Heart Rate Variability in Professional and Semiprofessional Soccer: A Scoping Review

In modern soccer, fitness and fatigue monitoring tools tend to be focused on noninvasive, time-efficient and player-friendly measures. Heart rate variability (HRV) has been suggested as an effective method for monitoring training response and readiness to perform. However, there is still a lack of consensus on HRV monitoring when it comes to soccer. Thus, this scoping review aims to map existing evidence on HRV in professional and semiprofessional soccer settings, and to identify knowledge gaps to inform future research directions. A search of databases (PubMed, Scopus, Web of Science, Google Scholar) according to the PRISMA-ScR statement was employed. Studies were screened for eligibility on inclusion criteria: (1) HRV was among the topics discussed in the article; (2) adult professional or semiprofessional soccer players were involved in the study; (3) both male and female participants; (4) no geographical area exclusion; (5) articles published in English; and (6) article full text available. The search of the selected databases revealed 8456 records. The titles and abstracts of all articles were retrieved for screening of eligibility, leaving 30 articles for further consideration. Following screening against set criteria, a total of 25 studies were included in this review, the sample size of which ranged from 6 to 124 participants. The participants in the included studies were professional and semiprofessional soccer players, interviewed clubs staff, and practitioners. Along with other monitoring strategies, morning vagally mediated HRV analysis via (ultra)short-term orthostatic measurements may be an efficient way to assess training adaptations and readiness to perform in professional and semiprofessional soccer players. Further research is required to make definitive recommendations.

Reliability of recovery heart rate variability measurements as part of the Lamberts Submaximal Cycle Test and the relationship with training status in trained to elite cyclists

PURPOSE

To determine if post-exercise heart rate variability, in the form of logged transformed root mean square of successive differences of the R-R intervals (LnRMSSD) can be measured reliably during the recovery from a submaximal cycle test and what the relationship of LnRMSSD is with training status of the cyclists.

METHODS

Fourteen male cyclists participated in the reliability part for the study, which included performing six Lamberts Submaximal Cycle Test (LSCT), during which recovery LnRMSSD was measured over 30 s (LnRMSSD30 s), 60 s LnRMSSD60 s)and 90 s LnRMSSD90 s). In addition, fifty male and twenty female cyclists completed a peak power output (PPO) test (including VO2peak) and 40 km time trial (40 km TT) before which they performed the LSCT as a standardized warm-up. Relationships between the LnRMSSD and PPO, VO2peak and 40 km TT time were studied.

RESULTS

Due to the design of the LSCT, submaximal heart and breathing rate were similar at the end of stage 3 of the LSCT, as well as during the recovery periods. The highest reliability was found in LnRMSSD60 s (ICC: 0.97) with a typical error of the measurement (TEM: 5.8%). In line with this the strongest correlations were found between LnRMSSD60 s and PPO (r = 0.93[male]; 0.85[female]), VO2peak (r = 0.71[male]; 0.63[female];) and 40 km TT (r = - 0.83[male]; - 0.63[female]).

CONCLUSIONS

LnRMSSD60 s can be measured reliably after the LSCT and can predict PPO, VO2peak and 40 km TT performance well in trained-to-elite cyclists. These findings suggest that recovery LnRMSSD can potentially play an important role in monitoring and fine-tuning training prescriptions in trained-to-elite cyclists.

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.

Classification of exercise fatigue levels by multi-class SVM from ECG and HRV

Among the various physiological signals, electrocardiogram (ECG) is a valid criterion for the classification of various exercise fatigue. In this study, we combine features extracted by deep neural networks with linear features from ECG and heart rate variability (HRV) for exercise fatigue classification. First, the ECG signals are converted into 2-D images by using the short-term Fourier transform (STFT), and image features are extracted by the visual geometry group (VGG) . The extracted image and linear features of ECG and HRV are sent to the different types of classifiers to distinguish distinct exercise fatigue level. To validate performance, the proposed methods are tested on (i) an open-source EPHNOGRAM dataset and (ii) a self-collected dataset (n = 51). The results reveal that the classification based on the concatenated features has the highest accuracy, and the calculation time of the system is also significantly reduced. This demonstrates that the proposed novel hybrid approach can be used to assist in improving the accuracy and timeliness of exercise fatigue classification in a real-time exercise environment. The experimental results show that the proposed method outperforms other recent state-of-the-art methods in terms of accuracy 96.90%, sensitivity 96.90%, F1-score of 0.9687 in EPHNOGRAM and accuracy 92.17%, sensitivity 92.63%, F1-score of 0.9213 in self-collected dataset.

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.

