Individual Endurance Training Prescription with Heart Rate Variability

Morning versus Nocturnal Heart Rate and Heart Rate Variability Responses to Intensified Training in Recreational Runners

BACKGROUND

Resting heart rate (HR) and HR variability (HRV) are widely used parameters to assess cardiac autonomic nervous system function noninvasively. While resting assessments can be performed during sleep or after awakening, it would be relevant to know how interchangeable the results of these measurements are. This study aimed at examining the alignment between nocturnal and morning assessments during regular endurance training and in response to intensive training. A total of 24 recreational runners performed a 3-week baseline period (BL) and a 2-week overload (OL) period (Lucia's training impulse + 80%). Their running performance was assessed with a 3000-m running test after the BL and OL. The participants recorded daily their nocturnal HR and HRV (the natural logarithm of the root mean square of successive differences; LnRMSSD) with a photoplethysmography-based wrist device and performed an orthostatic test (2-min supine, 2-min standing) every morning with a chest-strap HR sensor. The HR and LnRMSSD segments that were analyzed from the nocturnal recordings included start value (SleepStart), end value (SleepEnd), first 4-h segment 30 min after detected sleep onset (Sleep4h), and full sleep time (SleepFull). The morning segments consisted of the last-minute average in both body positions. All segments were compared at BL and in response to the 3000-m test and OL.

RESULTS

All nocturnal HR and LnRMSSD segments correlated with supine and standing segments at BL (r = 0.42 to 0.91, p < 0.05). After the 3000-m test, the HR increased and LnRMSSD decreased only in the SleepStart, Sleep4h, and SleepFull segments (p < 0.05). In response to the OL, the standing HR decreased (p < 0.01), while the LnRMSSD increased (p < 0.05) in all segments except for SleepStart. The Pearson correlations between relative changes in nocturnal and morning segments were - 0.11 to 0.72 (3000-m) and - 0.25 to 0.79 (OL). The OL response in Sleep4h HR and LnRMSSD correlated with the relative change in 3000-m time (r = 0.63, p = 0.001 and r=-0.50, p = 0.013, respectively).

CONCLUSIONS

Nocturnal and morning HR and LnRMSSD correlated moderately or highly in the majority of cases during the BL, but their responses to intensive training were not similarly aligned, especially in LnRMSSD. The nocturnal segments seemed to be sensitive to physical loading, and their responses were associated with the performance-related training responses.

Durability in recreational runners: effects of 90-min low-intensity exercise on the running speed at the lactate threshold

PURPOSE

Recent studies have suggested that the capability to resist deterioration of physiological characteristics could be an independent factor contributing to endurance performance. This study aimed at investigating whether prolonged low-intensity exercise induces shifts in the lactate threshold, and whether fatigue-induced changes differ between the sexes.

METHODS

A total of 31 (15 females) recreational runners performed an incremental treadmill test and a 90-min low-intensity exercise (LIT90) on two separate occasions. The LIT90 was performed at 90% of the first lactate threshold speed (LT1v), derived from the incremental treadmill test. The LT1v was determined from a 5-stage (3 min) submaximal threshold test (SubmaxLT), performed before and after LIT90. The SubmaxLTs were followed by a 10/5 reactivity jump test. Respiratory gases, heart rate (HR), and HR-derived detrended fluctuation analysis alpha 1 (DFA-a1) were assessed every 15 min during the LIT90.

RESULTS

A significant decrease (p < 0.01) was observed in the LT1v in females (- 5.8 ± 4.4%) and in males (- 5.3 ± 6.4%). The HR increased (p < 0.001) similarly in females (5.9 ± 3.1%) and in males (5.5 ± 3.6%) during the LIT90, while energy expenditure increased (3.1 ± 4.5%, p = 0.013) in females but remained unchanged in males (0.9 ± 3.1%). Change in DFA-a1 during the LIT90 was the only marker that correlated significantly with the relative change of LT1v (r = 0.463, p = 0.013).

CONCLUSION

LIT90 induced significant decreases in the LT1v, and the changes were comparable between sexes. DFA-a1 could be a potential intra-session marker of durability.

Monitoring Within-Individual Dose-Response Relationships in Professional Soccer Players: The Importance of Fitness Level

PURPOSE

To (1) examine within-individual player dose-response associations between selected training-load measures and changes in aerobic fitness level via submaximal exercise heart rate (HRex%) and (2) measure the relationships between these dose-response associations with basal HRex% (to study the influence of fitness level on dose-response relationship).

METHODS

During an in-season phase, selected training-load measures including total minutes, total distance, mechanical work (the sum number of accelerations and decelerations > 3 m2), high metabolic load distance, and Edwards' training impulse were collected via Global Positioning System and heart-rate sensors for analyzing accumulated load. A submaximal warm-up test was used repeatedly before and after 9 phases to elicit HRex% and track fitness changes at an individual level.

RESULTS

Negative to positive extensive ranges of within-individual associations were found among players for different metrics (r = -.84 to .89). The relationship between pooled HRex% (basal fitness) and dose-response correlations showed inverse very large (r = -.71) and large (r = -.65) values for accumulated weekly minutes and distance. However, moderate values were found for all other measures (r = -.35 to -.42).

CONCLUSIONS

Individual players show extensive different ranges of dose-response associations with training measures. The dose-response association is influenced by players' fitness level, and players with lower fitness levels show stronger inverse relationships with accumulated minutes and total distance.

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.

Time-Course of Changes in Multidimensional Fatigue and Functional Exercise Capacity and Their Associations during a Short Inpatient Pulmonary Rehabilitation Program

This study aimed to assess the time-course of changes in multidimensional fatigue and functional exercise capacity and their associations during an inpatient pulmonary rehabilitation (PR) program. Seventy COPD patients from three centres were enrolled for a four-week PR program and were evaluated before (T0) and at the end of each week (T1, T2, T3, and T4). Weekly change in multidimensional fatigue was assessed by the multidimensional inventory questionnaire (MFI-20) and functional exercise capacity by the 6-minute walking distance (6MWD). Reaction time (RT) and heart rate variability (HRV) were also assessed as complementary markers of fatigue. HRV did not change during the study (all p > 0.05). MFI-20 score and RT decreased during the first part of the program (p < 0.001) and levelled off at T2 (all p > 0.05 compared with each preceding time). While 6MWD improved by almost 70% during the first part of the PR, it continued to increase, albeit at a greatly reduced pace, between T2 and T4 (p < 0.05). In parallel, a negative association was found between MFI-20 score and 6MWD at each evaluation time (r ranged from 0.43 to 0.71), with a significantly stronger T3 correlation compared with the other time periods (all p < 0.05). The strengthening of the association between fatigue and functional exercise capacity at T3, which occurred concomitantly with the slowdown of functional exercise capacity improvement, is consistent with a role for fatigue in the limitation of performance changes during PR. The limitation of fatigue during PR is thus an interesting aspect to improve the magnitude of performance changes.

