The role of heart rate variability in sports physiology

Test-retest reliability and validity of vagally-mediated heart rate variability to monitor internal training load in older adults: a within-subjects (repeated-measures) randomized study

BACKGROUND

Vagally-mediated heart rate variability (vm-HRV) shows promise as a biomarker of internal training load (ITL) during exergame-based training or motor-cognitive training in general. This study evaluated the test-retest reliability of vm-HRV during exergaming in healthy older adults (HOA) and its validity to monitor ITL.

METHODS

A within-subjects (repeated-measures) randomized study was conducted that included baseline assessments and 4 measurement sessions. Participants played 5 exergames at 3 standardized levels of external task demands (i.e., "easy", "challenging", and "excessive") in random order for 90 s. Test-retest reliability was assessed on the basis of repeated-measures analyses of variance (ANOVA), intraclass correlation coefficients (ICC3,1), standard errors of measurement (SEM), and smallest detectable differences (SDD). Validity was determined by examining the effect of game level on vm-HRV in the ANOVA.

RESULTS

Fourty-three HOA (67.0 ± 7.0 years; 58.1% females (25 females, 18 males); body mass index = 23.7 ± 3.0 kg·m-2) were included. Mean R-R time intervals (mRR) and parasympathetic nervous system tone index (PNS-Index) exhibited mostly good to excellent relative test-retest reliability with no systematic error. Mean SEM% and SDD% were 36.4% and 100.7% for mRR, and 44.6% and 123.7% for PNS-Index, respectively. Significant differences in mRR and PNS-Index were observed between standardized levels of external task demands, with mostly large effect sizes (mean r = 0.847). These results persisted irrespective of the type of neurocognitive domain trained and when only motoric and cognitive demands were manipulated while physical intensity was kept constant. The remaining vm-HRV parameters showed inconsistent or poor reliability and validity.

CONCLUSION

Only mRR and PNS-Index demonstrated reliable measurement and served as valid biomarkers for ITL during exergaming at a group level. Nonetheless, the presence of large SEMs hampers the detection of individual changes over time and suggests insufficient precision of these measurements at the individual level. Future research should further investigate the reliability and validity of vm-HRV with a specific focus on comparing different measurement methodologies and exercise conditions, particularly focusing on ultra-short-term HRV measurements, and investigate the potential implications (i.e., superiority to other markers of ITL or monitoring strategies?) of using vm-HRV as a biomarker of ITL.

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.

Correlation Between Heart Rate Variability and Agility Scores of Elite Badminton Players: A Pilot Study

Introduction Heart rate variability (HRV) indexes the autonomic nervous system, and HRV values are found to be higher in elite badminton players. Since an athlete's agility has a direct influence on badminton sporting performance, this study will analyze the correlation between HRV and agility. Aim The study's primary aim is to analyze the correlation between HRV and agility scores of elite badminton players. Methodology Ten elite badminton players who are currently participating at the state and national levels were recruited for the study. The study's participants were aged between 18 and 21 years, had a body mass index (BMI) of less than 22.9 kg/m2, were currently training 10-12 sessions of badminton per week (120-180 minutes per session), and had no comorbidities, injuries, or illnesses. For a duration of 14 days, a cross-sectional study design was utilized to evaluate the badminton players. Participants were tested in two blocks; each block consisted of five days of HRV and agility testing (Southeast Missouri [SEMO] agility test) followed by a break for two days. Higher agility performance was reflected by a lower SEMO agility test score. Results Data were analyzed using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp., Armonk, NY). HRV and agility scores had a negative correlation, as indicated by the two-tailed Spearman correlation analysis (rs(8) = -0.82, P < 0.01). Conclusions The results showed that HRV and agility scores are highly correlated in elite badminton players. The results indicate that higher HRV values lead to better agility performance. Future studies need to be conducted on a large scale to evaluate the correlation in a diverse population.

Real-World Fatigue Testing in Professional Rugby Union: A Systematic Review and Meta-analysis

BACKGROUND

Professional rugby union is a high-intensity contact sport with position-specific high training and match volumes across a season that may lead to periods of fatigue if above a typically experienced threshold. This study assesses the influence of match play and/or training on fatigue levels in rugby union players.

OBJECTIVE

We aimed to perform a systematic review and meta-analysis of measures used to assess fatigue status in male professional rugby union players.

METHODS

Using electronic databases (PubMed, SPORTDiscus, Web of Science, Cochrane Library, EMBASE, and MEDLINE), a systematic review of fatigue testing in rugby union was conducted on (1) neuromuscular, (2) subjective self-report, (3) biochemical, and (4) heart rate-derived measures.

RESULTS

Thirty-seven articles were included in this systematic review, of which 14 were further included in a meta-analysis. The results of the meta-analysis revealed small, yet not significant, decreases in countermovement jump height immediately after (effect size [ES] =  - 0.29; 95% confidence interval [CI] - 0.64 to 0.06), 24 h (ES =  - 0.43; 95% CI - 3.99 to 3.21), and 48 h (ES =  - 0.22; 95% CI - 0.47 to 0.02) after exposure to rugby union match play or training. Reported wellness (ES =  - 0.33; 95% CI - 1.70 to 1.04) and tiredness (ES =  - 0.14; 95% CI - 1.30 to 1.03) declined over a period of a few weeks (however, the results were not-statistically significant), meanwhile muscle soreness increased (ES = 0.91; 95% CI 0.06 to 1.75) within the 96 h after the exposure to rugby union match play or training. Finally, while cortisol levels (ES = 1.87; 95% CI - 1.54 to 5.29) increased, testosterone declined (ES =  - 1.54; 95% CI - 7.16 to 4.08) within the 24 h after the exposure. However, these results were not statistically significant.

CONCLUSIONS

Subjective measures of muscle soreness can be used to assess fatigue after match play and training in rugby union players. Within-study and between-study variability for countermovement jump height, biochemical markers, and heart rate-derived measures means the utility (practical application) of these measures to assess fatigue in professional rugby union players after matches and training is unclear.

CLINICAL TRIAL REGISTRATION

PROSPERO ID: CRD42020216706.

Unveiling the acute neurophysiological responses to strength training: An exploratory study on novices performing weightlifting bouts with different motor learning models

Currently, there is limited evidence regarding various neurophysiological responses to strength exercise and the influence of the adopted practice schedule. This study aimed to assess the acute systemic effects of snatch training bouts, employing different motor learning models, on skill efficiency, electric brain activity (EEG), heart rate variability (HRV), and perceived exertion as well as mental demand in novices. In a within-subject design, sixteen highly active males (mean age: 23.13 ± 2.09 years) randomly performed snatch learning bouts consisting of 36 trials using repetitive learning (RL), contextual interference (blocked, CIb; and serial, CIs), and differential learning (DL) models. Spontaneous resting EEG and HRV activities were recorded at PRE and POST training bouts while measuring heart rate. Perceived exertion and mental demand were assessed immediately after, and barbell kinematics were recorded during three power snatch trials performed following the POST measurement. The results showed increases in alpha, beta, and gamma frequencies from pre- to post-training bouts in the majority of the tested brain regions (p values ranging from < 0.0001 to 0.02). The CIb model exhibited increased frequencies in more regions. Resting time domain HRV parameters were altered following the snatch bouts, with increased HR (p < 0.001) and decreased RR interval (p < 0.001), SDNN, and RMSSD (p values ranging from < 0.0001 to 0.02). DL showed more pronounced pulse-related changes (p = 0.01). Significant changes in HRV frequency domain parameters were observed, with a significant increase in LFn (p = 0.03) and a decrease in HFn (p = 0.001) registered only in the DL model. Elevated HR zones (> HR zone 3) were more dominant in the DL model during the snatch bouts (effect size = 0.5). Similarly, the DL model tended to exhibit higher perceived physical (effect size = 0.5) and mental exertions (effect size = 0.6). Despite the highest psycho-physiological response, the DL group showed one of the fewest significant EEG changes. There was no significant advantage of one learning model over the other in terms of technical efficiency. These findings offer preliminary support for the acute neurophysiological benefits of coordination-strength-based exercise in novices, particularly when employing a DL model. The advantages of combining EEG and HRV measurements for comprehensive monitoring and understanding of potential adaptations are also highlighted. However, further studies encompassing a broader range of coordination-strength-based exercises are warranted to corroborate these observations.

