narrative review of the literature with the aim to determine which currently available wearable devices are capable of measuring continuous, precise HRV measures. The review also aims to evaluate which devices would be suitable in a field setting specific to military populations. The Polar H10 appears to be the most accurate wearable device when compared to criterion measures and even appears to supersede traditional methods during exercise. However, currently, the H10 must be paired with a watch to enable the raw data to be extracted for HRV analysis if users need to avoid using an app (for security or data ownership reasons) which incurs additional cost.

Changes in Short-Term and Ultra-Short Term Heart Rate, Respiratory Rate, and Time-Domain Heart Rate Variability Parameters during Sympathetic Nervous System Activity Stimulation in Elite Modern Pentathlonists-A Pilot Study

Monitoring of markers reflecting cardiac autonomic activity before and during stressful situations may be useful for identifying the physiological state of an athlete and may have medical or performance implications. The study aimed to determine group and individual changes in short-term (5 min) and ultra-short-term (1 min) heart rate (HR), respiratory rate (RespRate), and time-domain heart rate variability (HRV) parameters during sympathetic nervous system activity (SNSa) stimulation among professional endurance athletes. Electrocardiographic recordings were performed in stable measurement conditions (Baseline) and during SNSa stimulation via isometric handgrip in 12 elite modern pentathlonists. Significant increases in short-term HR and decreases in time-domain HRV parameters with no changes in RespRate were observed during SNSa stimulation. Significant differences were observed between Baseline (all minutes) and the last (i.e., 5th) minute of SNSa stimulation for ultra-short-term parameters. Analysis of intra-individual changes revealed some heterogeneity in responses. The study provides baseline responses of HR, RespRate, and time-domain HRV parameters to SNSa stimulation among elite pentathlonists, which may be useful for identifying abnormal responses among fatigued or injured (e.g., concussed) athletes. More attention to individual analysis seems to be necessary when assessing physiological responses to sympathetic stimuli in professional endurance athletes.

Effectiveness of Training Prescription Guided by Heart Rate Variability Versus Predefined Training for Physiological and Aerobic Performance Improvements: A Systematic Review and Meta-Analysis

A systematic review and meta-analysis were performed to determine if heart rate variability-guided training (HRV-g), compared to predefined training (PT), maximizes the further improvement of endurance physiological and performance markers in healthy individuals. This analysis included randomized controlled trials assessing the effects of HRV-g vs. PT on endurance physiological and performance markers in untrained, physically active, and well-trained subjects. Eight articles qualified for inclusion. HRV-g training significantly improved maximum oxygen uptake (VO2max) (MD = 2.84, CI: 1.41, 4.27; p < 0.0001), maximum aerobic power or speed (WMax) (SMD = 0.66, 95% CI 0.33, 0.98; p < 0.0001), aerobic performance (SMD = 0.71, CI 0.16, 1.25; p = 0.01) and power or speed at ventilatory thresholds (VT) VT1 (SMD = 0.62, CI 0.04, 1.20; p = 0.04) and VT2 (SMD = 0.81, CI 0.41, 1.22; p < 0.0001). However, HRV-g did not show significant differences in VO2max (MD = 0.96, CI −1.11, 3.03; p = 0.36), WMax (SMD = 0.06, CI −0.26, 0.38; p = 0.72), or aerobic performance (SMD = 0.14, CI −0.22, 0.51; p = 0.45) in power or speed at VT1 (SMD = 0.27, 95% CI −0.16, 0.70; p = 0.22) or VT2 (SMD = 0.18, 95% CI −0.20, 0.57; p = 0.35), when compared to PT. Although HRV-based training periodization improved both physiological variables and aerobic performance, this method did not provide significant benefit over PT.