Application of Multiscale Sample Entropy in Assessing Effects of Exercise Training on Skin Blood Flow Oscillations in People with Spinal Cord Injury

Spinal cord injury (SCI) causes a disruption of autonomic nervous regulation to the cardiovascular system, leading to various cardiovascular and microvascular diseases. Exercise training is an effective intervention for reducing risk for microvascular diseases in healthy people. However, the effectiveness of exercise training on improving microvascular function in people with SCI is largely unknown. The purpose of this study was to compare blood flow oscillations in people with spinal cord injury and different physical activity levels to determine if such a lifestyle might influence skin blood flow. A total of 37 participants were recruited for this study, including 12 athletes with SCI (ASCI), 9 participants with SCI and a sedentary lifestyle (SSCI), and 16 healthy able-bodied controls (AB). Sacral skin blood flow (SBF) in response to local heating at 42 °C for 50 min was measured using laser Doppler flowmetry. The degree of the regularity of blood flow oscillations (BFOs) was quantified using a multiscale entropy approach. The results showed that BFO was significantly more irregular in ASCI and AB compared to SSCI during the maximal vasodilation period. Our results also demonstrate that the difference in the regularity of BFOs between original SBF signal and phase-randomized surrogate time series was larger in ASCI and AB compared to SSCI. Our findings indicate that SCI causes a loss of complexity of BFOs and exercise training may improve complexity in people with SCI. This study demonstrates that multiscale entropy is a sensitive method for detecting differences between different categories of people with SCI and might be able to detect effects of exercise training related to skin blood flow.

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.

Practices and Applications of Heart Rate Variability Monitoring in Endurance Athletes

Heart rate variability reflects fluctuations in the changes in consecutive heartbeats, providing insight into cardiac autonomic function and overall physiological state. Endurance athletes typically demonstrate better cardiac autonomic function than non-athletes, with lower resting heart rates and greater variability. The availability and use of heart rate variability metrics has increased in the broader population and may be particularly useful to endurance athletes. The purpose of this review is to characterize current practices and applications of heart rate variability analysis in endurance athletes. Important considerations for heart rate variability analysis will be discussed, including analysis techniques, monitoring tools, the importance of stationarity of data, body position, timing and duration of the recording window, average heart rate, and sex and age differences. Key factors affecting resting heart rate variability will be discussed, including exercise intensity, duration, modality, overall training load, and lifestyle factors. Training applications will be explored, including heart rate variability-guided training and the identification and monitoring of maladaptive states such as overtraining. Lastly, we will examine some alternative uses of heart rate variability, including during exercise, post-exercise, and for physiological forecasting and predicting performance.

Central and Peripheral Fatigue in Recreational Trail Runners: A Pilot Study

BACKGROUND

Understanding fatigue mechanisms is crucial for exercise performance. However, scientific evidence on non-invasive methods for assessing fatigue in trail running competitions is scarce, especially when vertical kilometer trail running races (VK) are considered. The main purpose of this study was to assess the autonomic nervous system (ANS) activity (i.e., central fatigue) and the state of muscle activation (i.e., peripheral fatigue) before and after a VK competition.

METHODS

A cross-sectional pilot study was performed. After applying inclusion/exclusion criteria, 8 recreational male trail runners (31.63 ± 7.21 yrs, 1.75 m ± 0.05 m, 70.38 ± 5.41 kg, BMI: 22.88 ± 0.48, running experience: 8.0 ± 3.63 yrs, weekly training volume: 58.75 ± 10.35 km) volunteered to participate and were assessed for both central (i.e., via heart rate variability, HRV) and peripheral (via tensiomyography, TMG) fatigue before and after a VK race.

RESULTS

After the VK, resting heart rate, RMSSD (p = 0.01 for both) and SDNN significantly decreased (p = 0.02), while the stress score and the sympathetic-parasympathetic ratio increased (p = 0.01 and p = 0.02, respectively). The TMG analyses suggest that runners already suffered peripheral fatigue before the VK and that 20-30 min are enough for muscular recovery after the race. In summary, our data suggest that participants experienced a pre-competition fatigue status. Further longitudinal studies are necessary to investigate the mechanisms underlying fatigue during trail running races, while training periodization and tapering strategies could play a key role for minimizing pre-competition fatigue status.

Fractal correlation properties of HRV as a noninvasive biomarker to assess the physiological status of triathletes during simulated warm-up sessions at low exercise intensity: a pilot study

BACKGROUND

The non-linear index alpha 1 of Detrended Fluctuation Analysis (DFA a1) of heart rate variability, has been shown to be a marker of fatigue during endurance exercise. This report aims to explore its ability to assess the physiological status as a surrogate metric for "readiness to train" while performing simulated warm-up sessions the day after two different exercise sessions.

METHODS

11 triathletes were recruited to determine the first ventilatory threshold (VT1) during a baseline assessment and to perform 10-min of cycling at 90% of VT1 (simulating a warm-up bout) before (PRE) and within 36 h after (POST) light and heavy running exercise. RR intervals were recorded for DFA a1 analysis along with neuromuscular testing to verify the effects of the performed exercise sessions. In addition to common statistical methods, magnitude-based inferences (MBI) were applied to assess the changes in true score and thus also the practical relevance of the magnitude.

RESULTS

Rating of perceived exertion for the heavy exercise session showed a significant higher rating as opposed to the light exercise session (p < 0.001, d = 0.89). In regard of MBIs, PRE versus POST comparisons revealed a significant reduced DFA a1 with large effect size after the heavy exercise session (p = 0.001, d = - 1.44) and a 99% chance that this negative change was clinically relevant.

CONCLUSIONS

Despite inter-individual differences, DFA a1 offers potential to assess physiological status and guide athletes in their training as an easy-to-apply monitoring procedure during a standardized warm-up. A regular assessment including individual data history and statistical references for identification of response is recommended. Further data are necessary to confirm the results in a larger and more homogeneous population.