Quarter-Annulus Si-Photodetector with Equal Inner and Outer Radii of Curvature for Reflective Photoplethysmography Sensors

Reflection-type photoplethysmography (PPG) pulse sensors used in wearable smart watches, true wireless stereo, etc., have been recently considered a key component for monitoring biological signals such as heart rate, SPO3, and blood pressure. Typically, the optical front end (OFE) of these PPG sensors is heterogeneously configured and packaged with light sources and receiver chips. In this paper, a novel quarter-annulus photodetector (NQAPD) with identical inner and outer radii of curvature has been developed using a plasma dicing process to realize a ring-type OFE receiver, which maximizes manufacturing efficiency and increases the detector collection area by 36.7% compared to the rectangular PD. The fabricated NQAPD exhibits a high quantum efficiency of over 90% in the wavelength of 500 nm to 740 nm and the highest quantum efficiency of 95% with a responsivity of 0.41 A/W at the wavelength of 530 nm. Also, the NQAPD is shown to increase the SNR of the PPG signal by 5 to 7.6 dB compared to the eight rectangular PDs. Thus, reflective PPG sensors constructed with NQAPD can be applied to various wearable devices requiring low power consumption, high performance, and cost-effectiveness.

Exercise Exertion Level Prediction Using Data from Wearable Physiologic Monitors

This study aims to develop machine learning (ML) algorithms to predict exercise exertion levels using physiological parameters collected from wearable devices. Real-time ECG, oxygen saturation, pulse rate, and revolutions per minute (RPM) data were collected at three intensity levels during a 16-minute cycling exercise. Parallel to this, throughout each exercise session, the study subjects' ratings of perceived exertion (RPE) were gathered once per minute. Each 16-minute exercise session was divided into a total of eight 2-minute windows. Each exercise window was labeled as "high exertion," or "low exertion" classes based on the self-reported RPEs. For each window, the gathered ECG data were used to derive the heart rate variability (HRV) features in the temporal and frequency domains. Additionally, each window's averaged RPMs, heart rate, and oxygen saturation levels were calculated to form all the predictive features. The minimum redundancy maximum relevance algorithm was used to choose the best predictive features. Top selected features were then used to assess the accuracy of ten ML classifiers to predict the next window's exertion level. The k-nearest neighbors (KNN) model showed the highest accuracy of 85.7% and the highest F1 score of 83%. An ensemble model showed the highest area under the curve (AUC) of 0.92. The suggested method can be used to automatically track perceived exercise exertion in real-time.

Non-pharmacological interventions for the treatment of post-stroke fatigue: A systematic review

BACKGROUND

Post-stroke fatigue (PSF) affects 50% of stroke survivors. Current guidance on management of this condition is limited.

AIMS

This systematic review and meta-analysis aimed to identify and analyze all randomized clinical trials (RCTs) of non-pharmacological interventions for the treatment of PSF.

SUMMARY OF REVIEW

Six electronic databases were searched from inception to January 2023 for English-language RCTs investigating the efficacy of non-pharmacological interventions versus passive controls in patients with PSF. The primary outcome was fatigue severity at the end of the intervention. The Cochrane risk-of-bias (ROB)2 tool was used to assess evidence quality. A total of 7990 records were retrieved, 333 studies were scrutinized, and 13 completed RCTs (484 participants) were included. Interventions included psychological therapies, physical therapies, and brain stimulation. Nine studies provided sufficient data for meta-analysis, of which seven also had follow-up data. Fatigue severity was lower in the intervention groups at the end of the intervention compared with control (participants = 310, standardized mean difference (SMD) = -0.57, 95% confidence intervals (CIs) (-0.87 to -0.28)) and at follow-up (participants = 112, SMD = -0.36, 95% CIs (-0.83 to 0.10)). Certainty in the effect estimate was downgraded to low for a serious ROB and imprecision. Subgroup analysis revealed significant benefits with physical therapy and brain stimulation but not psychological therapies, though sample sizes were low.

CONCLUSION

Non-pharmacological interventions improved fatigue but the quality of evidence was low. Further RCTs are needed for PSF management.

Predicting Post-Traumatic Stress Disorder Treatment Response Using Heart Rate Variability to Virtual Reality Environment and Modified Stroop Task: An Exploratory Study

Predicting treatment response can inform treatment decisions, expectations, and optimize use of mental health treatment resources. This study examined heart rate (HR), heart rate variability (HRV), and a modified Stroop task (mStroop) to predict post-traumatic stress disorder (PTSD) treatment response. We report on an observational, longitudinal study with 45 U.S. veterans in outpatient PTSD care, who had deployed to Iraq or Afghanistan. HR and HRV were collected before, during, and after virtual reality (VR) combat and civilian scenes. HRV recovery was defined as HRV after a 3-minute VR simulation minus HRV during a VR scene. mStroop threat variables included index scores for combat and general threat. Self-report data were collected at baseline and 6 months later. The outcome variable was the 17-item Clinician Administered PTSD Scale (CAPS). Controlling for baseline CAPS and number of combat experiences, the following baseline HRV recovery variables were significant predictors of 6-month CAPS: standard deviation of normal beat to beat interval (SDNN) after combat scene minus SDNN during combat scene and low-frequency (LF HRV) after civilian scene minus LF during civilian scene. HRV at rest, HR reactivity, HR recovery, and mStroop scores did not predict treatment response. In conclusion, HRV recovery variables in the context of a standardized VR stressor were significant predictors of PTSD treatment response after controlling for baseline CAPS and number of combat experiences. The direction of this relationship indicates that greater baseline HRV recovery predicts lower 6-month PTSD symptom severity. This was an exploratory study in need of replication.

Optimizing support vector machines and autoregressive integrated moving average methods for heart rate variability data correction

Heart rate variability (HRV) is the variation in time between successive heartbeats and can be used as an indirect measure of autonomic nervous system (ANS) activity. During physical exercise, movement of the measuring device can cause artifacts in the HRV data, severely affecting the analysis of the HRV data. Current methods used for data artifact correction perform insufficiently when HRV is measured during exercise. In this paper we propose the use of autoregressive integrated moving average (ARIMA) and support vector regression (SVR) for HRV data artifact correction. Since both methods are only trained on previous data points, they can be applied not only for correction (i.e., gap filling), but also prediction (i.e., forecasting future values). Our paper describes:•why HRV is difficult to predict and why ARIMA and SVR might be valuable options.•finding the best hyperparameters for using ARIMA and SVR to correct HRV data, including which criterion to use for choosing the best model.•which correction method should be used given the data at hand.