HRV-Based Training for Improving VO2max in Endurance Athletes. A Systematic Review with Meta-Analysis

This review aimed to synthesize evidence regarding interventions based on heart rate variability (HRV)-guided training for VO_2max improvements in endurance athletes and address the issues that impact this performance enhancement. The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, CINAHL Complete, the Web of Science Core Collection, Global Health, Current Contents Connect, and the SciELO citation index were searched. Inclusion criteria were: randomized controlled trials; studies with trained athletes enrolled in any regular endurance training; studies that recruited men, women, and both sexes combined; studies on endurance training controlled by HRV; studies that measured performance with VO_2max. A random-effects meta-analysis calculating the effect size (ES) was used. Moderator analyses (according to the athlete's level and gender) and metaregression (according to the number of participants in each group) were undertaken to examine differences in ES. HRV-guided training and control training enhanced the athletes' VO_2max (p < 0.0001), but the ES for the HRV-guided training group was significantly higher (p < 0.0001; ES_HRVG-CG = 0.187). The amateur level and female subgroup reported better and significant results (p < 0.0001) for VO_2max. HRV-guided training had a small (ES = 0.402) but positive effect on endurance athlete performance (VO_2max), conditioned by the athlete's level and sex.

Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review

Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre- and post-intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV-based interventions reduced the amount of moderate- and/or high-intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV-based training. Peak oxygen uptake ( V ˙ O 2 peak ) and submaximal running parameters (eg, LT1, LT2) improved following both HRV-based and predefined training, with no clear difference in the extent of improvement in V ˙ O 2 peak . Submaximal running parameters tended to improve more following HRV-based training. Research findings to date have been limited and inconsistent. Both HRV-based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.

HRV-Guided Training for Professional Endurance Athletes: A Protocol for a Cluster-Randomized Controlled Trial

Physiological training responses depend on sympathetic (SNS) and parasympathetic nervous system (PNS) balance. This activity can be measured using heart rate variability (HRV). Such a measurement method can favor individualized training planning to improve athletes’ performance. Recently, HRV-guided training has been implemented both on professional and amateur sportsmen and sportswomen with varied results. There is a dearth of studies involving professional endurance athletes following a defined HRV-guided training protocol. The objectives of the proposed protocol are: (i) to determine changes in the performance of high-level athletes after following an HRV-guided or a traditional training period and (ii) to determine differences in the athletes’ performance after following both training protocols. This will be a 12-week cluster-randomized controlled protocol in which professional athletes will be assigned to an HRV-based training group (HRV-G) or a traditional-based training group (TRAD-G). TRAD-G will train according to a predefined training program. HRV-G training will depend on the athletes’ daily HRV. The maximal oxygen uptake (VO_2max) attained in an incremental treadmill test will be considered as the primary outcome. It is expected that this HRV-guided training protocol will improve functional performance in the high-level athletes, achieving better results than a traditional training method, and thus providing a good strategy for coaches of high-level athletes.

Minimal Stabilization Time for Ultra-short Heart Rate Variability Measurements in Professional Soccer

The main aims of this study were: 1) to compare 1-minute RMSSD measurements using different stabilization times between them and also with the criterion; and 2) to determine the agreement between every 1-minute RMSSD measurement with the criterion in professional soccer players. Seven hundred eighteen HRV measurements from professional soccer players were taken. HRV was calculated from 5 to 10 minutes (criterion) and from 1-minute windows with different pre-stabilization times. Friedman and post-hoc tests were applied to compare 1-minute and criterion measurements. Effect size was considered to describe magnitude of change. To determine agreement, Spearman’s correlation was applied, and Bland–Altman analysis was also done between each ultra-short HRV time window and the 5-minute HRV criterion period. The 1-minute HRV without any pre-stabilization time was the only one different from all the other 1-minute measurements that included 1 or more minutes of pre-stabilization (p<0.001). One-minute HRV measurements with 1 or more minutes of pre-stabilisation were highly correlated with those for the criterion period. One-minute HRV without pre-stabilization showed the lowest correlation and the highest bias from the criterion. It is concluded that 1-minute HRV measurements with a prior 1-minute or longer pre-stabilization time are valid to measure HRV in professional male soccer players.

New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy?

In the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.