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.

Evaluating the Typical Day-to-Day Variability of WHOOP-Derived Heart Rate Variability in Olympic Water Polo Athletes

Heart rate (HR) and HR variability (HRV) can be used to infer readiness to perform exercise in athletic populations. Advancements in the photoplethysmography technology of wearable devices such as WHOOP allow for the frequent and convenient measurement of HR and HRV, and therefore enhanced application in athletes. However, it is important that the reliability of such technology is acceptable prior to its application in practical settings. Eleven elite male water polo players (age 28.8 ± 5.3 years [mean ± standard deviation]; height 190.3 ± 3.8 cm; body mass 95.0 ± 6.9 kg; international matches 117.9 ± 92.1) collected their HR and HRV daily via a WHOOP strap (WHOOP 3.0, CB Rank, Boston, MA, USA) over 16 weeks ahead of the 2021 Tokyo Olympic Games. The WHOOP strap quantified HR and HRV via wrist-based photoplethysmography during overnight sleep periods. The weekly (i.e., 7-day) coefficient of variation in lnRMSSD (lnRMSSD_CV) and HR (HR_CV) was calculated as a measure of day-to-day variability in lnRMSSD and HR, and presented as a mean of the entire recording period. The mean weekly lnRMSSD_CV and HR_CV over the 16-week period was 5.4 ± 0.7% (mean ± 95% confidence intervals) and 7.6 ± 1.3%, respectively. The day-to-day variability in WHOOP-derived lnRMSSD and HR is within or below the range of day-to-day variability in alternative lnRMSSD (~3-13%) and HR (~10-11%) assessment protocols, indicating that the assessment of HR and HRV by WHOOP does not introduce any more variability than that which is naturally present in these variables.

Validity of the Polar H10 Sensor for Heart Rate Variability Analysis during Resting State and Incremental Exercise in Recreational Men and Women

Heart rate variability (HRV) is frequently applied in sport-specific settings. The rising use of freely accessible applications for its recording requires validation processes to ensure accurate data. It is the aim of this study to compare the HRV data obtained by the Polar H10 sensor chest strap device and an electrocardiogram (ECG) with the focus on RR intervals and short-term scaling exponent alpha 1 of Detrended Fluctuation Analysis (DFA a1) as non-linear metric of HRV analysis. A group of 25 participants performed an exhaustive cycling ramp with measurements of HRV with both recording systems. Average time between heartbeats (RR), heart rate (HR) and DFA a1 were recorded before (PRE), during, and after (POST) the exercise test. High correlations were found for the resting conditions (PRE: r = 0.95, rc = 0.95, ICC3,1 = 0.95, POST: r = 0.86, rc = 0.84, ICC3,1 = 0.85) and for the incremental exercise (r > 0.93, rc > 0.93, ICC3,1 > 0.93). While PRE and POST comparisons revealed no differences, significant bias could be found during the exercise test for all variables (p < 0.001). For RR and HR, bias and limits of agreement (LoA) in the Bland−Altman analysis were minimal (RR: bias of 0.7 to 0.4 ms with LoA of 4.3 to −2.8 ms during low intensity and 1.3 to −0.5 ms during high intensity, HR: bias of −0.1 to −0.2 ms with LoA of 0.3 to −0.5 ms during low intensity and 0.4 to −0.7 ms during high intensity). DFA a1 showed wider bias and LoAs (bias of 0.9 to 8.6% with LoA of 11.6 to −9.9% during low intensity and 58.1 to −40.9% during high intensity). Linear HRV measurements derived from the Polar H10 chest strap device show strong agreement and small bias compared with ECG recordings and can be recommended for practitioners. However, with respect to DFA a1, values in the uncorrelated range and during higher exercise intensities tend to elicit higher bias and wider LoA.

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.

Physiological, Perceptual, and Performance Responses to the 2-Week Block of High- versus Low-Intensity Endurance Training

PURPOSE

This study examined the physiological, perceptual, and performance responses to a 2-wk block of increased training load and compared whether responses differ between high-intensity interval (HIIT) and low-intensity training (LIT).

METHODS

Thirty recreationally trained males and females performed a 2-wk block of 10 HIIT sessions (INT, n = 15) or 70% increased volume of LIT (VOL, n = 15). Running time in the 3000 m and basal serum and urine hormone concentrations were measured before (T1) and after the block (T2), and after a recovery week (T3). In addition, weekly averages of nocturnal heart rate variability (HRV) and perceived recovery were compared with the baseline.

RESULTS

Both groups improved their running time in the 3000 m from T1 to T2 (INT = -1.8% ± 1.6%, P = 0.003; VOL = -1.4% ± 1.7%, P = 0.017) and from T1 to T3 (INT = -2.5% ± 1.6%, P < 0.001; VOL = -2.2% ± 1.9%, P = 0.001). Resting norepinephrine concentration increased in INT from T1 to T2 (P = 0.01) and remained elevated at T3 (P = 0.018). The change in HRV from the baseline was different between the groups during the first week (INT = -1.0% ± 2.0% vs VOL = 1.8% ± 3.2%, P = 0.008). Muscle soreness increased only in INT (P < 0.001), and the change was different compared with VOL across the block and recovery weeks (P < 0.05).

CONCLUSIONS

HIIT and LIT blocks increased endurance performance in a short period. Although both protocols seemed to be tolerable for recreational athletes, a HIIT block may induce some negative responses such as increased muscle soreness and decreased parasympathetic activity.

Validity and reliability of different smartphones applications to measure HRV during short and ultra-short measurements in elite athletes

BACKGROUND AND OBJECTIVE

Heart rate variability (HRV) has been proposed as a useful marker that can show the performance adaptation and optimize the training process in elite athletes. The development of wearable technology permits the measurement of this marker through smartphone applications. The purpose of this study is to assess the validity and reliability of short and ultra-short HRV measurements in elite cyclists using different smartphone applications.

METHOD

Twenty-six professional cyclists were measured at rest in supine and in seated positions through the simultaneous use of an electrocardiogram and two different smartphone applications that implement different technologies to measure HRV: Elite HRV (with a chest strap) and Welltory (photoplethysmography). Level of significance was set at p < 0.05.

RESULTS

Compared to an electrocardiogram, Elite HRV and Welltory showed no differences neither in supine nor in seated positions (p > 0.05) and they showed very strong to almost perfect correlation levels (r = 0.77 to 0.94). Furthermore, no differences were found between short (5 min) and ultra-short (1 min) length measurements. Intraclass correlation coefficient showed good to excellent reliability and the standard error of measurement remained lower than 6%.