Heart Rate Variability in Psychiatric Disorders: A Systematic Review

Introduction

Heart rate variability (HRV) is a measure of the fluctuation in time interval between consecutive heart beats. Decreased heart rate variability has been shown to have associations with autonomic dysfunction in psychiatric conditions such as depression, substance abuse, anxiety, and schizophrenia, although its use as a prognostic tool remains highly debated. This study aims to review the current literature on heart rate variability as a diagnostic and prognostic tool in psychiatric populations.

Methods

A literature search was conducted using the MEDLINE, EMBASE, Cochrane, and PsycINFO libraries to identify full-text studies involving adult psychiatric populations that reported HRV measurements. From 1647 originally identified, 31 studies were narrowed down through an abstract and full-text screen. Studies were excluded if they enrolled adolescents or children, used animal models, enrolled patients with another primary diagnosis other than psychiatric as outlined by the diagnostic and statistical manual of mental disorders (DSM) V, or if they assessed HRV in the context of treatment rather than diagnosis. Study quality assessment was conducted using a modified Downs and Blacks quality assessment tool for observational rather than interventional studies. Data were reported in four tables: 1) summarizing study characteristics, 2) methods of HRV detection, 3) key findings and statistics, and 4) quality assessment.

Results

There is significant variability between studies in their methodology of recording as well as reporting HRV, which makes it difficult to meaningfully interpret data that is clinically applicable due to the presence of significant bias in existing studies. The presence of an association between HRV and the severity of various psychiatric disorders, however, remains promising.

Conclusion

Future studies should be done to further explore how HRV parameters may be used to enhance the diagnosis and prognosis of several psychiatric disorders.

Analysis of time-domain indices, frequency domain measures of heart rate variability derived from ECG waveform and pulse-wave-related HRV among overweight individuals: an observational study

Background: Research on the compatibility of time domain indices, frequency domain measurements of heart rate variability obtained from electrocardiogram (ECG) waveforms, and pulse wave signal (pulse rate variability; PRV) features is ongoing. The promising marker of cardiac autonomic function is heart rate variability. Recent research has looked at various other physiological markers, leading to the emergence of pulse rate variability. The pulse wave signal can be studied for variations to understand better changes in arterial stiffness and compliance, which are key indicators of cardiovascular health. Methods: 35 healthy overweight people were included. The Lead II electrocardiogram (ECG) signal was transmitted through an analog-to-digital converter (PowerLab 8/35 software, AD Instruments Pty. Ltd., New South Wales, Australia). This signal was utilized to compute Heart Rate Variability (HRV) and was sampled at a rate of 1024 Hz. The same AD equipment was also used to capture a pulse signal simultaneously. The right index finger was used as the recording site for the pulse signal using photoplethysmography (PPG) technology. Results: The participants' demographic data show that the mean age was 23.14 + 5.27 years, the mean weight was 73.68 +  7.40 kg, the mean body fat percentage was 32.23   +  5.30, and the mean visceral fat percentage was 4.60   +  2.0. The findings revealed no noticeable difference between the median values of heart rate variability (HRV) and PRV. Additionally, a strong correlation was observed between HRV and PRV. However, poor agreement was observed in the measurement of PRV and HRV. Conclusion: All indices of HRV showed a greater correlation with PRV. However, the level of agreement between HRV and PRV measurement was poor. Hence, HRV cannot be replaced with PRV and vice-versa.

Exercise Cardiac Load and Autonomic Nervous System Recovery during In-Season Training: The Impact on Speed Deterioration in American Football Athletes

Fully restoring autonomic nervous system (ANS) function is paramount for peak sports performance. Training programs failing to provide sufficient recovery, especially during the in-season, may negatively affect performance. This study aimed to evaluate the influence of the physiological workload of collegiate football training on ANS recovery and function during the in-season. Football athletes recruited from a D1 college in the southeastern US were prospectively followed during their 13-week "in-season". Athletes wore armband monitors equipped with ECG and inertial movement capabilities that measured exercise cardiac load (ECL; total heartbeats) and maximum running speed during and baseline heart rate (HR), HR variability (HRV) 24 h post-training. These metrics represented physiological load (ECL = HR·Duration), ANS function, and recovery, respectively. Linear regression models evaluated the associations between ECL, baseline HR, HRV, and maximum running speed. Athletes (n = 30) were 20.2 ± 1.5 years, mostly non-Hispanic Black (80.0%). Negative associations were observed between acute and cumulative exposures of ECLs and running speed (β = -0.11 ± 0.00, p < 0.0000 and β = -0.15 ± 0.04, p < 0.0000, respectively). Similarly, negative associations were found between baseline HR and running speed (β = -0.45 ± 0.12, 95% CI: -0.70, -0.19; p = 0.001). HRV metrics were positively associated with running speed: (SDNN: β = 0.32 ± 0.09, p < 0.03 and rMSSD: β = 0.35 ± 0.11, p < 0.02). Our study demonstrated that exposure to high ECLs, both acutely and cumulatively, may negatively influence maximum running speed, which may manifest in a deteriorating ANS. Further research should continue identifying optimal training: recovery ratios during off-, pre-, and in-season phases.

The Effectiveness of Utilizing HRV Indices as a Predictor of ACFT Performance Outcomes

BACKGROUND

The Army Combat Fitness Test (ACFT) is a performance assessment used by the U.S. Army to assess a cadet's strength, endurance, and agility with a series of six events to ensure that cadets are combat ready. Heart rate variability (HRV) is an instrument that measures cardiac autonomic modulation and has been incorporated to predict the performance of athletes in daily training and competition since acute bouts of exercise alter HRV variables.

PURPOSE

To assess the applicability of using HRV to predict ACFT score performance outcomes in cadets.

METHODS

Fifty army cadets (n = 36 male; n = 14 female; age = 20.60 ± 3.61 years; height = 173.34 ± 10.39 cm; body mass = 76.33 ± 14.68 kg; body fat percentage  = 17.58 ± 5.26%) completed the ACFT and reported for HRV assessment. HRV assessment had the participant lay supine for 5 minutes, and traditional time and frequency domain variables were assessed. A Pearson's correlation and multiple linear regressions were run.

RESULTS

HRV time and frequency domains were not significantly correlated in linear regression models except the stress index (SI) and the 2-mile run (2MR). The standing power throw and sprint drag carry were significantly correlated with traditional HRV variables.

CONCLUSIONS

HRV was not a predictor of ACFT performance for individual events or overall ACFT. The SI presented predictive properties only for 2MR, with no other significant correlations between HRV variables with standing power throw and sprint drag carry. The SI ability to predict 2MR performance outcome via HRV is a promising tool to assess army cadet performance and recovery.

Wearable and Non-Invasive Sensors for Rock Climbing Applications: Science-Based Training and Performance Optimization

Rock climbing has evolved from a method for alpine mountaineering into a popular recreational activity and competitive sport. Advances in safety equipment and the rapid growth of indoor climbing facilities has enabled climbers to focus on the physical and technical movements needed to elevate performance. Through improved training methods, climbers can now achieve ascents of extreme difficulty. A critical aspect to further improve performance is the ability to continuously measure body movement and physiologic responses while ascending the climbing wall. However, traditional measurement devices (e.g., dynamometer) limit data collection during climbing. Advances in wearable and non-invasive sensor technologies have enabled new applications for climbing. This paper presents an overview and critical analysis of the scientific literature on sensors used during climbing. We focus on the several highlighted sensors with the ability to provide continuous measurements during climbing. These selected sensors consist of five main types (body movement, respiration, heart activity, eye gazing, skeletal muscle characterization) that demonstrate their capabilities and potential climbing applications. This review will facilitate the selection of these types of sensors in support of climbing training and strategies.

