The use of heart rate variability measures to assess autonomic control during exercise

Exercise-mediated modulation of autonomic nervous system and inflammatory response in sleep-deprived individuals: A narrative reviews of implications for cardiovascular health

Sleep deprivation is a growing concern in cardiovascular risk, causing physiological disruptions like autonomic dysregulation and inflammation. Recent research indicates that sleep deprivation increases sympathetic nervous activity while decreasing parasympathetic activity, leading to increased blood pressure, impaired endothelial function, and heightened inflammation. Exercise has emerged as a non-pharmacological approach to increase cardiovascular health. However, the impact of exercise on sleep deprivation-induced changes in autonomic activity and inflammation remains unclear. To explore this, we reviewed studies investigating the effects of acute exercise on autonomic regulation and inflammatory markers following sleep deprivation. We conducted a narrative review of the literature. PubMed/MEDLINE, Google Scholar, and Web of Science (WOS) searched the articles between May 2022 and April 2023. The papers had to: [1] focus on recent studies between 2000 and 2023; [2] consist of sleep deprivation participants; [3] be published in English. Acute moderate- to high-intensity exercise after sleep deprivation may reduce parasympathetic activity, trigger pro-inflammatory cytokines, and delay recovery to normal levels. In contrast, regular exercise routines may mitigate the adverse effects of sleep deprivation on autonomic regulation and reduce systemic inflammation. Sleep deprivation can lead to autonomic imbalance, increased blood pressure, and increased inflammatory responses, which are further amplified by acute exercise, increasing the cardiovascular burden. When sleep deprivation occurs, exercise intensity and timing should be carefully chosen to avoid adverse cardiovascular health risks.

Orthostatic testing for heart rate and heart rate variability monitoring in exercise science and practice

Orthostatic testing, involving the transition from different body positions (e.g., from lying or sitting position to an upright or standing position), offers valuable insights into the autonomic nervous system (ANS) functioning and cardiovascular regulation reflected through complex adjustments in, e.g., measures of heart rate (HR) and heart rate variability (HRV). This narrative review explores the intricate physiological mechanisms underlying orthostatic stress responses and evaluates its significance for exercise science and sports practice. Into this matter, active orthostatic testing (e.g., active standing up) challenges the cardiovascular autonomic function in a different way than a passive tilt test. It is well documented that there is a transient reduction in blood pressure while standing up, leading to a reflex increase in HR and peripheral vasoconstriction. After that acute response systolic and diastolic blood pressures are usually slightly increased compared to supine lying body position. The ANS response to standing is initiated by instantaneous cardiac vagal withdrawal, followed by sympathetic activation and vagal reactivation over the first 25-30 heartbeats. Thus, HR increases immediately upon standing, peaking after 15-20 beats, and is less marked during passive tilting due to the lack of muscular activity. Standing also decreases vagally related HRV indices compared to the supine position. In overtrained endurance athletes, both parasympathetic and sympathetic activity are attenuated in supine and standing positions. Their response to standing is lower than in non-overtrained athletes, with a tendency for further decreased HRV as a sign of pronounced vagal withdrawal and, in some cases, decreased sympathetic excitability, indicating a potential overtraining state. However, as a significant main characteristic, it could be noted that additional pathophysiological conditions consist in a reduced responsiveness or counter-regulation of neural drive in ANS according to an excitatory stimulus, such as an orthostatic challenge. Hence, especially active orthostatic testing could provide additional information about HR(V) reactivity and recovery giving valuable insights into athletes' training status, fatigue levels, and adaptability to workload. Measuring while standing might also counteract the issue of parasympathetic saturation as a common phenomenon especially in well-trained endurance athletes. Data interpretation should be made within intra-individual data history in trend analysis accounting for inter-individual variations in acute responses during testing due to life and physical training stressors. Therefore, additional measures (e.g., psychometrical scales) are required to provide context for HR and HRV analysis interpretation. However, incidence of orthostatic intolerance should be evaluated on an individual level and must be taken into account when considering to implement orthostatic testing in specific subpopulations. Recommendations for standardized testing procedures and interpretation guidelines are developed with the overall aim of enhancing training and recovery strategies. Despite promising study findings in the above-mentioned applied fields, further research, thorough method comparison studies, and systematic reviews are needed to assess the overall perspective of orthostatic testing for training monitoring and fine-tuning of different populations in exercise science and training.

Blood pressure and heart rate variability to assess autonomic response to an acute bout of high intensity interval exercise in healthy young adults

Autonomic nervous system (ANS) activity causes acute variations in blood pressure (BP) and heart rate (HR). These systems are challenged during high intensity interval exercise (HIIE). However, BP variability (BPV) and HR variability (HRV) response to HIIE is unknown. We characterized BPV and HRV during an acute HIIE bout using spectral low frequency [LF] and high frequency [HF] domains. We hypothesized that BPV would increase and HRV would decrease during high-intensity and active-recovery of HIIE compared to baseline [BL] and BPV would reduce and HRV would increase during cool down, post-HIIE, and 30 min post-HIIE compared to BL. HIIE involved 10 min of alternating high-intensity and active-recovery (approximately 70% and 10% of Wattmax) on a recumbent stepper. We did a secondary analysis on 23 datasets. The participants were 25 ± 1.5 years, 48% females. Our results showed high-intensity BPV LF was not significantly different from BL while HF increased. HRV LF and HF decreased compared to BL. During active-recovery, LF and HF for BPV and HRV increased greater than high-intensity. HRV LF and HF returned to BL after 30 min of recovery, whereas BPV HF was higher compared to BL. The rapid switching during HIIE uniquely modulates cardiovascular and ANS.

Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science

This updated guideline replaces the "Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science" first published in 2014. Based on the older version of the guideline, the authors have reviewed and evaluated the findings on the use of heart rate (HR) and heart rate variability (HRV) that have been published in the meantime and incorporated them into a new version of this guideline.This guideline was developed for application in clinical practice and research purposes in the fields of occupational medicine and occupational science to complement evaluation procedures with respect to exposure and risk assessment at the workplace by the use of objective physiological workload indicators. In addition, HRV is also suitable for assessing the state of health and for monitoring the progress of illnesses and preventive medical measures. It gives an overview of factors influencing the regulation of the HR and HRV at rest and during work. It further illustrates methods for measuring and analyzing these parameters under standardized laboratory and real workload conditions, areas of application as well as the quality control procedures to be followed during the recording and evaluation of HR and HRV.

Comparison of the Perceived Stress Reactivity Scale with physiological and self-reported stress responses during ecological momentary assessment and during participation in a virtual reality version of the Trier Social Stress Test

Valid approaches to conveniently measure stress reactivity are needed due to the growing evidence of its health-impairing effects. This study examined whether the Perceived Stress Reactivity Scale (PSRS) predicts cardiovascular and psychological responses to psychosocial stressors during daily life and during a virtual reality (VR) Trier Social Stress Test (TSST). Medical students answered a standardized baseline questionnaire to assess perceived stress reactivity by the PSRS. The PSRS asks participants to rate the intensity of their typical affective responses to common stressors during daily life. They were further asked to participate in a VR-TSST and in an ecological momentary assessment (EMA) over a period of three consecutive workdays during daily life. Blood pressure and self-reported stress were repeatedly, heart rate variability (HRV) continuously measured during the VR-TSST and EMA. Furthermore, participants repeatedly assessed task demands, task control and social conflict during the EMA. Data was analysed using multilevel analysis and multiple linear regression. Results indicate that the PSRS moderates associations between blood pressure (but not HRV) and demands and control during daily life. Furthermore, the PSRS directly predicted self-reported stress, but did not moderate associations between self-reported stress and demands, control and social conflict. The PSRS did not predict physiological and self-reported stress responses to the VR-TSST. This study partly confirmed convergent validity of the PSRS to stress reactivity in daily life. Furthermore, the lack of association between the PSRS and stress responses to the VR-TSST calls for future studies to search for reliable and valid ways to assess stress reactivity.