CONCLUSION

Both smartphone applications can be implemented to monitor HRV using short- and ultra-short length measurements in elite endurance athletes.

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.

High-Intensity Functional Training Guided by Individualized Heart Rate Variability Results in Similar Health and Fitness Improvements as Predetermined Training with Less Effort

Heart rate variability (HRV) may be useful for prescribing high-intensity functional training (HIFT) exercise programs. This study aimed to compare effects of HRV-guided and predetermined HIFT on cardiovascular function, body composition, and performance.

METHODS

Recreationally-active adults (n = 55) were randomly assigned to predetermined HIFT (n = 29, age = 24.1 ± 4.1 years) or HRV-guided HIFT (n = 26, age = 23.7 ± 4.5) groups. Both groups completed 11 weeks of daily HRV recordings, 6 weeks of HIFT (5 d·week-1), and pre- and post-test body composition and fitness assessments. Meaningful changes in resting HRV were used to modulate (i.e., reduce) HRV-guided participants' exercise intensity. Linear mixed models were used with Bonferroni post hoc adjustment for analysis.

RESULTS

All participants significantly improved resting heart rate, lean mass, fat mass, strength, and work capacity. However, no significant between-groups differences were observed for cardiovascular function, body composition, or fitness changes. The HRV-guided group spent significantly fewer training days at high intensity (mean difference = -13.56 ± 0.83 days; p < 0.001).

CONCLUSION

HRV-guided HIFT produced similar improvements in cardiovascular function, body composition, and fitness as predetermined HIFT, despite fewer days at high intensity. HRV shows promise for prescribing individualized exercise intensity during HIFT.

What Is behind Changes in Resting Heart Rate and Heart Rate Variability? A Large-Scale Analysis of Longitudinal Measurements Acquired in Free-Living

The aim of this study was to investigate the relationship between heart rate and heart rate variability (HRV) with respect to individual characteristics and acute stressors. In particular, the relationship between heart rate, HRV, age, sex, body mass index (BMI), and physical activity level was analyzed cross-sectionally in a large sample of 28,175 individuals. Additionally, the change in heart rate and HRV in response to common acute stressors such as training of different intensities, alcohol intake, the menstrual cycle, and sickness was analyzed longitudinally. Acute stressors were analyzed over a period of 5 years for a total of 9 million measurements (320±374 measurements per person). HRV at the population level reduced with age (p < 0.05, r = -0.35, effect size = moderate) and was weakly associated with physical activity level (p < 0.05, r = 0.21, effect size = small) and not associated with sex (p = 0.35, d = 0.02, effect size = negligible). Heart rate was moderately associated with physical activity level (p < 0.05, r = 0.30, effect size = moderate) and sex (p < 0.05, d = 0.63, effect size = moderate) but not with age (p = 0.35, r = -0.01). Similar relationships between BMI, resting heart rate (p < 0.05, r = 0.19, effect size = small), and HRV (p < 0.05, r = -0.10, effect size = small) are shown. In response to acute stressors, we report a 4.6% change in HRV (p < 0.05, d = 0.36, effect size = small) and a 1.3% change in heart rate (p < 0.05, d = 0.38, effect size = small) in response to training, a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and a 12% reduction in HRV (p < 0.05, d = 0.55, effect size = moderate) after high alcohol intake, a 1.6% change in heart rate (p < 0.05, d = 1.41, effect size = large) and a 3.2% change in HRV (p < 0.05, d = 0.80, effect size = large) between the follicular and luteal phases of the menstrual cycle, and a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and 10% reduction in HRV (p < 0.05, d = 0.47, effect size = moderate) during sickness. Acute stressors analysis revealed how HRV is a more sensitive but not specific marker of stress. In conclusion, a short resting heart rate and HRV measurement upon waking using a smartphone app can effectively be used in free-living to quantify individual stress responses across a large range of individuals and stressors.

Current and Potential Applications of Wearables in Sports Cardiology

Purpose of the review

Commercial wearable biosensors are commonly used among athletes and highly active individuals, although their value in sports cardiology is not well established. In this review, we discuss the evidence for the current applications of wearables and provide our outlook for promising future directions of this emerging field.

Recent findings

The integration of routine assessment of physiological parameters, activity data, and features such as electrocardiogram recording has generated excitement over a role for wearables to help diagnose and monitor cardiovascular disease. Presently, however, there are significant challenges limiting their routine clinical use. While studies suggest that wearable-derived data may help guide training, evidence for the use of wearables in guiding exercise regimens for individuals with cardiovascular disease is lacking. Further, there is a paucity of data to demonstrate its efficacy in detecting exercise-related arrhythmias or conditions associated with sudden cardiac death. Further technological developments may lead to a greater potential for wearables to aid in sports cardiology practice.

Summary

The ability to collect vast amounts of physiological information can help athletes personalize training regimens. However, interpretation of these data and separating the signal from the noise are paramount, especially when used in a clinical setting. While there are currently no standardized approaches for the use of wearable-derived data in sports cardiology, we outline three domains in which they could guide the care of athletes in the future: (1) optimizing athletic performance (2) guiding exercise in athletes with known cardiovascular disease, and (3) screening for cardiovascular disease.

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.

Influence of a 100-mile ultramarathon on heart rate and heart rate variability

Aims

This study aimed to investigate the impact of an ultramarathon (UM) with a distance of 100 miles on heart rate (HR) and heart rate variability (HRV).

Methods

28 runners (25 men and 3 women) underwent 24-hour Holter ECG monitoring 1 week before the UM, immediately after the UM and after a week of recovery. The influence of age, body mass index (BMI), HR and HRV on the run time and recovery was investigated.

Results

A rise in the baseline HR (18.98%) immediately after the run accompanied by a significant drop in the SD of all normal RR intervals (7.12%) 1 week after. Except for the runners' age, BMI, HR and HRV showed no influence on the competition time. Full return of HRV to the athletes' baseline did not occur within 1 week. There were no significant differences between finishers and non-finishers in the analysed parameters.

Conclusion

The present results show that a 100-mile run leads to an increase in sympathetic activity and thus to an increase in HR and a decrease in HRV. Also, HRV might be a suitable parameter to evaluate the state of recovery after a 100-mile run but does not help to quantify the status of recovery, as the damage to the tendomuscular system primarily characterises this after completing a UM.