High-intensity exercise prescription guided by heart rate variability in breast cancer patients: a study protocol for a randomized controlled trial

BACKGROUND

Breast cancer is a chronic disease with a large growth in its treatments, prognosis, improvements, side effects and rehabilitation therapies research. These advances have also highlighted the need to use physical exercise as a countermeasure to reduce the cardiotoxicity of pharmacological treatments, increase patients' strength and quality of life and improve body composition, physical condition and mental health. However, new investigations show the need for a closed exercise individualisation to produce higher physiological, physical and psychological benefits in remote exercise programs. To this end, the present study will use, in a novel way in this population, heart rate variability (HRV) as a measure for prescribing high-intensity training. Thus, the primary objective of this randomised clinical trial is to analyse the effects of a high-intensity exercise program daily guided by HRV, a preplanned moderate to high-intensity exercise intervention and a usual care group, in breast cancer patients after chemotherapy and radiotherapy treatments.

METHODS

For this purpose, a 16-week intervention will be carried out with 90 breast cancer patients distributed in 3 groups (a control group, a moderate to high-intensity preplanned exercise group and a high-intensity exercise group guided by HRV). Both physical exercise interventions will be developed remotely and supervised including strength and cardiovascular exercises. Physiological variables, such as cardiotoxicity, biomarkers, lipid profile, glucose, heart rate and blood pressure; physical measures like cardiorespiratory capacity, strength, flexibility, agility, balance and body composition; and psychosocial variables, as health-related quality of life, fatigue, functionality, self-esteem, movement fear, physical exercise level, anxiety and depression will be measure before, after the intervention and 3 and 6 months follow up.

DISCUSSION

Personalized high-intensity exercise could be a promising exercise intervention in contrast to moderate-intensity or usual care in breast cancer patients to reach higher clinical, physical and mental effects. In addition, the novelty of controlling HRV measures daily may reflect exercise effects and patients' adaptation in the preplanned exercise group and a new opportunity to adjust intensity. Moreover, findings may support the effectiveness and security of physical exercise remotely supervised, although with high-intensity exercise, to reach cardiotoxicity improvements and increase physical and psychosocial variables after breast cancer treatments. Trial registration ClinicalTrials.gov nº NCT05040867 ( https://clinicaltrials.gov/ct2/show/record/NCT05040867 ).

Training Periodization, Intensity Distribution, and Volume in Trained Cyclists: A Systematic Review

A well-planned periodized approach endeavors to allow road cyclists to achieve peak performance when their most important competitions are held.

PURPOSE

To identify the main characteristics of periodization models and physiological parameters of trained road cyclists as described by discernable training intensity distribution (TID), volume, and periodization models.

METHODS

The electronic databases Scopus, PubMed, and Web of Science were searched using a comprehensive list of relevant terms. Studies that investigated the effect of the periodization of training in cyclists and described training load (volume, TID) and periodization details were included in the systematic review.

RESULTS

Seven studies met the inclusion criteria. Block periodization (characterized by employment of highly concentrated training workload phases) ranged between 1- and 8-week blocks of high-, medium-, or low-intensity training. Training volume ranged from 8.75 to 11.68 h·wk-1 and both pyramidal and polarized TID were used. Traditional periodization (characterized by a first period of high-volume/low-intensity training, before reducing volume and increasing the proportion of high-intensity training) was characterized by a cyclic progressive increase in training load, the training volume ranged from 7.5 to 10.76 h·wk-1, and pyramidal TID was used. Block periodization improved maximum oxygen uptake (VO2max), peak aerobic power, lactate, and ventilatory thresholds, while traditional periodization improved VO2max, peak aerobic power, and lactate thresholds. In addition, a day-by-day programming approach improved VO2max and ventilatory thresholds.

CONCLUSIONS

No evidence is currently available favoring a specific periodization model during 8 to 12 weeks in trained road cyclists. However, few studies have examined seasonal impact of different periodization models in a systematic way.

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.

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.

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 Monitoring during a Padel Match

Padel, an increasingly popular sport, presents some associated cardiovascular risks, which can be prevented by heart rate variability (HRV) monitoring. However, there is no study worldwide that characterizes HRV during padel games. Therefore, this study aims to monitor HRV responses and characterize them using linear and non-linear metrics at three timepoints: at baseline, during a game, and during recovery. Twenty-seven amateur participants had their HRV monitored before, during, and after a 90 min padel game. We extracted time, frequency, and non-linear measures with MATLAB for baseline, rest period, and at three periods of 5 min during the game. The differences in measures were assessed through an ANOVA. The autonomic modulation was affected by the padel match in amateur players. In this regard, the root mean square of successive differences between normal heartbeats (RMSsd), Poincaré plot (perpendicular standard deviation (SD1) and horizontal standard deviation (SD2)), sample entropy (SampEn), low frequencies (LF), and very low frequencies (VLF) were significantly reduced during the game, whereas alpha-2, high frequencies (HF), and the ratio between low and high frequencies (LF/HF) increased during the game. Furthermore, an abrupt change was found in the autonomic modulation between game and recovery assessments, which suggests the need to rethink the practices of cool-down protocols. The multiple timepoints analyzed during this study allow us to investigate the evolution of different HRV measures in the time, frequency, and non-linear domains, clarifying the interpretation of the variables, especially the less-investigated ones such as the non-linear measures.