Sympathovagal Balance and Body Shape Index in Elite and Amateur Athletes: The Relationship Unraveled

Background Heart rate variability (HRV) is one piece among a complex network of adaptations existent in athletes that help them gain a better understanding of their own physiology. Sympathovagal balance is one of the spectral components of HRV analysis and is used to assess the frequently changing oscillations of a healthy heart, which can help in gauging the response of cardiac function towards physiological stress during exercise. This index is extensively used in appraising cardiac autonomic modulation. An evaluation of body composition in athletes has become a critical consideration when tracking HRV, as it helps practitioners understand the role of the autonomic nervous system (ANS) in obesity. The body shape index (BSI), which is based on waist circumference (WC), is an anthropometric parameter with decent predictive ability when measuring centripetal obesity. In this regard, the current study is an attempt to unravel the relationship between BSI and sympathovagal balance during exercise performed on two different instruments (treadmill and ergometer) by elite and amateur athletes. Methods It was an observational case-control study that included 30 elite and 120 amateur athletes. Symptom-limited exercise testing was performed by athletes on a motorized treadmill and ergometer in the sports physiology laboratory of a rural medical college in central India. Different anthropometric parameters like BSI and body surface area (BSA) were also recorded. Short-term HRV extracted from electrocardiogram (ECG) recordings was obtained using the Power Lab system and HRV analysis by LabChart software. Results The sympathovagal ratio, i.e., ratio of low frequency (LF) to high frequency (HF) in elite and amateur male populations showed a higher value than that in females, indicating a dominant sympathetic response in the males. There was a significant (p=0.042) positive correlation (r=0.24) between BSI and LF/HF Ratio in amateur females during treadmill exercise, whereas a significant (p=0.049) negative correlation (r=-0.27) was obtained in amateur males during ergometer exercise. Hence, increased weight and BSI were found to be associated with high sympathetic dominance, indicating a sympathovagal imbalance. Conclusion We attempted to explore the interaction between BSI and LF/HF during exercise performed on two different instruments (treadmill and ergometer) by elite and amateur athletes, which can help in testing the response of cardiac function to stress experienced during exercise. The study's uniqueness stems from discovering the relationship between BSI and HRV and how this relationship impacts sports performance. BSI measurement in athletes, both elite and amateur, allows for the assessment and forecasting of potential autonomic activity under exercise-induced stress by linking HRV with BSI.

Heart Rate Variability-Derived Thresholds for Exercise Intensity Prescription in Endurance Sports: A Systematic Review of Interrelations and Agreement with Different Ventilatory and Blood Lactate Thresholds

BACKGROUND

Exercise intensities are prescribed using specific intensity zones (moderate, heavy, and severe) determined by a 'lower' and a 'higher' threshold. Typically, ventilatory (VT) or blood lactate thresholds (LT), and critical power/speed concepts (CP/CS) are used. Various heart rate variability-derived thresholds (HRVTs) using different HRV indices may constitute applicable alternatives, but a systematic review of the proximity of HRVTs to established threshold concepts is lacking.

OBJECTIVE

This systematic review aims to provide an overview of studies that determined HRVTs during endurance exercise in healthy adults in comparison with a reference VT and/or LT concept.

METHODS

A systematic literature search for studies determining HRVTs in healthy individuals during endurance exercise and comparing them with VTs or LTs was conducted in Scopus, PubMed and Web of Science (until January 2022). Studies claiming to describe similar physiological boundaries to delineate moderate from heavy (HRVTlow vs. VTlow and/or LTlow), and heavy from severe intensity zone (HRVThigh vs. VThigh and/or LThigh) were grouped and their results synthesized.

RESULTS

Twenty-seven included studies (461 participants) showed a mean difference in relative HR between HRVTlow and VTlow of - 0.6%bpm in weighted means and 0.02%bpm between HRVTlow and LTlow. Bias between HR at HRVTlow and VTlow was 1 bpm (limits of agreement (LoA): - 10.9 to 12.8 bpm) and 2.7 bpm (LoA: - 20.4 to 25.8 bpm) between HRVTlow and LTlow. Mean difference in HR between HRVThigh and VThigh was 0.3%bpm in weighted means and 2.9%bpm between HRVThigh and LThigh while bias between HR at HRVThigh and VThigh was - 4 bpm (LoA: - 17.9 to 9.9 bpm) and 2.5 bpm (LoA: - 12.1 to 17.1 bpm) between HRVThigh and LThigh.

CONCLUSION

HRVTlow seems to be a promising approach for the determination of a 'lower' threshold comparable to VTlow and potentially for HRVThigh compared to VThigh, although the latter needs further empirical evaluation. LoA for both intensity zone boundaries indicates bias of HRVTs on an individual level. Taken together, HRVTs can be a promising alternative for prescribing exercise intensity in healthy, male athletes undertaking endurance activities but due to the heterogeneity of study design, threshold concepts, standardization, and lack of female participants, further research is necessary to draw more robust and nuanced conclusions.

Active Rehabilitation Following Acute Mild Traumatic Brain Injury: A Systematic Review

Purpose:

Following mild traumatic brain injury (mTBI), patients are often advised to restrict physical activity until full symptom resolution followed by gradual return to activity. However, extended rest periods may prolong recovery and contribute to persistent symptoms. Emerging evidence suggests early active rehabilitation that increases heart rate without exacerbating symptoms may improve mTBI patient recovery. This review aims to: (1) appraise evidence on active rehabilitation intervention for mTBI recovery within one-month of injury (i.e., exercise type, duration, intensity, etc.); and (2) recommend evidence-based rehabilitation protocols.

Method:

Pubmed, CINAHL, PsychARTICLES, SportDISCUS, and AMED databases were searched using key terms “mild Traumatic Brain Injury”, “Rehabilitation”, “Acute”, and their synonyms. Evidence was appraised using Cochrane RoB-2 and ROBINS-I.

Results:

434 citations were initially identified with seven papers systematically reviewed. Within the reviewed articles, only three were randomized controlled trials with low risk of bias, and four were non-randomized trials with low to moderate risk of bias. Findings highlighted that a range of active rehabilitation protocols were used with different exercise modalities (primarily treadmills and static cycling), durations (9–20 min, or until symptomatic, for 30–50 days or symptoms resolved), and intensities (low, moderate or high). Active rehabilitation did not cause any serious adverse events (i.e., death, hospitalisation etc.), and six studies reported that it did not exacerbate mTBI symptoms in any participants (with one participant having symptom worsening in one study). Overall, the majority of reviewed studies ( n = 4) showed that active rehabilitation decreased time to mTBI symptom resolution compared to controls (strict rest/stretching exercises).

Conclusions:

Individualized active rehabilitation prescribed within one-month post-mTBI appears to be safe and effective at decreasing recovery time to symptom resolution in mTBI. However, there is a lack of consensus regarding specific intervention protocols that needs to be addressed before adoption within clinical practice.

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.