Effect of four different forms of high intensity training on BDNF response to Wingate and Graded Exercise Test

This study examined the effects of a nine-week intervention of four different high-intensity training modalities [high-intensity functional training (HIFT), high-intensity interval training (HIIT), high-intensity power training (HIPT), and high-intensity endurance training (HIET)] on the resting concentration of brain-derived neurotropic factor (BDNF). In addition, we evaluated the BDNF responses to Graded Exercise Test (GXT) and Wingate Anaerobic Test (WAnT) in men. Thirty-five healthy individuals with body mass index 25.55 ± 2.35 kg/m2 voluntarily participated in this study and were randomly assigned into four training groups. During nine-weeks they completed three exercise sessions per week for one-hour. BDNF was analyzed before and after a GXT and WAnT in two stages: (stage 0-before training and stage 9-after nine weeks of training). At stage 0, an increase in BDNF concentration was observed in HIFT (33%; p < 0.05), HIPT (36%; p < 0.05) and HIIT (38%; p < 0.05) after GXT. Even though HIET showed an increase in BDNF (10%) this was not statistically significant (p > 0.05). At stage 9, higher BDNF levels after GXT were seen only for the HIFT (30%; p < 0.05) and HIIT (18%; p < 0.05) groups. Reduction in BDNF levels were noted after the WAnT in stage 0 for HIFT (- 47%; p < 0.01), HIPT (- 49%; p < 0.001), HIET (- 18%; p < 0.05)], with no changes in the HIIT group (- 2%). At stage 9, BDNF was also reduced after WAnT, although these changes were lower compared to stage 0. The reduced level of BDNF was noted in the HIFT (- 28%; p < 0.05), and HIPT (- 19%;p < 0.05) groups. Additionally, all groups saw an improvement in VO2max (8%; p < 0.001), while BDNF was also correlated with lactate and minute ventilation and selected WAnT parameters. Our research has shown that resting values of BDNF after nine weeks of different forms of high-intensity training (HIT) have not changed or were reduced. Resting BDNF measured at 3th (before GXT at stage 9) and 6th day after long lasting HITs (before WAnT at stage 9) did not differed (before GXT), but in comparison to the resting value before WAnT at the baseline state, was lower in three groups. It appears that BDNF levels after one bout of exercise is depended on duration time, intensity and type of test/exercise.

Superior Adaptations in Adolescent Runners Using Heart Rate Variability (HRV)-Guided Training at Altitude

We evaluated the efficacy of heart rate variability (HRV)-guided training in adolescent athletes during a 2-week, high altitude (≈1900 m) training camp. Sixteen middle- and long-distance runners (4 female/12 male, 16.9 ± 1.0 years, 65.44 ± 4.03 mL·kg-1·min-1) were divided into 2 matched groups, both of which received the same training plan, but one of which acquired postwaking HRV values that were used to tailor the training prescription. During the camp, seven athletes in the HRV-guided group combined for a total of 32 training adjustments, whereas there were only 3 runners combined for 14 total training adjustments in the control group. A significant group by time interaction (p < 0.001) for VO2max was driven by VO2max improvements in the HRV group (+2.8 mL·kg-1·min-1, +4.27%; pBonf = 0.002) that were not observed in the control condition (+0.8 mL·kg-1·min-1, +1.26%; pBonf = 0.643). After returning from the camp, all athletes in the HRV group set a personal best, and six out of eight achieved their best positions in the National Championship, whereas only 75% of athletes in the control group set a personal best and five out of eight achieved their best positions in the National Championship. These data provide evidence in support of HRV-guided training as a way to optimize training prescriptions in adolescent athletes.

Monitoring Training and Recovery during a Period of Increased Intensity or Volume in Recreational Endurance Athletes

The purpose of the study was to examine the effects of progressively increased training intensity or volume on the nocturnal heart rate (HR) and heart rate variability (HRV), countermovement jump, perceived recovery, and heart rate-running speed index (HR-RS index). Another aim was to analyze how observed patterns during the training period in these monitoring variables were associated with the changes in endurance performance. Thirty recreationally trained participants performed a 10-week control period of regular training and a 10-week training period of either increased training intensity (INT, n = 13) or volume (VOL, n = 17). Changes in endurance performance were assessed by an incremental treadmill test. Both groups improved their maximal speed on the treadmill (INT 3.4 ± 3.2%, p < 0.001; VOL 2.1 ± 1.8%, p = 0.006). In the monitoring variables, only between-group difference (p = 0.013) was found in nocturnal HR, which decreased in INT (p = 0.016). In addition, perceived recovery decreased in VOL (p = 0.021) and tended to decrease in INT (p = 0.056). When all participants were divided into low-responders and responders in maximal running performance, the increase in the HR-RS index at the end of the training period was greater in responders (p = 0.005). In conclusion, current training periods of increased intensity or volume improved endurance performance to a similar extent. Countermovement jump and HRV remained unaffected, despite a slight decrease in perceived recovery. Long-term monitoring of the HR-RS index may help to predict positive adaptations, while interpretation of other recovery-related markers may need a more individualized approach.

Monitoring the Heart Rate Variability Responses to Training Loads in Competitive Swimmers Using a Smartphone Application and the Banister Impulse-Response Model

PURPOSE

First, to examine whether heart rate variability (HRV) responses can be modeled effectively via the Banister impulse-response model when the session rating of perceived exertion (sRPE) alone, and in combination with subjective well-being measures, are utilized. Second, to describe seasonal HRV responses and their associations with changes in critical speed (CS) in competitive swimmers.

METHODS

A total of 10 highly trained swimmers collected daily 1-minute HRV recordings, sRPE training load, and subjective well-being scores via a novel smartphone application for 15 weeks. The impulse-response model was used to describe chronic root mean square of the successive differences (rMSSD) responses to training, with sRPE and subjective well-being measures used as systems inputs. Changes in CS were obtained from a 3-minute all-out test completed in weeks 1 and 14.

RESULTS

The level of agreement between predicted and actual HRV data was R2 = .66 (.25) when sRPE alone was used. Model fits improved in the range of 4% to 21% when different subjective well-being measures were combined with sRPE, representing trivial-to-moderate improvements. There were no significant differences in weekly group averages of log-transformed (Ln) rMSSD (P = .34) or HRV coefficient of variation of Ln rMSSD (P = .12); however, small-to-large changes (d = 0.21-1.46) were observed in these parameters throughout the season. Large correlations were observed between seasonal changes in HRV measures and CS (changes in averages of Ln rMSSD: r = .51, P = .13; changes in coefficient of variation of Ln rMSSD: r = -.68, P = .03).