A Novel Sparse Linear Mixed Model for Multi-Source Mixed-Frequency Data Fusion in Telemedicine

Digital health and telemonitoring have resulted in a wealth of information to be collected to monitor, manage, and improve human health. The multi-source mixed-frequency health data overwhelm the modeling capacity of existing statistical and machine learning models, due to many challenging properties. Although predictive analytics for big health data plays an important role in telemonitoring, there is a lack of rigorous prediction model that can automatically predicts patients' health conditions, e.g., Disease Severity Indicators (DSIs), from multi-source mixed-frequency data. Sleep disorder is a prevalent cardiac syndrome that is characterized by abnormal respiratory patterns during sleep. Although wearable devices are available to administrate sleep studies at home, the manual scoring process to generate the DSI remains a bottleneck in automated monitoring and diagnosis of sleep disorder. To address the multi-fold challenges for precise prediction of the DSI from high-dimensional multi-source mixed-frequency data in sleep disorder, we propose a sparse linear mixed model that combines the modified Cholesky decomposition with group lasso penalties to enable joint group selection of fixed effects and random effects. A novel Expectation Maximization (EM) algorithm integrated with an efficient Majorization Maximization (MM) algorithm is developed for model estimation of the proposed sparse linear mixed model with group variable selection. The proposed method was applied to the SHHS data for telemonitoring and diagnosis of sleep disorder and found that a few significant feature groups that are consistent with prior medical studies on sleep disorder. The proposed method also outperformed a few benchmark methods with the highest prediction accuracy.

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

BACKGROUND AND AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Novel AI-based HRV analysis (NAIHA) in healthcare automation and related applications

BACKGROUND

Heart rate variability (HRV) analysis computed on R-R interval series of ECG records with heavy burden of ectopic beats or non-sinus rhythm can significantly distort HRV parameters and hence clinically ineligible for HRV analysis. Yet, existing algorithmic methods of HRV analysis do not check such eligibility and require manual identification of eligible window (portion of ECG record) to ensure reliability.

OBJECTIVE

We aimed to propose a robust algorithm with a sliding window feature to automate the identification of an eligible window, if available, which compute HRV parameters within that window obviating manual input.

METHODS

The proposed algorithm classifies each window as either eligible or ineligible. With a window classified eligible, we stop sliding through the record, otherwise we move to the next window and repeat the eligibility identification process, until either an eligible window is found, or all windows are exhausted.

RESULTS

When evaluated on random subset of 100 records from MIMIC-III waveform database, the proposed algorithm excluded every ineligible record, and missed only 1.25% of eligible ones. The HRV parameters computed using proposed method closely approximated the standard HRV analysis with Pearson correlation coefficients (ideally one) and fractions of variance unexplained (ideally zero) ranging from 96.3% to 99.8% and 0.34% to 7.43%, respectively.

CONCLUSIONS

When translated into practice, proposed algorithm will reduce clinicians'' burden without compromising the accuracy of HRV analysis, potentially leading to its wider adoption.

Automatic Detection of Aerobic Threshold through Recurrence Quantification Analysis of Heart Rate Time Series

During exercise with increasing intensity, the human body transforms energy with mechanisms dependent upon actual requirements. Three phases of the body's energy utilization are recognized, characterized by different metabolic processes, and separated by two threshold points, called aerobic (AerT) and anaerobic threshold (AnT). These thresholds occur at determined values of exercise intensity(workload) and can change among individuals. They are considered indicators of exercise capacities and are useful in the personalization of physical activity plans. They are usually detected by ventilatory or metabolic variables and require expensive equipment and invasive measurements. Recently, particular attention has focused on AerT, which is a parameter especially useful in the overweight and obese population to determine the best amount of exercise intensity for weight loss and increasing physical fitness. The aim of study is to propose a new procedure to automatically identify AerT using the analysis of recurrences (RQA) relying only on Heart rate time series, acquired from a cohort of young athletes during a sub-maximal incremental exercise test (Cardiopulmonary Exercise Test, CPET) on a cycle ergometer. We found that the minima of determinism, an RQA feature calculated from the Recurrence Quantification by Epochs (RQE) approach, identify the time points where generic metabolic transitions occur. Among these transitions, a criterion based on the maximum convexity of the determinism minima allows to detect the first metabolic threshold. The ordinary least products regression analysis shows that values of the oxygen consumption VO₂, heart rate (HR), and Workload correspondent to the AerT estimated by RQA are strongly correlated with the one estimated by CPET (r > 0.64). Mean percentage differences are <2% for both HR and VO₂ and <11% for Workload. The Technical Error for HR at AerT is <8%; intraclass correlation coefficients values are moderate (≥0.66) for all variables at AerT. This system thus represents a useful method to detect AerT relying only on heart rate time series, and once validated for different activities, in future, can be easily implemented in applications acquiring data from portable heart rate monitors.

The effects of a 3-day mountain bike cycling race on the autonomic nervous system (ANS) and heart rate variability in amateur cyclists: a prospective quantitative research design

BACKGROUND

The acute and chronic adaptation of endurance athletes' hearts shows that increased volume of endurance exercise might cause an acute reduction in cardiac function, causing a physiological cascade that leads to the release of cardiac biomarkers specific to cardiomyocyte stress. Heart rate variability (HRV) is a valuable tool used as a physiological measurement to evaluate the autonomic nervous system (ANS). It is frequently used to assess cardiac autonomic regulation, determining a patient's risk for unfavorable events. This study set out to determine the changes in the ANS by participating in a 3-day mountain bike cycling race in amateur cyclists using HRV as an outcome measure.

METHODS

Sixteen healthy participants (male and female) participating in a 3-day mountain bike cycling race underwent five-minute resting electrocardiography recordings in a supine position 2 days before the race (baseline testing). In addition, HRV measurements were recorded after each race day and 24 h post-race (recovery).

RESULTS

Time-domain and frequency-domain measures showed significant changes from baseline HRV parameters after each race day (p ≤ 0.05). In addition, our data revealed that the mean heart rate and R-R variability intervals did not return to baseline values after 24 h of recovery. Thus, autonomic nervous system (ANS) alterations may be due to changes in cardiac sympatho-vagal balance.

CONCLUSIONS

The main strength of this study is using HRV as a measuring and screening tool to assess cardiac autonomic activity, whereby the state of the ANS before and after endurance races can be measured. Thus, physicians, athletes, and coaches can determine the stress of endurance races on the ANS and plan recovery strategies. The reasoning is that if the ANS is in a state of sub-optimal function, susceptible amateur athletes might be at risk for a cardiovascular event or maladaptation due to the endurance race.

Heart rate variability among healthy untrained adults during mild intensity stationary cycling exercise

Background

Stationary cycling is the popular, preferred, and convenient form of exercise. During exercise, autonomic modulation is seen which can be assessed by heart rate variability (HRV). The aim of the study was to evaluate the changes in HRV during mild-intensity cycling exercise.

Materials and Methods

An observational cross-sectional study was done on 20 healthy male volunteers with the age (35.44 ± 4.12), height (71.12 ± 11.98), and weight (161.23 ± 11.65), BMI (27.12 ± 3.49) attending various YOGA sessions in AYUSH OPD. Volunteers underwent an exercise program at the mild intensity of 30% to 50% of maximal heart rate on a stationary cycle for 20 min. HRV was recorded by the HRV mobile unit Dynamika Machine at rest, every 5 min (4×) over 20 min and during the recovery period. Repeated measures of analysis of variance with post-hoc analysis with Bonferroni and Holm's multiple comparisons.