Correlation between physical efficiency index using Harvard step test and heart rate variation in college students

The purpose of this study is to investigate the relationship between physical efficiency index (PEI) calculated by the Harvard step test and heart rate variation (HRV), and to identify parameters of HRV that can predict PEI in college students. Sixteen college students were participated in this study and they were randomly divided into two groups; higher PEI group (HPEI, n=6) and lower PEI group (LPEI, n=10). To investigate the relationship between PEI and HRV, we were measured HRV and Harvard step test. HRV test was the resting, immediately, 15 min and 30 min after the Harvard step test using electrocardiography device polyG-I. Relationship between PEI and HRV were determined Pearson correlation coefficient, and multiple regression analysis was performed for examining HRV parameters to predict PEI. As shown in the result, not only PEI was negatively correlated with root mean squared differences between adjacent normal RR intervals (RMSSD), but had a positive correlation with low-frequency/high-frequency, but also normalized low frequency (normLF), the ratio of LF, and RMSSD, the change in RR interval showed a significant difference at each time point of measurement according to PEI levels. But, there were no significant differences among the HRV variables except normLF and RMS-SD. Our findings suggest a critical information that PEI calculated by the Harvard step test can be used as an index to predict the autonomic nerve function, and high PEI may have a positive effect on changes in autonomic nerve activity during recovery after exercise intervention.

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.

Decrease of heart rate variability during exercise: An index of cardiorespiratory fitness

The present study proposes to measure and quantify the heart rate variability (HRV) changes during effort as a function of the heart rate and to test the capacity of the produced indices to predict cardiorespiratory fitness measures. Therefore, the beat-to-beat cardiac time interval series of 18 adolescent athletes (15.2 ± 2.0 years) measured during maximal graded effort test were detrended using a dynamical first-order differential equation model. HRV was then calculated as the standard deviation of the detrended RR intervals (SDRR) within successive windows of one minute. The variation of this measure of HRV during exercise is properly fitted by an exponential decrease of the heart rate: the SDRR is divided by 2 every increase of heart rate of 20 beats/min. The HR increase necessary to divide by 2 the HRV is linearly inversely correlated with the maximum oxygen consumption (r = -0.60, p = 0.006), the maximal aerobic power (r = -0.62, p = 0.006), and, to a lesser extent, to the power at the ventilatory thresholds (r = -0.53, p = 0.02 and r = -0.47, p = 0.05 for the first and second threshold). It indicates that the decrease of the HRV when the heart rate increases is faster among athletes with better fitness. This analysis, based only on cardiac measurements, provides a promising tool for the study of cardiac measurements generated by portable devices.

Acute Changes in Heart Rate Variability to Glucose and Fructose Supplementation in Healthy Individuals: A Double-Blind Randomized Crossover Placebo-Controlled Trial

Simple Summary

In this study, we investigated the cardio-autonomic stress responses to the ingestion of liquid glucose, fructose, a combination thereof and a placebo in healthy individuals at rest. The cardio-autonomic response was more pronounced in all groups with carbohydrates compared to placebo indicating an increased cardio-autonomic stress response resulting in a reduced heart-rate variability. When investigating different levels of blood glucose, the findings showed a significant decline in heart-rate variability with increasing blood glucose levels. This was also seen with severely low levels of blood glucose. The speed of how quick blood glucose increased and decreased also impacted the cardio-autonomic response which further deteriorated heart-rate variability. These findings indicate that healthy human’s autonomic system responds quickly to changes in their blood glucose.

Abstract

Background: It is unknown how different types of carbohydrates alter the cardio-autonomic system in healthy individuals. Therefore, the aim of this study was to investigate how heart-rate variability changes to single dose ingestion of glucose, fructose, glucose and fructose, and an artificial sweetener (sucralose). Methods: In a double-blind randomized crossover placebo-controlled setting, 15 participants received all study-specific substances in liquid form. During each 2-h visit, venous blood glucose was measured in a 5-min interval while heart-rate variability was measured continuously via Holter-electrocardiograph. Results: Ingestion of different types of carbohydrates and sucralose showed significant differences for heart rate (p < 0.001), SDNN (p < 0.008), RMSSD (p < 0.001), pNN50 (p < 0.001) and blood pressure (p < 0.001). Different glucose levels significantly altered parameters of heart-rate variability and blood pressure (all p < 0.001), while the rate of change in blood glucose led to changes in heart rate variability, but not in heart rate (p = 0.25) or blood pressure (p = 0.99). Conclusions: Ingestion of different types of carbohydrates lead to reductions in heart-rate variability compared to a placebo. Blood glucose values above or below 70–90 mg/dL decreased heart rate variability while this was also seen for rapid glucose changes, yet not as pronounced. Healthy individuals should be conscious about carbohydrate intake while maintaining blood glucose levels between 70–90 mg/dL.

Effect of maturation on parasympathetic modulation during exercise and recovery

OBJECTIVES

This study examined the effect of maturation on parasympathetic nervous system (PNS) response from rest to light- to moderate-intensity exercise and recovery from maximal exercise in pre- (n = 10; maturity offset = -3.0 ± 1.2 years; age = 10.1 ± 1.9 years), mid- (n = 9; maturity offset = -0.1 ± 0.6 years; age = 13.7 ± 1.0 years), and postpubertal (n = 10; maturity offset = 1.9 ± 0.6 years; age = 15.6 ± 1.2 years) boys and men (n = 10; age = 24.1 ± 2.0 years).

DESIGN

Participants completed seated rest, light-intensity exercise (50% HR_max), and moderate-intensity exercise (65% HR_max). Following moderate-intensity exercise, intensity was ramped to elicit maximal HR and followed by 25 min of seated recovery. Log transformed values for root mean square of successive differences (lnRMSSD), high-frequency power (lnHF) and normalized HF power (lnHFnu) assessed PNS modulation during 3 min of rest, light-intensity exercise, moderate-intensity exercise, and 3-min epochs throughout recovery.

RESULTS

During light-intensity exercise, lnRMSSD and lnHF were greater in prepubertal (lnRMSSD = 3.4 ± 0.3 ms; lnHF = 5.4 ± 0.7 ms²) compared to men (lnRMSSD = 2.8 ± 0.5 ms; lnHF = 4.0 ± 0.9 ms²). During moderate-intensity exercise, lnHF differed between prepubertal and men (2.8 ± 1.0 vs. 1.4 ± 1.0 ms²). During recovery, HRV variables were greater in prepubertal compared to postpubertal and men.

CONCLUSIONS

Prepubertal boys have reduced PNS withdrawal during light-intensity exercise and greater PNS reactivation following exercise.

Fractal correlation properties of heart rate variability as a biomarker of endurance exercise fatigue in ultramarathon runners

Although heart rate variability (HRV) indexes have been helpful for monitoring the fatigued state while resting, little data indicate that there is comparable potential during exercise. Since an index of HRV based on fractal correlation properties, alpha 1 of detrended fluctuation analysis (DFA a1) displays overall organismic demands, alteration during exertion may provide insight into physiologic changes accompanying fatigue. Two weeks after collecting baseline demographic and gas exchange data, 11 experienced ultramarathon runners were divided into two groups. Seven runners performed a simulated ultramarathon for 6 h (Fatigue group, FG) and four runners performed daily activity over a similar period (Control group, CG). Before (Pre) and after (Post) the ultramarathon or daily activity, DFA a1, heart rate (HR), running economy (RE) and countermovement jumps (CMJ) were measured while running on a treadmill at 3 m/s. In Pre versus Post comparisons, data showed a decline with large effect size in DFA a1 post intervention only for FG (Pre: 0.71, Post: 0.32; d = 1.34), with minor differences and small effect sizes in HR (d = 0.02) and RE (d = 0.21). CG showed only minor differences with small effect sizes in DFA a1 (d = 0.19), HR (d = 0.15), and RE (d = 0.31). CMJ vertical peak force showed fatigue-induced decreases with large effect size in FG (d = 0.82) compared to CG (d = 0.02). At the completion of an ultramarathon, DFA a1 decreased with large effect size while running at low intensity compared to pre-race values. DFA a1 may offer an opportunity for real-time tracking of physiologic status in terms of monitoring for fatigue and possibly as an early warning signal of systemic perturbation.