CONCLUSION

The impulse-response model and data collected via a novel smartphone application can be used to model HRV responses to swimming training and nontraining-related stressors. Large relationships between seasonal changes in measured HRV parameters and CS provide further evidence for incorporating a HRV-guided training approach.

Heart Rate Variability and Physical Demands of In-Season Youth Elite Soccer Players

Monitoring fatigue and performance is important for adjusting training loads in soccer. Therefore, knowing the status of the player when applying a training stimulus is key to optimizing the players' development. This study aims to evaluate the interaction between internal and external load, during training and matches, in an elite youth soccer team.

METHODS

seventeen youth players of the highest Spanish category were monitored with GPS devices during training and matches, as well as recording their nocturnal heart rate variability (HRV). We employed a linear mixed model to assess the physical demands between training and matches, and to compare the HRV variables.

RESULTS

a higher total distance (+2993.35-5746.56 m; ES = 1.4), distance at high intensity (+641.24-1907 m; ES = 1.5), sprint distance (+350.46-795.05 m; ES = 2.1), number of sprints (+18.38-41.58; ES = 1.9), and number of repeated sprints (+5.91-15.30; ES = 1.7) (all p < 0.001), but not in the number of accelerations, were reported during the matches when compared to the training sessions during the 11 weeks. The analysis of the HRV variables showed no significant differences between the accumulated values during a training week, providing similar results pre-match or post-match (p > 0.05). The LF/HF_RATIO showed a negative influence on the total distance ran, distance at high intensity, distance in sprint, number of sprints, and repeated sprint. RR_MEAN was positively related to the sprint number.

CONCLUSION

the results of the present study suggest that nocturnal HRV variables are not different between pre-match and post-match. Furthermore, it suggests that LF/HF_RATIO and RR_MEAN during pre-match can determine the external load that the player will be able to complete during the match.

Heart Rate Variability Changes From Traditional vs. Ultra-Short-Term Recordings in Relation to Preseason Training Load and Performance in Futsal Players

Nakamura, FY, Antunes, P, Nunes, C, Costa, JA, Esco, MR, and Travassos, B. Heart rate variability changes from traditional vs. ultra-short-term recordings in relation to preseason training load and performance in futsal players. J Strength Cond Res 34(10): 2974-2981, 2020-The aims of this study were to analyze heart rate variability (HRV) changes in futsal players during preseason training using both "criterion" (10-minute) and ultra-shortened (2-minute) measures, and to determine whether they were related to changes in the Yo-Yo Intermittent Recovery Test, level 1 (Yo-Yo IR1) performance and accumulated training load (TL). Eleven male competitive futsal players (age = 25.19 ± 4.70 years; body mass = 73.15 ± 11.70 kg; and height = 176.90 ± 5.01 cm) volunteered for the study. Data collection took place during the first to the fourth weeks of preseason training. Training load was monitored with session ratings of perceived exertion. The total distance (TD) covered during the Yo-Yo IR1 was recorded during week 1 and week 4. Heart rate variability was measured through the log-transformed root mean square of successive normal-to-normal interval differences using the ultra-short analysis, with its weekly mean (lnRMSSDM) and coefficient of variation (lnRMSSDCV) recorded, and by means of the criterion method (weeks 1 and 4). lnRMSSDM was likely higher at week 4 compared with week 1 using both criterion and ultra-short recordings. Moderate-to-large correlations were found between changes in the lnRMSSDM and lnRMSSDCV values and changes in TL and TD (r values ranged from -0.48 to 0.65). Changes in ultra-short HRV measures (i.e., increase in lnRMSSDM and decrease in lnRMSSDCV) during futsal preseason were associated with increased performance. The players who accumulated higher perceived TLs displayed smaller improvements in the Yo-Yo IR1 performance and HRV.

Heart Rate Variability in Women with Systemic Lupus Erythematosus: Association with Health-Related Parameters and Effects of Aerobic Exercise

Abnormal heart rate variability (HRV) has been observed in patients with systemic lupus erythematosus (SLE). In a combined cross-sectional and interventional study approach, we investigated the association of HRV with inflammation and oxidative stress markers, patient-reported outcomes, and the effect of 12 weeks of aerobic exercise in HRV. Fifty-five women with SLE (mean age 43.5 ± 14.0 years) were assigned to either aerobic exercise (n = 26) or usual care (n = 29) in a non-randomized trial. HRV was assessed using a heart rate monitor during 10 min, inflammatory and oxidative stress markers were obtained, psychological stress (Perceived Stress Scale), sleep quality (Pittsburg Sleep Quality Index), fatigue (Multidimensional Fatigue Inventory), depressive symptoms (Beck Depression Inventory), and quality of life (36-item Short-Form Health Survey) were also assessed. Low frequency to high frequency power (LFHF) ratio was associated with physical fatigue (p = 0.019). Sample entropy was inversely associated with high-sensitivity C-reactive protein (p = 0.014) and myeloperoxidase (p = 0.007). There were no significant between-group differences in the changes in HRV derived parameters after the exercise intervention. High-sensitivity C-reactive protein and myeloperoxidase were negatively related to sample entropy and physical fatigue was positively related to LFHF ratio. However, an exercise intervention of 12 weeks of aerobic training did not produce any changes in HRV derived parameters in women with SLE in comparison to a control group.

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.

Acute Physiological Responses to Four Running Sessions Performed at Different Intensity Zones

This study investigated acute responses and post 24-h recovery to four running sessions performed at different intensity zones by supine heart rate variability, countermovement jump, and a submaximal running test. A total of 24 recreationally endurance-trained male subjects performed 90 min low-intensity (LIT), 30 min moderate-intensity (MOD), 6×3 min high-intensity interval (HIIT) and 10×30 s supramaximal-intensity interval (SMIT) exercises on a treadmill. Heart rate variability decreased acutely after all sessions, and the decrease was greater after MOD compared to LIT and SMIT (p<0.001; p<0.01) and HIIT compared to LIT (p<0.01). Countermovement jump decreased only after LIT (p<0.01) and SMIT (p<0.001), and the relative changes were different compared to MOD (p<0.01) and HIIT (p<0.001). Countermovement jump remained decreased at 24 h after SMIT (p<0.05). Heart rate during the submaximal running test rebounded below the baseline 24 h after all sessions (p<0.05), while the rating of perceived exertion during the running test remained elevated after HIIT (p<0.05) and SMIT (p<0.01). The current results highlight differences in the physiological demands of the running sessions, and distinct recovery patterns of the measured aspects of performance. Based on these results, assessments of performance and recovery from multiple perspectives may provide valuable information for endurance athletes, and help to improve the quality of training monitoring.