Determination of minimal recording period to assess resting heart rate variability during pregnancy

Traditionally, resting heart rate variability (rHRV) is measured for 10 min using the last 5 min for analyses (e.g., criterion period). It is unknown whether the measurement period can be shortened in pregnant women as there are currently no established standards. We aimed to compare shorter time segments (e.g., from the 1st to 10th minutes) of the parasympathetic index natural logarithm transformation of root mean square of successive R–R differences (Ln rMSSD) with the criterion period in pregnant and nonpregnant women. Twelve pregnant (age: 30.8 ± 3.4 years; gestational age: 20.1 ± 5.0 weeks) and 15 nonpregnant women (age: 29.8 ± 4.0 years) were included. rHRV was measured using a portable heart rate monitor for 10 min while sitting. Ln rMSSD difference/agreement between shorter time segments and criterion period was analyzed. The result observed between the 4th–5th minutes was the shortest time segment not different from/highly agreed with the criterion period in pregnant women (difference [95% confidence interval (CI)]: −0.10 [−0.22 to 0.02]/bias ± 1.96 × SD: −0.06 [−0.38 to 0.25]). In nonpregnant women, the 2nd–3rd-minute segment was the shortest with similar results (difference [95% CI]: −0.04 [−0.15 to 0.07]/bias ± 1.96 × SD: −0.03 [−0.39 to 0.32]). The Ln rMSSD was found to be stable from the 5th–10th minutes and the 3rd–10th minutes in pregnant and nonpregnant women, respectively. A shortened rHRV assessment can increase its applicability in clinical/exercise-training settings.

Novelty Ln rMSSD can be measured for 5 min in pregnant women, with the last 1-min segment analyzed. The last 1-min segment from 3 min can be used for rHRV measurement in nonpregnant women. The shortened rHRV assessment can facilitate its applicability in clinical/exercise-training settings.

Factors Affecting Training and Physical Performance in Recreational Endurance Runners

Endurance running has become an immensely popular sporting activity, with millions of recreational runners around the world. Despite the great popularity of endurance running as a recreational activity during leisure time, there is no consensus on the best practice for recreational runners to effectively train to reach their individual objectives and improve physical performance in a healthy manner. Moreover, there are lots of anecdotal data without scientific support, while most scientific evidence on endurance running was developed from studies observing both recreational and professional athletes of different levels. Further, the transference of all this information to only recreational runners is difficult due to differences in the genetic predisposition for endurance running, the time available for training, and physical, psychological, and physiological characteristics. Therefore, the aim of this review is to present a selection of scientific evidence regarding endurance running to provide training guidelines to be used by recreational runners and their coaches. The review will focus on some key aspects of the training process, such as periodization, training methods and monitoring, performance prediction, running technique, and prevention and management of injuries associated with endurance running.

Short-Term Cardiac Autonomic Recovery after a Repeated Sprint Test in Young Soccer Players

The aim of this study was to describe the time course (within 2 h post-exercise) of heart rate variability (HRV) recovery following a traditional repeated sprint ability (RSA) test applied to youth soccer players. Twenty-four young soccer players (18.4 ± 0.5 years) undertook the following assessments: (1) 10 min rest in the seated position for HRV assessment; (2) a repeated sprint ability (RSA) test; (3) passive recovery in the seated position for 10 min, immediately after finishing the RSA test and 1 h and 2 h post-RSA test. During the HRV measurements (using the natural log of root mean square difference of successive normal RR intervals—lnRMSSD) the participants were instructed to assume a comfortable sitting position, remaining awake and breathing spontaneously for 10 min. Magnitude-based inference was used in the analyses. After the RSA test, the post-1 h measure was almost certainly lower than the resting measure, but almost certainly higher than the lnRMSSD measured post-RSA test. The lnRMSSD post-2 h was likely lower than the resting lnRMSSD and very likely higher than post-1 h. In conclusion, lnRMSSD is severely depressed after performing an RSA test, and reactivation is incomplete after 2 h of passive recovery. This result should be considered by practitioners when applying successive training sessions within intervals shorter than 2 h.