Heart rate variability kinetics during different intensity domains of cycling exercise in healthy subjects

The purpose of this study was to verify the heart rate variability (HRV) and heart rate (HR) kinetics during the fundamental phase in different intensity domains of cycling exercise. Fourteen males performed five exercise sessions: (1) maximal incremental cycling test; (2) two rest-to-exercise transitions for each intensity domain, that is, heavy (Δ30) and severe (Δ60) domains. HRV markers (SD1 and SD2) and HR kinetics in the fundamental phase were analyzed by first-order exponential fitting. There were no significant differences in amplitude values between SD1_Δ30 (8.98 ± 3.52 ms) and SD1_Δ60 (9.44 ± 3.24 ms) and SD2_Δ30 (24.93 ± 9.16 ms) and SD2_Δ60 (25.98 ± 7.29 ms). Significant difference was observed between HR_Δ30 (52 ± 7 bpm) and HR_Δ60 (63 ± 8 bpm). The time constant (τ) values were significantly different between SD1_Δ30 (17.61 ± 6.26 s) and SD1_Δ60 (13.86 ± 5.90 s), but not between SD2_Δ30 (20.06 ± 3.73 s) and SD2_Δ60 (19.47 ± 6.03 s) or HR_Δ30 (56.75 ± 18.22 s) and HR_Δ60 (58.49 ± 15.61 s). However, the τ values for HR_Δ30 were higher and significantly different in relation to SD1_Δ30 and SD2_Δ30, as well as for HR_Δ60 in relation to SD1_Δ60 and SD2_Δ60. The kinetics of the autonomic variable (SD1 marker) was accelerated by the increased intensity. Moreover, significant differences were found for the τ values, with faster HRV markers than HR, in both intensities of Δ30 and Δ60, which suggests that these variables indicate distinct and specific cardiac autonomic response times during different intensity domains in cycling.HIGHLIGHTS The application of HRV to optimize exercise prescription at different effort intensities is extremely important to obtain assertive and effective results.Analysis of the kinetic responses of HRV is a useful tool for the evaluation of exercise performance and health status.A faster kinetics was found for HRV markers in comparison to HR, for both intensities analysed, which suggests that these variables indicate distinct and specific cardiac autonomic response times during different intensity domains in cycling.

Real-Time Estimation of Aerobic Threshold and Exercise Intensity Distribution Using Fractal Correlation Properties of Heart Rate Variability: A Single-Case Field Application in a Former Olympic Triathlete

A non-linear heart rate variability (HRV) index based on fractal correlation properties called alpha1 of Detrended Fluctuation Analysis (DFA-alpha1), has been shown to change with endurance exercise intensity. Its unique advantage is that it provides information about current absolute exercise intensity without prior lactate or gas exchange testing. Therefore, real-time assessment of this metric during field conditions using a wearable monitoring device could directly provide a valuable exercise intensity distribution without prior laboratory testing for different applied field settings in endurance sports. Until of late no mobile based product could display DFA-alpha1 in real-time using off the shelf consumer products. Recently an app designed for iOS and Android devices, HRV Logger, was updated to assess DFA-alpha1 in real-time. This brief research report illustrates the potential merits of real-time monitoring of this metric for the purposes of aerobic threshold (AT) estimation and exercise intensity demarcation between low (zone 1) and moderate (zone 2) in a former Olympic triathlete. In a single-case feasibility study, three practically relevant scenarios were successfully evaluated in cycling, (1) estimation of a HRV threshold (HRVT) as an adequate proxy for AT using Kubios HRV software via a typical cycling stage test, (2) estimation of the HRVT during real-time monitoring using a cycling 6 min stage test, (3) a simulated 1 h training ride with enforcement of low intensity boundaries and real-time HRVT confirmation. This single-case field evaluation illustrates the potential of an easy-to-use and low cost real-time estimation of the aerobic threshold and exercise intensity distribution using fractal correlation properties of HRV. Furthermore, this approach may enhance the translation of science into endurance sports practice for future real-world settings.

A New Detection Method Defining the Aerobic Threshold for Endurance Exercise and Training Prescription Based on Fractal Correlation Properties of Heart Rate Variability

The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), a nonlinear index of heart rate variability (HRV) based on fractal correlation properties, has been shown to steadily change with increasing exercise intensity. To date, no study has specifically examined using the behavior of this index as a method for defining a low intensity exercise zone. The aim of this report is to compare both oxygen intake (VO₂) and heart rate (HR) reached at the first ventilatory threshold (VT1), a well-established delimiter of low intensity exercise, to those derived from a predefined DFA a1 transitional value. Gas exchange and HRV data were obtained from 15 participants during an incremental treadmill run. Comparison of both VO₂ and HR reached at VT1 defined by gas exchange (VT1 GAS) was made to those parameters derived from analysis of DFA a1 reaching a value of 0.75 (HRVT). Based on Bland Altman analysis, linear regression, intraclass correlation (ICC) and t testing, there was strong agreement between VT1 GAS and HRVT as measured by both HR and VO₂. Mean VT1 GAS was reached at 39.8 ml/kg/min with a HR of 152 bpm compared to mean HRVT which was reached at 40.1 ml/kg/min with a HR of 154 bpm. Strong linear relationships were seen between test modalities, with Pearson’s r values of 0.99 (p < 0.001) and.97 (p < 0.001) for VO₂ and HR comparisons, respectively. Intraclass correlation between VT1 GAS and HRVT was 0.99 for VO₂ and 0.96 for HR. In addition, comparison of VT1 GAS and HRVT showed no differences by t testing, also supporting the method validity. In conclusion, it appears that reaching a DFA a1 value of 0.75 on an incremental treadmill test is closely associated with crossing the first ventilatory threshold. As training intensity below the first ventilatory threshold is felt to have great importance for endurance sport, utilization of DFA a1 activity may provide guidance for a valid low training zone.

Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription?

Exercise and training prescription in endurance-type sports has a strong theoretical background with various practical applications based on threshold concepts. Given the challenges and pitfalls of determining individual training zones on the basis of subsystem indicators (e.g., blood lactate concentration, respiratory parameters), the question arises whether there are alternatives for intensity distribution demarcation. Considering that training in a low intensity zone substantially contributes to the performance outcome of endurance athletes and exceeding intensity targets based on a misleading aerobic threshold can lead to negative performance and recovery effects, it would be desirable to find a parameter that could be derived via non-invasive, low cost and commonly available wearable devices. In this regard, analytics conducted from non-linear dynamics of heart rate variability (HRV) have been adapted to gain further insights into the complex cardiovascular regulation during endurance-type exercise. Considering the reciprocal antagonistic behavior and the interaction of the sympathetic and parasympathetic branch of the autonomic nervous system from low to high exercise intensities, it may be promising to use an approach that utilizes information about the regulation quality of the organismic system to determine training-intensity distribution. Detrended fluctuation analysis of HRV and its short-term scaling exponent alpha1 (DFA-alpha1) seems suitable for applied sport-specific settings including exercise from low to high intensities. DFA-alpha1 may be taken as an indicator for exercise prescription and intensity distribution monitoring in endurance-type sports. The present perspective illustrates the potential of DFA-alpha1 for diagnostic and monitoring purposes as a “global” system parameter and proxy for organismic demands.