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.

Heart rate variability before and after 14 weeks of training in Thoroughbred horses and Standardbred trotters with different training experience

Changes in heart rate and heart rate variabilty (HRV) were investigated in untrained (UT; starting their first racing season) and detrained (DT; with 1–3 years of race experience) racehorses before and after 14-week conventional training. HRV was measured at rest over 1 h between 9:00 and 10:00 AM on the usual rest day of the horses. The smallest worthwhile change (SWC) rate was calculated for all HRV parameters. UT horses had significantly higher heart rate compared to DT (P<0.001). There were no gender- or training-related differences in heart rate. The root-mean-square of successive differences (rMSSD) in the consecutive inter-beat-intervals obtained after the 14-week training period was lower compared to pre-training rMSSD (P<0.001). The rMSSD was not influenced by breed, age or gender. In DT horses, there was a significant decrease in the high frequency (HF) component of HRV (P≤0.05) as the result of the 14-week training. These results may reflect saturation of high-frequency oscillations of inter-beat intervals rather than the reduction in parasympathetic influence on the heart. The HF did not differ significantly between the two measurements in UT horses; however, 16.6% of the animals showed a decrease in HF below SWC (P≤0.05). This supports the likelihood of parasympathetic saturation. Although no significant decrease in heart rate was found for the post-training, 30.0% of DT and 58.3% of UT horses still showed a decrease in heart rate below the SWC. Also by individual examination, it was also visible that despite significant post-training decrease in rMSSD, 1 (4.6%) DT and 2 (6.7%) UT horses reached SWC increase in rMMSD. In the case of these horses, the possibility of maladaptation should be considered. The present results indicate that similar to as found in human athletes, cardiac ANS status of racehorses also changes during the physiological adaptation to training. To explore more precise links between HRV and training effectiveness in horses, a more frequent recording would be necessary. Detailed analysis of HRV parameters based on SWC will be able to highlight the importance of fitness evaluation at individual level.

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.

Can Exercise Reduce the Autonomic Dysfunction of Patients With Cancer and Its Survivors? A Systematic Review and Meta-Analysis

Background: Cancer therapies have increased patient survival rates, but side effects such as cardiotoxicity and neurotoxicity can lead to autonomic nervous and cardiovascular system dysfunction. This would result in a decrease in parasympathetic activity and the enhancement of sympathetic activity. Heart rate variability (HRV), which reflects autonomic modulation, is a valuable physiological tool since it correlates with cancer-related fatigue, stress, depression, and mortality in patients with cancer.

Objective: This study aimed to analyze the effects of exercise programs on the autonomic modulation, measured by the HRV of patients with cancer and its survivors.

Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the quality of the articles was assessed with the Physiotherapy Evidence Database (PEDro) scale. The meta-analysis statistic procedure was performed by using RevMan software version 5.3.

Results: From the 252 articles found, six studies were included in the review involving 272 participants aged 30–75 years. Exercise programs had a mean length of 10.4 ± 4.6 weeks, a frequency of 3 ± 1.4 days/week, and a mean duration of 78 ± 23.9 min. In time-domain HRV measures, exercise may increase in the SD of normal-to-normal intervals [p < 0.00001, with a mean difference (MD) of 12.79 ms from 9.03 to 16.55] and a decreased root mean square of successive R–R interval differences (p = 0.002, with an MD of 13.08 ms from 4.90 to 21.27) in comparison with control groups (CG). The frequency-domain data reveal that the exercise group (EG) improve significantly more than the CGs in low frequency [absolute power: p < 0.0001, with a standardized mean difference (SMD) of 0.97 from 0.61 to 1.34; relative power: p = 0.04, with an MD = −7.70 from −15.4 to −0.36], high-frequency [absolute power: p = 0.001, with a SMD of 1.49 from 0.32 to 2.66; relative power: p = 0.04, with an MD of 8.00 normalized units (n.u.) from 0.20 to 15.80], and low-to-high frequency ratio (p = 0.007 with an MD of −0.32 from −0.55 to −0.09).

Conclusion: Exercise programs could lead to positive effects on the autonomic modulation of patients with cancer and its survivors. More beneficial changes may occur with resistance and endurance workouts. However, due to the low number of interventions performed, further research is needed to substantiate the findings and to provide additional insights regarding the exercise intensity required to increase the autonomic modulation of the patient.

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.