Effect of individualized resistance training prescription with heart rate variability on individual muscle hypertrophy and strength responses

The aim of the present study was to investigate if resistance training (RT), performed with individualized recovery between sessions (RT-IND), promotes greater gains in strength and muscle mass and reduces the variability on adaptations compared to RT with fixed recovery intervals (RT-FIX). Twenty young men (age 21.9 ± 3.3 years) were randomized in the RT-IND and RT-FIX groups. Five days before the beginning of the training, measurements of the root mean square of successive R-R intervals differences (RMSSD) values of each individual were performed to establish the baseline values. Before each RT session, the RMSSD values determined whether the participants from RT-IND protocol were recovered from the previous session. Participants performed the RT session only if RMSSD values had returned to the baseline, otherwise they had to wait for an additional 24 h. RT-FIX performed an RT session every 48 h. Muscle strength was measured by one-maximal repetition (1-RM) test and muscle cross-section area (CSA) of the vastus laterals by ultrasonography were assessed pre- and post-training. 1-RM values increased significantly from pre to post-training for both groups (RT-IND: 30% and RT-FIX: 42%, main time effect, P < 0001), with no significant difference between groups. Muscle CSA increased significantly from pre to post-training (RT-IND: 15.7% and RT-FIX: 15.8%, main time effect, P < 0001), with no significant difference between groups. In conclusion, RT-IND did not increase the gains in muscle strength and mass neither reduce the variability in muscle adaptations when compared to the RT-FIX.

Heart Rate Monitoring in Team Sports-A Conceptual Framework for Contextualizing Heart Rate Measures for Training and Recovery Prescription

A comprehensive monitoring of fitness, fatigue, and performance is crucial for understanding an athlete's individual responses to training to optimize the scheduling of training and recovery strategies. Resting and exercise-related heart rate measures have received growing interest in recent decades and are considered potentially useful within multivariate response monitoring, as they provide non-invasive and time-efficient insights into the status of the autonomic nervous system (ANS) and aerobic fitness. In team sports, the practical implementation of athlete monitoring systems poses a particular challenge due to the complex and multidimensional structure of game demands and player and team performance, as well as logistic reasons, such as the typically large number of players and busy training and competition schedules. In this regard, exercise-related heart rate measures are likely the most applicable markers, as they can be routinely assessed during warm-ups using short (3–5 min) submaximal exercise protocols for an entire squad with common chest strap-based team monitoring devices. However, a comprehensive and meaningful monitoring of the training process requires the accurate separation of various types of responses, such as strain, recovery, and adaptation, which may all affect heart rate measures. Therefore, additional information on the training context (such as the training phase, training load, and intensity distribution) combined with multivariate analysis, which includes markers of (perceived) wellness and fatigue, should be considered when interpreting changes in heart rate indices. The aim of this article is to outline current limitations of heart rate monitoring, discuss methodological considerations of univariate and multivariate approaches, illustrate the influence of different analytical concepts on assessing meaningful changes in heart rate responses, and provide case examples for contextualizing heart rate measures using simple heuristics. To overcome current knowledge deficits and methodological inconsistencies, future investigations should systematically evaluate the validity and usefulness of the various approaches available to guide and improve the implementation of decision-support systems in (team) sports practice.

Agreement between Electrocardiogram and Heart Rate Meter Is Low for the Measurement of Heart Rate Variability during Exercise in Young Endurance Horses

Analysis of the heart rate variability (HRV) gains more and more importance in the assessment of training practice and welfare in equine industry. It relies on mathematical analyses of reliably and accurately measured variations in successive inter-beat intervals, measured as RR intervals. Nowadays, the RR intervals can be obtained through two different techniques: a heart rate meter (HRM) or an electrocardiogram (ECG). The agreement and reliability of these devices has not been fully assessed, especially for recordings during exercise. The purpose of this study was to assess the agreement of two commercially available devices using the two mentioned techniques (HRM vs ECG) for HRV analysis during a standardized exercise test. Simultaneous recordings obtained during light exercise and during canter with both devices were available for 36 horses. Data were compared using a Bland–Altman analysis and the Lin’s coefficient. The agreement between the assessed HRV measures from the data obtained from the ECG and HRM was acceptable only for the mean RR interval and the mean heart rate. For the other studied measures (SDNN, root mean square of successive differences, SD1, SD2, low frequency, high frequency), the agreement between the devices was too poor for them to be considered as interchangeable in these recording conditions. The agreement tended also to be worse when speed of the exercise increased. Therefore, it is necessary to be careful when interpreting and comparing results of HRV analysis during exercise, as the results will depend upon recording devices. Furthermore, corrections and data processing included in the software of the devices affect largely the output used in the subsequent HRV analysis; this must be considered in the choice of the device.