Multiple short bouts of exercise are better than a single continuous bout for cardiometabolic health: a randomised crossover trial

PURPOSE

To compare cardiometabolic responses to five consecutive days of daily postprandial exercise accumulated in three 10-min bouts or a single 30-min bout to a no-exercise control.

METHODS

Ten insufficiently active adults completed three trials in a randomised order. Each trial comprised five consecutive days of 30 min of exercise either accumulated in three separate 10-min bouts (ACC) after main meals; a single 30-min bout after dinner (CONT); or a no-exercise control (NOEX). Glucose regulation was assessed from an oral glucose tolerance test. Applanation tonometry was used to assess pulse wave velocity approximately 12 h following completion of the final trial.

RESULTS

Area under the 2-h glucose curve was similar for CONT (mean; 95% CI 917 mmol L^-1 2 h^-1; 815 to 1019) and ACC (931 mmol L^-1 2 h^-1; 794 to 1068, p = 0.671). Area under the 2-h insulin curve was greater following NOEX (70,328 pmol L^-1 2 h^-1; 30,962 to 109,693) than ACC (51,313 pmol L^-1 2 h^-1: 21,822 to 80,806, p = 0.007). Pulse wave velocity was lower for ACC (5.96 m s^-1: 5.38 to 6.53) compared to CONT (6.93 m s^-1: 5.92 to 7.94, p = 0.031) but not significantly lower for ACC compared to NOEX (6.52 m s^-1: 5.70 to 7.34, p = 0.151).

CONCLUSION

Accumulating 30 min of moderate-intensity walking in three bouts throughout the day is more effective at reducing markers of cardiometabolic health risk in insufficiently active, apparently healthy adults than a single daily bout. Both accumulated and single-bout walking were equally as effective at reducing postprandial glucose concentrations compared to a no-exercise control. Therefore, accumulating exercise in short bouts after each main meal might be more advantageous for overall cardiometabolic health.

Second Ventilatory Threshold Assessed by Heart Rate Variability in a Multiple Shuttle Run Test

Many studies have focused on heart rate variability in association with ventilatory thresholds. The purpose of the current study was to consider the ECG-derived respiration and the high frequency product of heart rate variability as applicable methods to assess the second ventilatory threshold (VT₂). Fifteen healthy young soccer players participated in the study. Respiratory gases and ECGs were collected during an incremental laboratory test and in a multistage shuttle run test until exhaustion. VΤ₂ was individually calculated using the deflection point of ventilatory equivalents. In addition, VT₂ was assessed both by the deflection point of ECG-derived respiration and high frequency product. Results showed no statistically significant differences between VT₂, and the threshold as determined with high frequency product and ECG-derived respiration (F(2,28)=0.83, p=0.45, η²=0.05). A significant intraclass correlation was observed for ECG-derived respiration (r=0.94) and high frequency product (r=0.95) with VT₂. Similarly, Bland Altman analysis showed a considerable agreement between VT₂ vs. ECG-derived respiration (mean difference of -0.06 km·h^-1, 95% CL: ±0.40) and VT₂ vs. high frequency product (mean difference of 0.02 km·h^-1, 95% CL: ±0.38). This study suggests that, high frequency product and ECG-derived respiration are indeed reliable heart rate variability indices determining VT₂ in a field shuttle run test.

Applicability of Dmax Method on Heart Rate Variability to Estimate the Lactate Thresholds in Male Runners

Introduction

The purpose of this study was to evaluate the application of the Dmax method on heart rate variability (HRV) to estimate the lactate thresholds (LT), during a maximal incremental running test (MIRT).

Methods

Nineteen male runners performed two MIRTs, with the initial speed at 8 km·h^-1 and increments of 1 km·h^-1 every 3 minutes, until exhaustion. Measures of HRV and blood lactate concentrations were obtained, and lactate (LT₁ and LT₂) and HRV (HRVT_DMAX1 and HRVT_DMAX2) thresholds were identified. ANOVA with Scheffe's post hoc test, effect sizes (d), the bias ± 95% limits of agreement (LoA), standard error of the estimate (SEE), Pearson's (r), and intraclass correlation coefficient (ICC) were calculated to assess validity.

Results

No significant differences were observed between HRVT_DMAX1 and LT₁ when expressed for speed (12.1 ± 1.4 km·h^-1 and 11.2 ± 2.1 km·h^-1; p=0.55; d = 0.45; r = 0.46; bias ± LoA = 0.8 ± 3.7 km·h^-1; SEE = 1.2 km·h^-1 (95% CI, 0.9-1.9)). Significant differences were observed between HRVT_DMAX2 and LT₂ when expressed for speed (12.0 ± 1.2 km·h^-1 and 14.1 ± 2.5 km·h^-1; p=0.00; d = 1.21; r = 0.48; bias ± LoA = -1.0 ± 1.8 km·h^-1; SEE = 1.1 km·h^-1 (95% CI, 0.8-1.6)), respectively. Reproducibility values were found for the LT₁ (ICC = 0.90; bias ± LoA = -0.7 ± 2.0 km·h^-1), LT₂ (ICC = 0.97; bias ± LoA = -0.1 ± 1.1 km·h^-1), HRVT_DMAX1 (ICC = 0.48; bias ± LoA = -0.2 ± 3.4 km·h^-1), and HRVT_DMAX2 (ICC = 0.30; bias ± LoA = 0.3 ± 3.5 km·h^-1).

Conclusions

The Dmax method applied over a HRV dataset allowed the identification of LT₁ that is close to aerobic threshold, during a MIRT.

Didgeridoo Health Promotion Method Improves Mood, Mental Stress, and Stability of Autonomic Nervous System

A potential method of health promotion using the traditional wooden brass instrument the didgeridoo was examined, especially in terms of mood, stress, and autonomic nerve stabilization. Twenty Japanese healthy subjects undertook 10 lessons of the Didgeridoo Health Promotion Method (DHPM) and a moods questionnaire, blood pressure, salivary amylase (sAmy) as a stress marker, pulse rate and autonomic balance expressed by Ln[low frequency (LF)/High frequency (HF) were examined twice before the entire lessons and once before and after each lesson. The subjects had improved total mood disturbance (TMD: overall mood disorder degree) as measured by the Japanese version of the Profile of Mood States 2nd Edition (POMS2) as a result of taking the lessons. The pulse of the subjects decreased after the lessons, which correlated with a reduction in sAmy. Additionally, it was found that sAmy decreased after the lessons with increasing age of the subject, subjects with higher TMD before the lessons, or subjects with higher sAmy values before the lessons. With autonomic balance measured by Ln[LF/HF], subjects who had parasympathetic dominance as a result of the lesson were significantly more frequent. Additionally, it has been shown that Ln[LF/HF] decreased over 10 weeks, and it is also clear that the effect is sustained. Health promotion is an important concern for societies as a whole. In this study, it became clear that the DHPM affected mood, stress, and autonomic stability. Future studies should focus on monitoring the effects of continuing the lessons for a longer period of time. Additionally, physical effects such as strength of respiratory muscles should be examined. DHPM may be employed in the work place to promote the mental health of workers as well as in regional neighborhood associations/communities.