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.

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.

Cardiopulmonary exercise testing and echocardiographic exam: an useful interaction

Cardiopulmonary exercise test (CPET) is a functional assessment that helps to detect disorders affecting the system involved in oxygen transport and utilization through the analysis of the gas exchange during exercise. The clinical application of CPET is various, it including training prescription, evaluation of treatment efficacy and outcome prediction in a broad spectrum of conditions. Furthermore, in patients with shortness of breath it provides pivotal information to bring out an accurate differential diagnosis between physical deconditioning, cardiopulmonary disease and muscular diseases. Modern software allows the breath-by-breath analysis of the volume of oxygen intake (VO₂), volume of carbon dioxide output (VCO₂) and expired air (VE). Through this analysis, CPET provides a series of additional parameters (peak VO₂, ventilatory threshold, VE/VCO₂ slope, end-tidal carbon dioxide exhaled) that characterize different patterns, helping in diagnosis process. Limitations to the routine use of CPET are mainly represented from the lack of measurement standardization and limited data from randomized multicentric studies. The integration of CPET with exercise stress echocardiography has been recently introduced in the clinical practice by integrating the diagnostic power offered by both the tools. This combined approach has been demonstrated to be valuable for diagnosing several cardiac diseases, including heart failure with preserved or reduced ejection fraction, cardiomyopathies, pulmonary arterial hypertension, valvular heart disease and coronary artery disease. Future investigations are needed to further promote this intriguing combination in the clinical and research setting.

Nutritional strategies in an elite wheelchair marathoner at 3900 m altitude: a case report

BACKGROUND

Altitude training is a common practice among middle-distance and marathon runners. During acclimatization, sympathetic drive may increase resting metabolic rate (RMR), therefore implementation of targeted nutritional interventions based on training demands and environmental conditions becomes paramount. This single case study represents the first nutritional intervention performed under hypobaric hypoxic conditions (3900 m) in Paralympic sport. These results may elucidate the unique nutritional requirements of upper body endurance athletes training at altitude.

CASE PRESENTATION

This case study examined the effects of a nutritional intervention on the body mass of a 36-year-old professional wheelchair athlete (silver medalist at the Paralympic Games and 106 victories in assorted road events) during a five-week altitude training camp, divided into pre-altitude at sea level (B_N), acclimatization to altitude (Puno, 3860 m) (B_H), specific training (W_1,2,3,4) and return to sea level (Post) phases. Energy intake (kcal) and body mass (kg) were recorded daily. Results demonstrated significant decrease in body mass between B_N and B_H (52.6 ± 0.4 vs 50.7 ± 0.5 kg, P < 0.001) which returned to pre-altitude values, upon returning to sea level at Post (52.1 ± 0.5 kg). A greater daily intake was observed during B_H (2899 ± 670 kcal) and W_1,2,3 (3037 ± 490; 3116 ± 170; 3101 ± 385 kcal) compared to B_N (2397 ± 242 kcal, P < 0.01) and Post (2411 ± 137 kcal, P < 0.01). No differences were reported between W₄ (2786 ± 375 kcal), B_N and Post. The amount of carbohydrates ingested (g · kg^- 1) was greater in W_1,2,3, (9.6 ± 2.1; 9.9 ± 1.2; 9.6 ± 1.2) than in B_N (7.1 ± 1.2) and Post (6.3 ± 0.8, P < 0.001). Effect sizes (Cohen's d) for all variables relative to B_N (all time points) exceed a large effect (d > 0.80).

CONCLUSIONS

These results suggest an elite wheelchair marathoner training at 3860 m required increased nutrient requirements as well as the systematic control needed to re-adapt a nutritional program. Moreover, our findings highlight training and nutritional prescription optimization of elite wheelchair athletes, under challenging environmental conditions.

Dose-Response Matters! - A Perspective on the Exercise Prescription in Exercise-Cognition Research

In general, it is well recognized that both acute physical exercises and regular physical training influence brain plasticity and cognitive functions positively. However, growing evidence shows that the same physical exercises induce very heterogeneous outcomes across individuals. In an attempt to better understand this interindividual heterogeneity in response to acute and regular physical exercising, most research, so far, has focused on non-modifiable factors such as sex and different genotypes, while relatively little attention has been paid to exercise prescription as a modifiable factor. With an adapted exercise prescription, dosage can be made comparable across individuals, a procedure that is necessary to better understand the dose-response relationship in exercise-cognition research. This improved understanding of dose-response relationships could help to design more efficient physical training approaches against, for instance, cognitive decline.

Effects of inspiratory muscle-training intensity on cardiovascular control in amateur cyclists

Chronic effects of inspiratory muscle training (IMT) on autonomic function and baroreflex regulation are poorly studied. This study aims at evaluating chronic effects of different IMT intensities on cardiovascular control in amateur cyclists. A longitudinal, randomized, controlled blind study was performed on 30 recreational male cyclists undergoing IMT for 11 wk. Participants were randomly allocated into sham-trained group (SHAM, n = 9), trained group at 60% of the maximal inspiratory pressure (MIP60, n = 10), and trained group at critical inspiratory pressure (CIP, n = 11). Electrocardiogram, finger arterial pressure, and respiratory movements were recorded before (PRE) and after (POST) training at rest in supine position (REST) and during active standing (STAND). From the beat-to-beat series of heart period (HP) and systolic arterial pressure (SAP), we computed time domain markers, frequency domain indexes in the low frequency (0.04-0.15 Hz) and high frequency (HF, 0.15-0.4 Hz) bands, an entropy-based complexity index (CI), and baroreflex markers estimated from spontaneous HP-SAP sequences. Compared with SHAM, the positive effect of MIP60 over the HP series led to the HF power increase during REST (PRE: 521.2 ± 447.5 ms²; POST: 1,161 ± 878.9 ms²) and the CI rise during STAND (PRE: 0.82 ± 0.18; POST: 0.97 ± 0.13). Conversely, the negative effect of CIP took the form of the decreased HP mean during STAND (PRE: 791 ± 71 ms; POST: 737 ± 95 ms). No effect of IMT was visible over SAP and baroreflex markers. These findings suggest that moderate-intensity IMT might be beneficial when the goal is to limit cardiac sympathetic hyperactivity at REST and/or in response to STAND.