Results

Significant change was observed in mean heart rate and time domain parameters. Frequency domain parameters that showed significant change were total power, High Frequency- HF (ms²), Very Low Frequency -VLF (ms²), Low Frequency -LF (ms²), and Very Low Frequency %-VLF (%).

Conclusions

The HRV parameters conclusively point towards cardiac parasympathetic withdrawal and sympathetic dominance at the initiation of exercise. With the progression of exercise, the sympathetic influence is retained. In the recovery period parasympathetic reactivation gains control over heart rate as well as HRV. The HRV response to exercise challenges may be helpful in designing exercise programs based on variations in the autonomic response.

On the improvement of heart rate prediction using the combination of singular spectrum analysis and copula-based analysis approach

In recent years, many people have been working from home due to the exceptional circumstances concerning the coronavirus disease 2019 (COVID-19) pandemic. It has also negatively influenced general health and quality of life. Therefore, physical activity has been gaining much attention in preventing the spread of Severe Acute Respiratory Syndrome Coronavirus. For planning an effective physical activity for different clients, physical activity intensity and load degree needs to be appropriately adjusted depending on the individual's physical/health conditions. Heart rate (HR) is one of the most critical health indicators for monitoring exercise intensity and load degree because it is closely related to the heart rate. Heart rate prediction estimates the heart rate at the next moment based on now and other influencing factors. Therefore, an accurate short-term HR prediction technique can deliver efficient early warning for human health and decrease the happening of harmful events. The work described in this article aims to introduce a novel hybrid approach to model and predict the heart rate dynamics for different exercises. The results indicate that the combination of singular spectrum analysis (SSA) and the Clayton Copula model can accurately predict HR for the short term.

Beetroot Juice Produces Changes in Heart Rate Variability and Reduces Internal Load during Resistance Training in Men: A Randomized Double-Blind Crossover

Beetroot juice (BJ) has been used as a sport supplement, improving performance in resistance training (RT). However, its effect on the modulation of the autonomic nervous system has not yet been widely studied. Therefore, the objective of this randomized double-blind crossover study was to assess the effect of acute BJ supplementation compared to placebo in blood pressure (BP), heart rate (HR), heart rate variability (HRV) and internal load during RT measure as Root Mean Square of the Successive Differences between adjacent RR intervals Slope (RMSSD and RMSSD-Slope, respectively). Eleven men performed an incremental RT test (three sets at 60%, 70% and 80% of their repetition maximum) composed by back squat and bench press with. HR, HRV and RMSSD-Slope were measured during and post exercise. As the main results, RMSSD during exercise decrease in the BJ group compared to placebo (p = 0.023; ES = 0.999), there were no differences in RMSSD post-exercise, and there were differences in RMSSD-Slope between groups in favor of the BJ group (p = 0.025; ES = 1.104) with a lower internal load. In conclusion, BJ supplementation seems to be a valuable tool for the reduction in the internal load of exercise during RT measured as RMSSD-Slope while enhancing performance.

Influences of Intense Physical Effort on the Activity of the Autonomous Nervous System and Stress, as Measured with Photoplethysmography

Background: The autonomic nervous system, which is composed of the sympathetic and parasympathetic nervous system, is closely related to the cardiovascular system. The temporal variation between each of the intervals between the consecutive “R” waves of an electrocardiogram is known as heart rate variability. Depending on the type of activity, both systems can be activated, and also influence the interval between “R” waves. Currently, with advancements in technology and electronic devices, photoplethysmography is used. Photoplethysmography detects changes in the intensity of reflected light that allow differentiation between systole and diastole and, therefore, determines the heart rate, its frequency and its variations. In this way, changes in the autonomic nervous system can be detected by devices such as the Max Pulse®. Objective: To determine whether the information provided by Max Pulse® on autonomic balance and stress is modified after intense physical exercise, thereby determining whether there is a relationship with body composition, and also whether there are differences with respect to gender. Materials and Methods: Fifty-three runners (38.9% female) with a mean age of 31.3 ± 8.1 years participated in the study. Two measurements (before and after intense physical effort) were performed with the Max Pulse® device. The flotoplethysmography measurement lasted 3 min, and was performed in the supine position. The exercise test was performed on a treadmill. It was initiated at a speed of 6 and 7 km/h for women and men, respectively. Subjects indicated the end of the test by making a hand gesture when unable to continue the test. Results: Autonomic nervous system activity and mental stress values decreased significantly (p < 0.05) in men and women, while autonomic nervous system balance decreased only in women. Physical stress increased (p < 0.05) in both sexes. Conclusions: Intense exercise causes changes in variables that assess autonomic nervous system balance and stress, as measured by a device based on photoplethysmography. The changes are evident in both sexes, and are not related to body composition.

The Autonomic Imbalance of Myocardial Ischemia during Exercise Stress Testing: Insight from Short-Term Heart Rate Variability Analysis

Exercise stress testing (EST) has limited power in diagnosing obstructive coronary artery disease (CAD). The heart rate variability (HRV) analysis might increase the sensitivity of CAD detection. This study aimed to evaluate the correlation between short-term HRV and myocardial ischemia during EST, including the acceleration, maximum, and recovery stages of heart rate (HR). The HRV during EST from 19 healthy (RHC) subjects and 35 patients with CAD (25 patients with insignificant CAD (iCAD), and 10 patients with significant CAD (sCAD)) were compared. As a result, all HRV indices decreased at the maximum stage and no significant differences between iCAD and sCAD were found. The low-frequency power of heart rate signal (LF) of the RHC group recovered relatively quickly from the third to the sixth minutes after maximum HR, compared with that of the sCAD group. The relative changes of most HRV indices between maximum HR and recovery stage were lower in the sCAD group than in the RHC group, especially in LF, the standard deviation of all normal to normal intervals (SDNN), and the standard deviation in the long axis direction of the Poincaré plot analysis (SD2) indices (p < 0.05). The recovery slope of LF was significantly smaller in the sCAD group than in the RHC group (p = 0.02). The result suggests that monitoring short-term HRV during EST provides helpful insight into the cardiovascular autonomic imbalance in patients with significant CAD. The relative change of autonomic tone, especially the delayed sympathetic recovery, could be an additional marker for diagnosing myocardial ischemia.

The Impact on the Stress-Associated Autonomic Response of Physiotherapy Students Receiving Interferential Current in an Electrotherapy Training Session

Electrical currents are didactic contents widely applied in the training of physiotherapy students, but the treatment is considered a stressful situation for both the patient who receives it and the student who applies it. The aim of this study was to evaluate the stress-associated autonomic response of physiotherapy students receiving interferential current by measuring and analysing heart rate variability. An observational case-control study was conducted. Ninety healthy male volunteers, all physiotherapy degree students, were enrolled while attending laboratory practice during the 2020-2021 academic year. Participants were randomly allocated to a sham electrotherapy group (44 subjects), in which heart rate variability was recorded for 10 min, both at rest and during the application of sham technique on the lower back (10 min), and an electrotherapy group (46 subjects), applying the same procedure with the electrical current flowing. Outcome measures included baseline (seated position) and postintervention (prone position) time domain parameter, diameters of the Poincaré plot 1 and 2, stress score, and sympathetic/parasympathetic ratio. The sham electrotherapy group exhibited significant increases in time domain parameter (p = 0.027) and diameters of the Poincaré plot 1 (p = 0.032), with a small effect size (d ≤ 0.5). The electrotherapy group exhibited significant increases in time domain parameter and diameters of the Poincaré plot 1 and 2 (p < 0.001) and decreases in the stress score and sympathetic/parasympathetic ratio (p < 0.001), with a large effect size (d > 0.8) other than for the time domain parameter (d = 0.42), indicating increased parasympathetic and decreased sympathetic activity. After interventions, there were significant differences between groups in diameters of the Poincaré plot 2 (p < 0.001), stress score (p = 0.01) and sympathetic/parasympathetic ratio (p = 0.003), with moderate effect size (d > 0.5). The application of the interferential current technique produces stress-associated autonomic response characterized by greater parasympathetic activity and decreased sympathetic activity. Further studies are needed to determine possible adverse effects.