Correlation properties of heart rate variability during endurance exercise: A systematic review

Background

Non‐linear measures of heart rate variability (HRV) may provide new opportunities to monitor cardiac autonomic regulation during exercise. In healthy individuals, the HRV signal is mainly composed of quasi‐periodic oscillations, but it also possesses random fluctuations and so‐called fractal structures. One widely applied approach to investigate fractal correlation properties of heart rate (HR) time series is the detrended fluctuation analysis (DFA). DFA is a non‐linear method to quantify the fractal scale and the degree of correlation of a time series. Regarding the HRV analysis, it should be noted that the short‐term scaling exponent alpha1 of DFA has been used not only to assess cardiovascular risk but also to assess prognosis and predict mortality in clinical settings. It has also been proven to be useful for application in exercise settings including higher exercise intensities, non‐stationary data segments, and relatively short recording times.

Method

Therefore, the purpose of this systematic review was to analyze studies that investigated the effects of acute dynamic endurance exercise on DFA‐alpha1 as a proxy of correlation properties in the HR time series.

Results

The initial search identified 442 articles (351 in PubMed, 91 in Scopus), of which 11 met all inclusion criteria.

Conclusions

The included studies show that DFA‐alpha1 of HRV is suitable for distinguishing between different organismic demands during endurance exercise and may prove helpful to monitor responses to different exercise intensities, movement frequencies, and exercise durations. Additionally, non‐linear DFA of HRV is a suitable analytical approach, providing a differentiated and qualitative view of exercise physiology.

Effects of Acute Normobaric Hypoxia on Non-linear Dynamics of Cardiac Autonomic Activity During Constant Workload Cycling Exercise

Aim

Measurements of Non-linear dynamics of heart rate variability (HRV) provide new possibilities to monitor cardiac autonomic activity during exercise under different environmental conditions. Using detrended fluctuation analysis (DFA) technique to assess correlation properties of heart rate (HR) dynamics, the present study examines the influence of normobaric hypoxic conditions (HC) in comparison to normoxic conditions (NC) during a constant workload exercise.

Materials and Methods

Nine well trained cyclists performed a continuous workload exercise on a cycle ergometer with an intensity corresponding to the individual anaerobic threshold until voluntary exhaustion under both NC and HC (15% O₂). The individual exercise duration was normalized to 10% sections (10-100%). During exercise HR and RR-intervals were continuously-recorded. Besides HRV time-domain measurements (meanRR, SDNN), fractal correlation properties using short-term scaling exponent alpha1 of DFA were calculated. Additionally, blood lactate (La), oxygen saturation of the blood (SpO₂), and rating of perceived exertion (RPE) were recorded in regular time intervals.

Results

We observed significant changes under NC and HC for all parameters from the beginning to the end of the exercise (10% vs. 100%) except for SpO₂ and SDNN during NC: increases for HR, La, and RPE in both conditions; decreases for SpO₂ and SDNN during HC, meanRR and DFA-alpha1 during both conditions. Under HC HR (40-70%), La (10-90%), and RPE (50-90%) were significantly-higher, SpO₂ (10-100%), meanRR (40-70%), and DFA-alpha1 (20-60%) were significantly-lower than under NC.

Conclusion

Under both conditions, prolonged exercise until voluntary exhaustion provokes a lower total variability combined with a reduction in the amplitude and correlation properties of RR fluctuations which may be attributed to increased organismic demands. Additionally, HC provoked higher demands and loss of correlation properties at an earlier stage during the exercise regime, implying an accelerated alteration of cardiac autonomic regulation.

Effects of a Short-Term Cycling Interval Session and Active Recovery on Non-Linear Dynamics of Cardiac Autonomic Activity in Endurance Trained Cyclists

Measurement of the non-linear dynamics of physiologic variability in a heart rate time series (HRV) provides new opportunities to monitor cardiac autonomic activity during exercise and recovery periods. Using the Detrended Fluctuation Analysis (DFA) technique to assess correlation properties, the present study examines the influence of exercise intensity and recovery on total variability and complexity in the non-linear dynamics of HRV. Sixteen well-trained cyclists performed interval sessions with active recovery periods. During exercise, heart rate (HR) and beat-to-beat (RR)-intervals were recorded continuously. HRV time domain measurements and fractal correlation properties were analyzed using the short-term scaling exponent alpha1 of DFA. Lactate (La) levels and the rate of perceived exertion (RPE) were also recorded at regular time intervals. HR, La, and RPE showed increased values during the interval blocks (p < 0.05). In contrast, meanRR and DFA-alpha1 showed decreased values during the interval blocks (p < 0.05). Also, DFA-alpha1 increased to the level in the warm-up periods during active recovery (p < 0.05) and remained unchanged until the end of active recovery (p = 1.000). The present data verify a decrease in the overall variability, as well as a reduction in the complexity of the RR-interval-fluctuations, owing to increased organismic demands. The acute increase in DFA-alpha1 following intensity-based training stimuli in active recovery may be interpreted as a systematic reorganization of the organism with increased correlation properties in cardiac autonomic activity in endurance trained cyclists.

Heart rate variability following youth concussion: how do autonomic regulation and concussion symptoms differ over time postinjury?

OBJECTIVES

Following youth concussion, objective physiological indicators are needed to corroborate changes in subjective clinical measures. The objectives of the current study were to: (1) explore the effect of concussion on heart rate variability (HRV) across days postinjury in youth athletes aged 13-18 years old, compared with healthy age-matched and sex-matched controls and (2) examine the relationship between postconcussion symptom domains (physical, cognitive, fatigue and emotional) and HRV.

METHODS

Prospective, longitudinal, case-control study (N=44). This study comprised 29 concussed athletes between the ages of 13 and 18 years old (21 females, 8 males) and 15 age-matched and sex-matched controls). All participants completed baseline testing, which included demographic information (age, sex, concussion history), self-reported concussion symptoms (Post-Concussion Symptom Inventory [PCSI]) and a 24-hour heart rate recording via the Polar RS800CX system. The PCSI and HRV were collected weekly while the participant was symptomatic and then 1, 3 and 6 months following symptom resolution. HRV variables included time and frequency domain measures. Data visualisations and mixed effects modelling were used to derive parsimonious models.

RESULTS

HRV increased across days postinjury. Concussion symptom domains (physical, cognitive, fatigue and emotional) all had a significant main effect on HRV; concussed participants who reported more symptoms had higher HRV compared with those who reported fewer symptoms. Visualisations of HRV depict the recovery trajectory as non-linear across time. No significant differences on HRV measures were found between concussed and control participants.

CONCLUSION

These preliminary findings provide the foundation to understand the varied trajectory and relationship between objective physiological measures and subjective symptom reporting.

Effect of Heart Rate Variability Biofeedback on Sport Performance, a Systematic Review

Aim is to determine if the training with heart rate variability biofeedback allows to improve performance in athletes of different disciplines. Methods such as database search on Web of Science, SpringerLink, EBSCO Academic Search Complete, SPORTDiscus, Pubmed/Medline, and PROQUEST Academic Research Library, as well as manual reference registration. The eligibility criteria were: (a) published scientific articles; (b) experimental studies, quasi-experimental, or case reports; (c) use of HRV BFB as main treatment; (d) sport performance as dependent variable; (e) studies published until October 2016; (f) studies published in English, Spanish, French or Portuguese. The guidelines of the PRISMA statement were followed. Out of the 451 records found, seven items were included. All studies had a small sample size (range from 1 to 30 participants). In 85.71% of the studies (n = 6) the athletes enhanced psychophysiological variables that allowed them to improve their sport performance thanks to training with heart rate variability biofeedback. Despite the limited amount of experimental studies in the field to date, the findings suggest that heart rate variability biofeedback is an effective, safe, and easy-to-learn and apply method for both athletes and coaches in order to improve sport performance.