Periodization and Block Periodization in Sports: Emphasis on Strength-Power Training-A Provocative and Challenging Narrative

ABSTRACT

Stone, MH, Hornsby, WG, Haff, GG, Fry, AC, Suarez, DG, Liu, J, Gonzalez-Rave, JM, and Pierce, KC. Periodization and block periodization in sports: emphasis on strength-power training-a provocative and challenging narrative. J Strength Cond Res 35(8): 2351-2371, 2021-Periodization can be defined as a logical sequential, phasic method of manipulating fitness and recovery phases to increase the potential for achieving specific performance goals while minimizing the potential for nonfunctional over-reaching, overtraining, and injury. Periodization deals with the micromanagement of timelines and fitness phases and is cyclic in nature. On the other hand, programming deals with the micromanagement of the training process and deals with exercise selection, volume, intensity, etc. Evidence indicates that a periodized training process coupled with appropriate programming can produce superior athletic enhancement compared with nonperiodized process. There are 2 models of periodization, traditional and block. Traditional can take different forms (i.e., reverse). Block periodization has 2 subtypes, single goal or factor (individual sports) and multiple goals or factors (team sports). Both models have strengths and weaknesses but can be "tailored" through creative programming to produce excellent results for specific sports.

Autonomic and Perceptual Responses to Induction of a Ketogenic Diet in Free-Living Endurance Athletes: A Randomized, Crossover Trial

PURPOSE

Considerable interindividual heterogeneity has been observed in endurance performance responses following induction of a ketogenic diet (KD). It is plausible that a physiological stress response in the period following the dramatic dietary shift associated with transition to a KD may explain this heterogeneity.

METHODS

In a randomized, crossover study design, 8 trained male runners completed an incremental exercise test and ran to exhaustion at 70%VO2max before and after a 31-day rigorously controlled habitual diet or KD intervention, and recorded heart rate variability (root mean square of the sum of successive differences in R-R intervals [rMSSD]) upon waking each morning along with the recovery-stress questionnaire for athletes each week. Data were analyzed using linear mixed models.

RESULTS

A significant reduction in rMSSD was observed in the KD (-9.77 [4.03] ms, P = .02), along with an increase in day-to-day variability in rMSSD (2.1% [1.0%], P = .03). The reduction in rMSSD in the KD for the subgroup of individuals exhibiting impaired exercise capacity following induction of the KD approached significance (Δ -22 [15] ms, P = .06, N = 4); whereas no effect was observed in those who exhibited unchanged exercise capacity (Δ 5 [18] ms, P = .61, N = 4). No main effects were observed for recovery-stress questionnaire for athletes.

CONCLUSIONS

Our data suggest those working with endurance athletes transitioning onto a KD may consider using noninvasive, inexpensive resting heart rate variability measures to gain individual-level insights into the likely short-term effects on exercise capacity.

Changes in the Trunk and Lower Extremity Kinematics Due to Fatigue Can Predispose to Chronic Injuries in Cycling

Kinematic analysis of the cycling position is a determining factor in injury prevention and optimal performance. Fatigue caused by high volume training can alter the kinematics of the lower body and spinal structures, thus increasing the risk of chronic injury. However, very few studies have established relationships between fatigue and postural change, being these in 2D analysis or incremental intensity protocols. Therefore, this study aimed to perform a 3D kinematic analysis of pedaling technique in a stable power fatigue protocol 23 amateur cyclists (28.3 ± 8.4 years) participated in this study. For this purpose, 3D kinematics in hip, knee, ankle, and lumbar joints, and thorax and pelvis were collected at three separate times during the protocol. Kinematic differences at the beginning, middle, and end of the protocol were analyzed for all joints using one-dimensional statistical parametric mapping. Significant differences (p < 0.05) were found in all the joints studied, but not all of them occur in the same planes or the same phase of the cycle. Some of the changes produced, such as greater lumbar and thoracic flexion, greater thoracic and pelvic tilt, or greater hip adduction, could lead to chronic knee and lumbar injuries. Therefore, bike fitting protocols should be carried out in fatigue situations to detect risk factor situations.

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.

Periodization: Variation in the Definition and Discrepancies in Study Design

Over the past several decades, periodization has been widely accepted as the gold standard of training theory. Within the literature, there are numerous definitions for periodization, which makes it difficult to study. When examining the proposed definitions and related studies on periodization, problems arise in the following domains: (1) periodization has been proposed to serve as the macro-management of the training process concerning the annual plan, yet research on long-term effects is scarce; (2) periodization and programming are being used interchangeably in research; and (3) training is not periodized alongside other stressors such as sport (i.e., only resistance training is being performed without the inclusion of sport). Overall, the state of the literature suggests that the inability to define periodization makes the statement of its superiority difficult to experimentally test. This paper discusses the proposed definitions of periodization and the study designs which have been employed to examine the concept.

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.

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.