Point-of-care technologies in heart, lung, blood and sleep disorders from the Center for Advancing Point-of-Care Technologies

Recent advancements in point-of-care technologies have transformed care for patients with heart, lung, blood, and sleep disorders by providing rapid, cost-effective, and accessible solutions to challenges in the detection and management of many health conditions. However, major barriers exist throughout the technology development process that inhibit the actualization of many promising and potentially successful ideas. The Center for Advancing Point of Care Technologies has established a system for supporting further innovation in this field and bridging the gap between initial idea conception and implementation. We highlight current and emerging point-of-care technologies throughout the development spectrum and emphasize the need for a needs-driven model of health technology development that involve appropriate stakeholders in the process.

Endurance Running Training Individually Guided by HRV in Untrained Women

da Silva, DF, Ferraro, ZM, Adamo, KB, and Machado, FA. Endurance running training individually guided by HRV in untrained women. J Strength Cond Res 33(3): 736-746, 2019-The aim of this study was to analyze the effects of heart rate variability (HRV)-guided training compared with a standardized prescription on (a) time to complete 5-km running performance (t5km), (b) peak treadmill running speed (Vpeak) and its time limit (tlim at Vpeak), and (c) autonomic cardiac modulation (i.e., parasympathetic activity and recovery) in untrained women. Additionally, we correlated changes in t5km with changes in Vpeak, tlim at Vpeak and autonomic cardiac modulation. Thirty-six untrained women were divided into a HRV-guided training group (HRVG) and a control group (CG). The CG followed a predefined program, alternating moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT). The determination of MICT or HIIT was based on the pretraining HRV for HRVG. MICT was performed if HRV was <mean - 1 SD of previous measures. Otherwise, HIIT was prescribed. The t5km, Vpeak, tlim at Vpeak, parasympathetic activity (i.e., rMSSD) and parasympathetic reactivation (i.e., HRR) were measured before and after the training period. The t5km decreased to a greater magnitude in the HRVG (-17.5 ± 5.6% vs. -14 ± 4.7%; Effect Size (ES) between-group difference = moderate). rMSSD and tlim at Vpeak only improved in HRVG (+23.3 ± 27.8% and +23.6 ± 31.9%, respectively). The HRVG experienced greater improvements in Vpeak and HRR (Vpeak: 10 ± 7.3% vs. 8.2 ± 4.7%; HRR: 19.1 ± 28.1% vs. 12.6 ± 12.9%; ES between-group difference = small). Although HRVG performed less MICT than CG, the volume of MICT was negatively related to changes in t5km. Vpeak changes were highly correlated with t5km changes. The greater improvements in HRVG for t5km and autonomic modulation reinforce the potential application of this tool.

Influence of Training Models at 3,900-m Altitude on the Physiological Response and Performance of a Professional Wheelchair Athlete: A Case Study

Sanz-Quinto, S, López-Grueso, R, Brizuela, G, Flatt, AA, and Moya-Ramón, M. Influence of training models at 3,900-m altitude on the physiological response and performance of a professional wheelchair athlete: A case study. J Strength Cond Res 33(6): 1715-1723, 2019-This case study compared the effects of two training camps using flexible planning (FP) vs. inflexible planning (IP) at 3,860-m altitude on physiological and performance responses of an elite marathon wheelchair athlete with Charcot-Marie-Tooth disease (CMT). During IP, the athlete completed preplanned training sessions. During FP, training was adjusted based on vagally mediated heart rate variability (HRV) with specific sessions being performed when a reference HRV value was attained. The camp phases were baseline in normoxia (BN), baseline in hypoxia (BH), specific training weeks 1-4 (W1, W2, W3, W4), and Post-camp (Post). Outcome measures included the root mean square of successive R-R interval differences (rMSSD), resting heart rate (HRrest), oxygen saturation (SO2), diastolic blood pressure and systolic blood pressure, power output and a 3,000-m test. A greater impairment of normalized rMSSD (BN) was shown in IP during BH (57.30 ± 2.38% vs. 72.94 ± 11.59%, p = 0.004), W2 (63.99 ± 10.32% vs. 81.65 ± 8.87%, p = 0.005), and W4 (46.11 ± 8.61% vs. 59.35 ± 6.81%, p = 0.008). At Post, only in FP was rMSSD restored (104.47 ± 35.80%). Relative changes were shown in power output (+3 W in IP vs. +6 W in FP) and 3,000-m test (-7s in IP vs. -16s in FP). This case study demonstrated that FP resulted in less suppression and faster restoration of rMSSD and more positive changes in performance than IP in an elite wheelchair marathoner with CMT.

Heart rate variability mediates motivation and fatigue throughout a high-intensity exercise program

High-intensity exercise interventions are often promoted as a time-efficient public health intervention to combat chronic disease. However, increased physical effort and subsequent fatigue can be barriers to long-term maintenance of high-intensity exercise programs. The purpose of the present study was to determine if heart rate variability (HRV) mediated state traits related to exercise program adherence. Fifty-five healthy men and women (ages 19-35 years) used a commercially available smartphone application to monitor daily HRV status throughout a 6-week high-intensity exercise intervention. Participants reported state motivation to exercise and global physical fatigue immediately prior to each exercise session. Temporary shifts toward increased parasympathetic reactivation (p = 0.030) resulted in significant increases in daily fatigue (p < 0.001) and decreases in motivation to exercise (p = 0.028). Through modulation of exercise volume, in response to these temporary shifts in HRV, these effects were reversed (p < 0.001) via increased parasympathetic withdrawal (p = 0.018). For the first time, these data demonstrate a mediating effect of HRV on adherence-related trait states throughout a high-intensity exercise program. Applied strategies, such as appropriately timed exercise volume moderation, may be able to leverage this effect and help facilitate long-term exercise program maintenance. Novelty These data establish a link between expected shifts in HRV throughout high-intensity exercise programs with motivation to participate and physical fatigue. Modulation of training volume, in response to these shifts, can optimize adherence-related behavioral responses during high-exercise programs.