Non-linear dynamics of heart rate variability during incremental cycling exercise

Within the last years complex models of cardiovascular regulation and exercise fatigue have implemented heart rate variability (HRV) as a measure of autonomic nervous system. Using detrended fluctuation analysis (DFA) to assess heart rate correlation properties, the present study examines the influence of exercise intensity on total variability and complexity in non-linear dynamics of HRV. Sixteen cyclists performed a graded exercise test on a bicycle ergometer. HRV time domain measures and fractal correlation properties were analyzed using short-term scaling exponent alpha1 of DFA. Amplitude and complexity of HRV parameters decreased significantly. DFA-alpha1 increased from rest to low exercise intensity and showed an almost linear decrease from higher intensities until exhaustion. These findings support a qualitative change in self-organized heart rate regulation from a complex autonomic control at rest and low intensities towards a breakdown of the interaction in control mechanisms with non-autonomic heart rate control dominating at high intensities.

Non-linear dynamics of cardiac autonomic activity during cycling exercise with varied cadence

In recent years, complex models of cardiac regulation have integrated heart rate variability (HRV) as a measure of the cardiac autonomic activity during exercise. Using detrended fluctuation analysis (DFA) technique, the present study examines the influence of cycling cadence and exercise duration on non-linear dynamics of HRV. Sixteen trained cyclists performed a 60-minute exercise bout at 90% of the individual anaerobic threshold on a bicycle ergometer. Cadence was changed every 10 min (90-120-60-120-60-90 rpm). Heart rate (HR) and RR-intervals were recorded continuously during exercise. HRV time domain measures (meanRR, SDNN) and correlation properties were analyzed using short-term scaling exponent alpha1 of DFA. Moreover, blood lactate (La) and rating of perceived exertion (RPE) were recorded at regular intervals at the end of condition. HR, La and RPE increased significantly at 120 rpm compared to 60 rpm. In contrast, all analyzed HRV parameters (meanRR, SDNN, DFA-alpha1) showed a significant decrease during cycling at 120 rpm compared to 60 rpm. The comparison of the first and last 10 min with the same cadence indicates a significant increase in HR and RPE, but also a significant decrease in all analyzed HRV measures. The decrease of HRV values over time and in relation to the increase in cadence indicates a decrease in the overall variability as well as a reduction in complexity of the RR-interval-fluctuations due to the increased organismic demands. Therefore, the decrease of DFA-alpha1 might be associated with a withdrawal of the organismic system aiming at the maintenance of the homeostasis under the control of the central nervous system. In this context, non-linear HRV analyses provide a more systemic view of cardiac regulation during exercise.

Correlations in magnitude series to assess nonlinearities: Application to multifractal models and heartbeat fluctuations

The correlation properties of the magnitude of a time series are associated with nonlinear and multifractal properties and have been applied in a great variety of fields. Here we have obtained the analytical expression of the autocorrelation of the magnitude series (C_{|x|}) of a linear Gaussian noise as a function of its autocorrelation (C_{x}). For both, models and natural signals, the deviation of C_{|x|} from its expectation in linear Gaussian noises can be used as an index of nonlinearity that can be applied to relatively short records and does not require the presence of scaling in the time series under study. In a model of artificial Gaussian multifractal signal we use this approach to analyze the relation between nonlinearity and multifractallity and show that the former implies the latter but the reverse is not true. We also apply this approach to analyze experimental data: heart-beat records during rest and moderate exercise. For each individual subject, we observe higher nonlinearities during rest. This behavior is also achieved on average for the analyzed set of 10 semiprofessional soccer players. This result agrees with the fact that other measures of complexity are dramatically reduced during exercise and can shed light on its relationship with the withdrawal of parasympathetic tone and/or the activation of sympathetic activity during physical activity.

Additive effects of heating and exercise on baroreflex control of heart rate in healthy males

This study assessed the additive effects of passive heating and exercise on cardiac baroreflex sensitivity (cBRS) and heart rate variability (HRV). Twelve healthy young men (25 ± 1 yr, 23.8 ± 0.5 kg/m²) randomly underwent two experimental sessions: heat stress (HS; whole body heat stress using a tube-lined suit to increase core temperature by ~1°C) and normothermia (NT). Each session was composed of a preintervention rest (REST1); HS or NT interventions; postintervention rest (REST2); and 14 min of cycling exercise [7 min at 40%HR_reserve (EX1) and 7 min at 60%HR_reserve (EX2)]. Heart rate and finger blood pressure were continuously recorded. cBRS was assessed using the sequence (cBRS_SEQ) and transfer function (cBRS_TF) methods. HRV was assessed using the indexes standard deviation of RR intervals (SDNN) and root mean square of successive RR intervals (RMSSD). cBRS and HRV were not different between sessions during EX1 and EX2 (i.e., matched heart rate conditions: EX1 = 116 ± 3 vs. 114 ± 3 and EX2 = 143 ± 4 vs. 142 ± 3 beats/min but different workloads: EX1 = 50 ± 9 vs. 114 ± 8 and EX2 = 106 ± 10 vs. 165 ± 8 W; for HS and NT, respectively; P < 0.01). However, when comparing EX1 of NT with EX2 of HS (i.e., matched workload conditions but with different heart rates), cBRS and HRV were significantly reduced in HS (cBRS_SEQ = 1.6 ± 0.3 vs. 0.6 ± 0.1 ms/mmHg, P < 0.01; SDNN = 2.3 ± 0.1 vs. 1.3 ± 0.2 ms, P < 0.01). In conclusion, in conditions matched by HR, the addition of heat stress to exercise does not affect cBRS and HRV. Alternatively, in workload-matched conditions, the addition of heat to exercise results in reduced cBRS and HRV compared with exercise in normothermia. NEW & NOTEWORTHY The present study assessed cardiac baroreflex sensitivity during the combination of heat and exercise stresses. This is the first study to show that prior whole body passive heating reduces cardiac baroreflex sensitivity and autonomic modulation of heart rate during exercise. These findings contribute to the better understanding of the role of thermoregulation on cardiovascular regulation during exercise.

Minimal Window Duration for Accurate HRV Recording in Athletes

Heart rate variability (HRV) is non-invasive and commonly used for monitoring responses to training loads, fitness, or overreaching in athletes. Yet, the recording duration for a series of RR-intervals varies from 1 to 15 min in the literature. The aim of the present work was to assess the minimum record duration to obtain reliable HRV results. RR-intervals from 159 orthostatic tests (7 min supine, SU, followed by 6 min standing, ST) were analyzed. Reference windows were 4 min in SU (min 3-7) and 4 min in ST (min 9-13). Those windows were subsequently divided and the analyses were repeated on eight different fractioned windows: the first min (0-1), the second min (1-2), the third min (2-3), the fourth min (3-4), the first 2 min (0-2), the last 2 min (2-4), the first 3 min (0-3), and the last 3 min (1-4). Correlation and Bland & Altman statistical analyses were systematically performed. The analysis window could be shortened to 0-2 instead of 0-4 for RMSSD only, whereas the 4-min window was necessary for LF and total power. Since there is a need for 1 min of baseline to obtain a steady signal prior the analysis window, we conclude that studies relying on RMSSD may shorten the windows to 3 min (= 1+2) in SU or seated position only and to 6 min (= 1+2 min SU plus 1+2 min ST) if there is an orthostatic test. Studies relying on time- and frequency-domain parameters need a minimum of 5 min (= 1+4) min SU or seated position only but require 10 min (= 1+4 min SU plus 1+4 min ST) for the orthostatic test.