ECG performance in simultaneous recordings of five wearable devices using a new morphological noise-to-signal index and Smith-Waterman-based RR interval comparisons

Background

Numerous wearables are used in a research context to record cardiac activity although their validity and usability has not been fully investigated. The objectives of this study is the cross-model comparison of data quality at different realistic use cases (cognitive and physical tasks). The recording quality is expressed by the ability to accurately detect the QRS complex, the amount of noise in the data, and the quality of RR intervals.

Methods

Five ECG devices (eMotion Faros 360°, Hexoskin Hx1, NeXus-10 MKII, Polar RS800 Multi and SOMNOtouch NIBP) were attached and simultaneously tested in 13 participants. Used test conditions included: measurements during rest, treadmill walking/running, and a cognitive 2-back task. Signal quality was assessed by a new local morphological quality parameter morphSQ which is defined as a weighted peak noise-to-signal ratio on percentage scale. The QRS detection performance was evaluated with eplimited on synchronized data by comparison to ground truth annotations. A modification of the Smith-Waterman algorithm has been used to assess the RR interval quality and to classify incorrect beat annotations. Evaluation metrics includes the positive predictive value, false negative rates, and F1 scores for beat detection performance.

Results

All used devices achieved sufficient signal quality in non-movement conditions. Over all experimental phases, insufficient quality expressed by morphSQ values below 10% was only found in 1.22% of the recorded beats using eMotion Faros 360°whereas the rate was 8.67% with Hexoskin Hx1. Nevertheless, QRS detection performed well across all used devices with positive predictive values between 0.985 and 1.000. False negative rates are ranging between 0.003 and 0.017. eMotion Faros 360°achieved the most stable results among the tested devices with only 5 false positive and 19 misplaced beats across all recordings identified by the Smith-Waterman approach.

Conclusion

Data quality was assessed by two new approaches: analyzing the noise-to-signal ratio using morphSQ, and RR interval quality using Smith-Waterman. Both methods deliver comparable results. However the Smith-Waterman approach allows the direct comparison of RR intervals without the need for signal synchronization whereas morphSQ can be computed locally.

Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds.

Neurophysiological Markers for Monitoring Exercise and Recovery Cycles in Endurance Sports

The current study analyzes the suitability and reliability of selected neurophysiological and vegetative nervous system markers as biomarkers for exercise and recovery in endurance sport. Sixty-two healthy men and women, endurance trained and moderately trained, performed two identical acute endurance tests (running trial 1 and running trial 2) followed by a washout period of four weeks. Exercise protocol consisted of an acute running trial lasting 60 minutes. An intensity corresponding to 95% of the heart rate at individual anaerobic threshold for 40 minutes was followed by 20 minutes at 110%. At pre-exercise, post-exercise, three hours post-exercise and 24 hours post-exercise, experimental diagnostics on Brain-derived neurotrophic factor (BDNF), heart rate variability (HRV), Stroop Color and Word Test (SCWT), and Short-Form McGill Pain Questionnaire (SF-MPQ) were performed. Significant changes over time were found for all parameters (p < .05). Furthermore, there was an approached statistical significance in the interaction between gender and training status in BDNF regulation (F₍₃₎ = 2.43; p = 0.06), while gender differences were found only for LF/HF-ratio (3hPoEx, F₍₃₎ = 3.40; p = 0.002). Regarding the reliability, poor ICC-values (< 0.5) were found for BDNF, Stroop sensitivity and pNN50, while all other parameters showed moderate ICC-values (0.5-0.75). Plasma-BDNF, SCWT performance, pain perception and all HRV parameters are suitable exercise-sensitive markers after an acute endurance exercise. Moreover, pain perception, SCWT reaction time and all HRV parameters show a moderate reliability, others rather poor. In summary, a selected neurophysiological and vegetative marker panel can be used to determine exercise load and recovery in endurance sports, but its repeatability is limited due to its vaguely reliability.

PE augmented mindfulness: A neurocognitive framework for research and future healthcare

Various well-controlled studies have suggested that practitioners in mindfulness can be prone to patient drop-out (e.g., due to chronic stress, pathology, cognitive reactivity), despite researchers having identified the underlying mechanisms that link mindfulness to mental health. In this article, a framework for physical exercise (PE) augmented mindfulness is proposed, which posits that consistently practiced PE before meditation can support (early-stage) mindfulness. Neurocognitive research shows PE (aerobic exercises or yoga) and mindfulness to impact similar pathways of stress regulation that involve cognitive control and stress regulation, thereby supporting the proposed synergistic potential of PE augmented mindfulness. Research focused on the psychophysiological impact of PE, showed its practice to promote short-term neurocognitive changes that can promote both cognitive control and the attainment of mindful awareness (MA). In order to chart dose responses required for protocol development, further research will be presented. Together these findings are discussed in light of future research on this multidisciplinary topic, protocol development, mindful walking, and further application in healthcare and beyond.

Normative Data on Heart Rate Variability Time and Frequency Domain Indices in a Healthy Central Indian Population Undergoing Treadmill Exercise

Background

Heart rate variability (HRV) is becoming one of the most valuable tools for assessing a healthy heart's complex and constantly changing oscillations. This study was a pioneering attempt to establish normative data on HRV during treadmill exercise for monitoring the cardiovascular health of the central Indian population.

Methodology

This was a cross-sectional study in the Sports Physiology Laboratory of the Department of Physiology in a Rural Medical College in central India. One hundred and twenty healthy subjects in the age range 17-40 years were recruited. Short-term HRV (5 min) was extracted from ECG recordings obtained using the Power lab system, AD Instruments, Australia.

Results

Time domain indices for males were - Standard deviation of N-N interval (SDNN): 162.61±162.11; Square root of mean squared difference of N-N intervals (RMSSD): 355.79±798.27; the percentage of adjacent NN intervals that differ from each other by more than 50 ms (pNN50): 23.10±27.87. Frequency domain indices in males were- LF power (%)- 535.74±3625.96; HF power (%) - 33.15±24.31, LF nu: 33.12± 16.06; HF nu: 57.22±14.89; LF/HF:0.77±0.74. Time-domain indices for females were SDNN as168.49±130.09; RMSSD: 182.41±154.85; pNN50:32.33±26.59. Frequency domain indices in females were LF power (%)-19.85±6.13; HF power (%) 43.03±16.39, LF nu-30.53±9.88; HF nu -60.95±8.70; LF/HF:0.54±0.27.

Conclusion

Baseline normative values for HRV spectral and time-domain analysis have been established for their clinical use in comparing the HRV of a healthy individual to that of a deceased individual or an athlete.

Analysis of Short-Term Heart Rate Asymmetry in High-Performance Athletes and Non-Athletes

Heart rate asymmetry (HRA) refers to how asymmetrically the acceleration and deceleration patterns in heartbeat fluctuations are distributed. There is limited evidence regarding HRA changes in athletes and their association with autonomic regulation. This study aimed to compare the short-term HRA of high-performance athletes and non-athletes during an autonomic function test by calculating relevant HRA measures. This exploratory study obtained beat-to-beat RR interval time series from 15 high-performance athletes and 12 non-athletes during a standardized autonomic function test. This test includes rest, postural change, controlled respiration, prolonged orthostatism, exercise, and recovery phases. The following HRA parameters were computed from the RR time series for both groups: asymmetric spread index (ASI), slope index (SI), Porta’s index (PI), Guzik’s index (GI), and Ehlers’ index (EI). We found significant differences (p < 0.01) in the mean value of several HRA parameters between athletes and non-athletes and across the autonomic function test phases, mainly in postural change and recovery phases. Our results indicate that high-performance athletes manifest a higher number and magnitude of cardiac decelerations than non-athletes after an orthostatic challenge, as indicated by GI and EI. In addition, lower HRA was found in athletes in the recovery phase than in non-athletes, as indicated by ASI.

Estimation of Heart Rate Variability Parameters by Machine Learning Approaches Applied to Facial Infrared Thermal Imaging

Heart rate variability (HRV) is a reliable tool for the evaluation of several physiological factors modulating the heart rate (HR). Importantly, variations of HRV parameters may be indicative of cardiac diseases and altered psychophysiological conditions. Recently, several studies focused on procedures for contactless HR measurements from facial videos. However, the performances of these methods decrease when illumination is poor. Infrared thermography (IRT) could be useful to overcome this limitation. In fact, IRT can measure the infrared radiations emitted by the skin, working properly even in no visible light illumination conditions. This study investigated the capability of facial IRT to estimate HRV parameters through a face tracking algorithm and a cross-validated machine learning approach, employing photoplethysmography (PPG) as the gold standard for the HR evaluation. The results demonstrated a good capability of facial IRT in estimating HRV parameters. Particularly, strong correlations between the estimated and measured HR (r = 0.7), RR intervals (r = 0.67), TINN (r = 0.71), and pNN50 (%) (r = 0.70) were found, whereas moderate correlations for RMSSD (r = 0.58), SDNN (r = 0.44), and LF/HF (r = 0.48) were discovered. The proposed procedure allows for a contactless estimation of the HRV that could be beneficial for evaluating both cardiac and general health status in subjects or conditions where contact probe sensors cannot be used.

An Overview of the Sensors for Heart Rate Monitoring Used in Extramural Applications

This work presents an overview of the main strategies that have been proposed for non-invasive monitoring of heart rate (HR) in extramural and home settings. We discuss three categories of sensing according to what physiological effect is used to measure the pulsatile activity of the heart, and we focus on an illustrative sensing modality for each of them. Therefore, electrocardiography, photoplethysmography, and mechanocardiography are presented as illustrative modalities to sense electrical activity, mechanical activity, and the peripheral effect of heart activity. In this paper, we describe the physical principles underlying the three categories and the characteristics of the different types of sensors that belong to each class, and we touch upon the most used software strategies that are currently adopted to effectively and reliably extract HR. In addition, we investigate the strengths and weaknesses of each category linked to the different applications in order to provide the reader with guidelines for selecting the most suitable solution according to the requirements and constraints of the application.

Effects of Acute Interval Exercise on Arterial Stiffness and Cardiovascular Autonomic Regulatory Responses: A Narrative Review of Potential Impacts of Aging

The physiological changes associated with aging deleteriously impact cardiovascular function and regulation and therefore increase the risk of developing cardiovascular disease. There is substantial evidence that changes in the autonomic nervous system and arterial stiffness play an important role in the development of cardiovascular disease during the aging process. Exercise is known to be effective in improving autonomic regulation and arterial vascular compliance, but differences in the type and intensity of exercise can have varying degrees of impact on vascular regulatory responses and autonomic function. There is still little evidence on whether there are differences in the response of exercise interventions to cardiovascular modulatory effects across the lifespan. In addition, acute interval exercise challenges can improve autonomic modulation, although the results of interval exercise on autonomic physiological parameters vary. Therefore, this narrative review focuses on evaluating the effects of acute interval exercise on blood pressure regulation and autonomic responses and also incorporates studies investigating different age groups to evaluate the effects of acute interval exercise on the autonomic nervous system. Herein we also summarize existing literature examining the acute cardiovascular responses to varied modes of interval exercise, as well as to further compare the benefits of interval exercise with other types of exercise on autonomic regulation and arterial stiffness. After reviewing the existing literature, it has been shown that with advancing age, changes in the autonomic nervous activity of interval exercise result in significant impacts on the cardiovascular system. We document that with advancing age, changes in the autonomic nerves lead to aging of the nervous system, thereby affecting the regulation of blood pressure. According to the limited literature, interval exercise is more effective in attenuating arterial stiffness than continuous exercise, but the difference in exercise benefits may depend on the training mode, intensity, duration of exercise, and the age of participants. Therefore, the benefits of interval exercise on autonomic and arterial stiffness improvement still warrant investigation, particularly the impact of age, in future research.

Factors that affect heart rate variability following acute resistance exercise: A systematic review and meta-analysis

BACKGROUND

There is controversial evidence regarding the effect of acute resistance exercise (ARE) on heart rate variability (HRV) parameters, which indicates the activities of the cardiac autonomic nervous system. The aim of this study was to perform a systematic review and meta-analysis of the literature on the effect of ARE on HRV parameters and identify its possible moderating factors.

METHODS

The PubMed-Medline, Web of Science, SPORTDiscus, and Cochrane Library databases were searched. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) declaration was followed, and the methodological quality of the studies was evaluated. The level of significance was set at p ≤ 0.05. Twenty-six studies met the inclusion criteria. Main effect analyses between pre- and post-test interventions demonstrated an increase in normalized units low frequency (p < 0.001; standardized mean difference (SMD) = 0.78; 95% confidence interval (95%CI): 0.46‒1.11) and low frequency/high frequency ratio (p < 0.001; SMD = 0.82; 95%CI: 0.64‒0.99) and a decrease in standard deviation of the normal-to-normal (NN) interval (p < 0.001; SMD = -0.58; 95%CI: -0.85 to -0.30), root mean square of the successive differences (p < 0.001; SMD = -1.01; 95%CI: -1.29 to -0.74), and normalized units high frequency (p < 0.001; SMD: -1.08; 95%CI: -1.43 to -0.73) following ARE in healthy individuals range: 15 ± 1 to 48 ± 2 years; mean ± SD).

RESULTS

There were differences between the subgroups in the number of sets used in an exercise (p = 0.05) for root mean square of the successive differences, as well as for exercise intensity (p = 0.01) and rest between sets (p = 0.05) for normalized units high frequency. Interestingly, there were differences between the subgroups in training volume for root mean square of the successive differences (p = 0.01), normalized units high frequency (p = 0.003) and normalized units low frequency (p = 0.02).

CONCLUSION

Overall, there was a withdrawal of cardiac parasympathetic and activation of cardiac sympathetic modulations following ARE, and these changes were greater with higher training volume ∼30 min after ARE in healthy individuals. Furthermore, the number of sets, intensity, and rest between sets affected HRV parameters. However, gender, body mass index, and training status did not influence the changes in HRV parameters as a response to ARE.