Consecutive ultra-short-term heart rate variability to track dynamic changes in autonomic nervous system during and after exercise

OBJECTIVE

Quantitative measurement of the dynamic changes in autonomic nervous system (ANS) during and after exercise has great significance in clinical, sports training and other fields. A consecutive ultra-short-term (30 s, UST) heart rate variability (HRV) method was proposed to track the exercise-induced autonomic control of heart rate (HR).

APPROACH

Twenty-three healthy young men participated in the study. The first four stages of the Modified Bruce Protocol (S0-S3) were performed. Six HRV indices, i.e. HF (power of high frequency ranged from 0.15 to 0.4 Hz), LF (power of low frequency ranged from 0.04 to 0.15 Hz), LF/HF, SD1 and SD2 of Poincaré plot, and SD2/SD1, over 30 s were calculated every 5 s over 3 min RR time series during, as well as after, exercise.

MAIN RESULTS

The results showed that during exercise, SD1, SD2, HF and LF dropped down quickly and tended to stabilize. Particularly, SD1 and HF showed a slight upward trend in the lower three stages while the declining time of SD2 in S3 lasted longer than the other stages. SD2/SD1 increased rapidly first and then decreased slowly. The values of SD2/SD1 in S3 remained higher than those in the other stages. After exercise, SD1, SD2, HF and LF kept increasing first and then declined slowly or fluctuated with decaying amplitudes. SD2/SD1 increased initially, then decreased and fluctuated slightly.

SIGNIFICANCE

Compared with the indices in frequency domain, the Poincaré indices were more sensitive and accurate in UST measurement of ANS during exercise. The results demonstrated that the UST method could characterize the dynamic changing tendency of ANS during and after exercise and quantify the differences of changes in ANS induced by exercise with different intensities. In particular, the vagal branch functioned dominantly in controlling HR in S0 but the effect of the sympathetic branch on HR enhanced with the increase of exercise intensity. In addition, the transient changes of ANS related with the sudden onset of exercise could also be reflected, despite perhaps being limited by the computation window width to some extent. Thus, the consecutive UST Poincaré indices could provide a feasible and simple method to measure quantitatively the exercise-induced dynamic changes in ANS.

Noninvasive measurements to evaluate the effects of military training on the human autonomic nervous system

Background: Chinese university freshmen receive 4-weeks military training that involved moderate to intense physical exercise. Studies have demonstrated heterogeneous effects of exercise on the autonomic nervous system.

Objective: To evaluate the effects of training on the autonomic nervous system noninvasively using electrogastrograms, heart rate variability (HRV), pulse rate, and the sympathetic skin response (SSR).

Methods: Twenty freshmen received all assessments in the fasting state and after a standard meal: (1) one week before the training, (2) at the end of the second week of the training, and (3) one week after the training.

Results: (1) The training had a significant effect on meal-induced gastric pacemaker activity. Before the training, a standard meal did not increase the dominant frequency of gastric slow waves, but the frequency increased during and after the training; (2) The preprandial high frequency (HF), low frequency (LF), and very low frequency (VLF) components of heart rate variability decreased significantly after the training. The ratio of the LF and HF (LF/HF) of the heart rate variability (HRV) did not significantly change after a meal or training condition. The basal pulse rate did not change. The latencies of the sympathetic skin response (SSR), as measured in the arm muscle, increased in response to the training.

Conclusion: Military training affects meal-induced changes in gastric pacemaker activity, causes a marked reduction of the vagal tone to the heart with maintenance of the vagal-sympathetic balance, and its effects on SSR may reflect a reduction in sympathetic tone.

Sympathetic enhancement in futsal players but not in football players after repeated sprint ability test

BACKGROUND

Heart rate variability (HRV) can disclose the specific adaptation of sympathovagal modulation to exercise. This study investigated the change in HRV measures after anaerobic and aerobic intermittent exercises in university football and futsal players.

METHOD

36 male university students with physically active lifestyle (n=14), football (n=12), and futsal (n=10) participated in this study. The participants completed the repeated sprint ability (RSA) test and Yo-Yo (YY) intermittent recovery test level 1 in randomised order. ECG signals of the participants were recorded in supine position 15 min before and 30 min after exercises. Before exercise, and 5 and 30 min after exercise, the blood pressures were also taken.

RESULTS

In the RSA protocol, the percentage changes in normalised high-frequency power (nHFP) were significantly decreased, while the percentage changes in the very low/high frequency power ratio (VLHR) and low/high frequency power ratio (LHR) were significantly increased in futsal players after exercise, as compared with the controls. No significant changes in all HRV indices were found in the YY protocol, except the respiratory frequency.

CONCLUSIONS

After exercise, the percent decrease in vagal modulation in futsal players was significantly reduced, while the percentage increase in sympathetic modulation in futsal players was significantly enhanced in the RSA test, but not in the YY test, as compared with the control group. The increase in sympathetic activity and the decrease in vagal activity in the futsal players were greater than the corresponding increase and decrease in the football players in the RSA test.

Relationships between Psychophysiological Responses to Cycling Exercise and Post-Exercise Self-Efficacy

Although self-efficacy (SE) is an important determinant of regular exercise, it is unclear how subjective and physiological states before, during, and after the exercise session affects post-exercise SE. The aim of this study was to clarify subjective and physiological factors affecting post-exercise SE assessed after a single exercise session at a physiologically equivalent level. Forty-three healthy volunteers (28 women, 15 men) completed an 82-min experimental session, comprising a 22-min pre-exercise rest, a 30-min steady-state cycling exercise at moderate intensity [40% of heart rate (HR) reserve], and a 30-min post-exercise rest. We measured physiological (HR) and subjective [Rating of Perceived Exertion (RPE), Feeling Scale (FS)] states during the experimental session. Autonomic states were assessed by power spectral analysis of heart rate variability (HRV) during pre- and post-exercise rest. Post-exercise SE, which was the participants' confidence in their ability to perform the 30-min exercise that they had just performed, was assessed at 30-min post-exercise. A stepwise multiple regression analysis, with post-exercise SE as the dependent variable and physiological and subjective measures of the exercise as candidate explanatory variables, showed that post-exercise SE was negatively correlated with RPE and positively correlated with FS at the end of the 30-min exercise. In addition, post-exercise SE was negatively correlated with high-frequency power of the post-exercise HRV, an index of parasympathetic function. These results indicate that post-exercise SE is related not only to subjective responses to the exercise but also to autonomic response after the exercise.

Monitoring Fatigue Status with HRV Measures in Elite Athletes: An Avenue Beyond RMSSD?

Among the tools proposed to assess the athlete's “fatigue,” the analysis of heart rate variability (HRV) provides an indirect evaluation of the settings of autonomic control of heart activity. HRV analysis is performed through assessment of time-domain indices, the square root of the mean of the sum of the squares of differences between adjacent normal R-R intervals (RMSSD) measured during short (5 min) recordings in supine position upon awakening in the morning and particularly the logarithm of RMSSD (LnRMSSD) has been proposed as the most useful resting HRV indicator. However, if RMSSD can help the practitioner to identify a global “fatigue” level, it does not allow discriminating different types of fatigue. Recent results using spectral HRV analysis highlighted firstly that HRV profiles assessed in supine and standing positions are independent and complementary; and secondly that using these postural profiles allows the clustering of distinct sub-categories of “fatigue.” Since, cardiovascular control settings are different in standing and lying posture, using the HRV figures of both postures to cluster fatigue state embeds information on the dynamics of control responses. Such, HRV spectral analysis appears more sensitive and enlightening than time-domain HRV indices. The wealthier information provided by this spectral analysis should improve the monitoring of the adaptive training-recovery process in athletes.