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

BACKGROUND AND OBJECTIVE

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

METHOD

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

RESULTS

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

CONCLUSION

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

Role of Body Mass and Physical Activity in Autonomic Function Modulation on Post-COVID-19 Condition: An Observational Subanalysis of Fit-COVID Study

The harmful effects of coronavirus disease 2019 (COVID-19) can reach the autonomic nervous system (ANS) and endothelial function. Therefore, the detrimental multiorgan effects of COVID-19 could be induced by deregulations in ANS that may persist after the acute SARS-CoV-2 infection. Additionally, investigating the differences in ANS response in overweight/obese, and physically inactive participants who had COVID-19 compared to those who did not have the disease is necessary. The aim of the study was to analyze the autonomic function of young adults after mild-to-moderate infection with SARS-CoV-2 and to assess whether body mass index (BMI) and levels of physical activity modulates autonomic function in participants with and without COVID-19. Patients previously infected with SARS-CoV-2 and healthy controls were recruited for this cross-sectional observational study. A general anamnesis was taken, and BMI and physical activity levels were assessed. The ANS was evaluated through heart rate variability. A total of 57 subjects were evaluated. Sympathetic nervous system activity in the post-COVID-19 group was increased (stress index; p = 0.0273). They also presented lower values of parasympathetic activity (p < 0.05). Overweight/obese subjects in the post-COVID-19 group presented significantly lower parasympathetic activity and reduced global variability compared to non-obese in control group (p < 0.05). Physically inactive subjects in the post-COVID-19 group presented significantly higher sympathetic activity than active subjects in the control group. Parasympathetic activity was significantly increased in physically active subjects in the control group compared to the physically inactive post-COVID-19 group (p < 0.05). COVID-19 promotes changes in the ANS of young adults, and these changes are modulated by overweight/obesity and physical activity levels.

Assessment of Physiological Responses During Field Science Task Performance: Feasibility and Future Needs

Objective

By understanding the physiological demands of different types of tasks that will be performed during extravehicular activity (EVA) on Mars, human performance safety risks can be mitigated. In addition, such understanding can assist in planning EVAs with an appropriate balance of human health and safety with scientific mission return.

Background

This paper describes the results of a study of technical feasibility performed within a Mars human research analog, with participants conducting scientifically relevant planetary science sample analysis and return tasks in two distinct field locations.

Methods

The authors collected heart rate, respiration rate, and heart rate variability (HRV) data, using commercial off-the-shelf hardware and software from study participants as they performed field science tasks within a concept of operations for a Mars science return human expedition mission. These data were remotely monitored, shared in real time, and later analyzed to identify different responses to different tasks in order to determine if there were any predictable or consistent patterns among participants.

Results

It was ultimately determined that, while differences exist between responses to tasks, they are highly subject to multiple sources of individual variability, dynamics of evolving field science tasks, and demands of a demanding physical environment. Further, distributional analyses of participants do not support parametric statistical analysis techniques.

Conclusion

The authors conclude that the physiology of individual astronauts should be extensively studied and modeled to support individualized automated monitoring tools for each crew member that is sent to Mars. Application: Physiological monitoring for specialized populations will require significant individual-level analysis, baselining, and bootstrap statistical methods to enable appropriate human performance determinations.

The Effect of Studying a Double Degree in the Psychophysiological Stress Response in the Bachelor's Thesis Defense

The aim of this research was to analyze the effect of studying a single or double degree in the psychophysiological stress response and academic performance of university students in their bachelor's thesis defense. We analyzed the autonomic stress response, cortical arousal, subjective distress perception, and the sense of objective and subjective academic fulfilment of 84 single-degree physiotherapy students and 26 double-degree sport sciences and physiotherapy students during their bachelor's thesis defense. The results showed that the bachelor's thesis defense was a stressful event for double-degree students, showing an activation of the sympathetic nervous system and presenting a higher autonomic habituation response for the double degree students compared to the single degree students. We found higher mean grades during the whole degree and higher grades in the written and oral bachelor's thesis academic achievements for single-degree students compared to double-degree students. No significant differences were found between single-degree and double-degree students in subjective distress perception and cortical arousal. No correlation was found between academic performance variables and subjective distress perception, cortical arousal, and autonomic modulation variables. We conclude that the bachelor's thesis defense produces a large anticipatory anxiety response in single-degree physiotherapy students and in double-degree sport sciences and physiotherapy students. Double-degree students showed higher levels of habituation and adaptability to the stressful event, with a better autonomic response. Academic achievements were significantly higher among single-degree students compared to the double-degree group.

Different acquisition systems for heart rate variability analysis may lead to diverse outcomes

Heart rate variability (HRV) is a relevant physiological variable for the estimation of cardiac autonomic function. Although the gold standard for HRV registration is the electrocardiogram (ECG), several applications (APPs) have been increasingly developed. The evaluation carried out by these devices must be compatible with ECG standards. The aim of this study was to compare the data obtained simultaneously with ECG and APP with chest heart rate transmitters. Fifty-six healthy individuals (28 men and 28 women) were evaluated at rest through a short simultaneous HRV measurement with both devices. Data from both acquisition systems were analyzed separately using their own analysis software and exported and analyzed using a validated software. Signal recordings were compatible between the two acquisition systems (Pearson r=0.99; P<0.0001). Although a high correlation was found for the HRV variables obtained in the time domain (Spearman r=0.99; P<0.0001), the correlation decreased in the frequency domain (Pearson r=0.85; P<0.0001) when two software programs were used. Comparison of the averages of spectral analysis parameters also showed differences when HRV data were analyzed separately in each device for low-frequency (LF) and high-frequency (HF) bands. Although the portability of these mobile devices allows for optimal HRV evaluation, the direct analysis obtained from these devices must be carefully evaluated with respect to frequency domain parameters.

Heart Rate Variability Reflects Similar Cardiac Autonomic Function in Explosive and Aerobically Trained Athletes

Autonomic cardiac function can be indirectly detected non-invasively by measuring the variation in microtiming of heart beats by a method known as heart rate variability (HRV). Aerobic training for sport is associated with reduced risk for some factors associated with cardiovascular diseases (CVD), but effects on autonomic function in different athlete types are less known. To compare cardiac autonomic modulation using a standard protocol and established CVD risk factors in highly trained intercollegiate athletes competing in aerobic, explosive, and cross-trained sports. A total of 176 college athletes were categorized in distinct sports as explosive (EA), aerobic (AA), or cross-trained (mixed) athletes. Eight different HRV measures obtained at rest were compared across training type and five health factors: systolic (SBP), diastolic blood pressure (DBP), body weight (BW), sex, and race. All athletic types shared favorable HRV measures that correlated with low CVD risk factors and indicated normal sympathovagal balance. A significant correlation was reported between DBP and pNN50 (% RR intervals > 50 ms) (β = -0.214, p = 0.011) and between BW and low-frequency (LF) power (β = 0.205, p = 0.006). Caucasian and African American athletes differed significantly (p < 0.05) with respect to four HRV variables: pNN50, HF power, LF power, and LF/HF ratios. Explosive, aerobic and mixed athletes had similar cardiovascular and autonomic HRV results in all eight HRV parameters measured. All athletes reported LF and pNN50 values that were significantly correlated with two CVD risk factors: DBP and BW. Compared with Caucasian teammates, African American athletes demonstrated lower LF/HF and higher pNN50, indicating an even more favorable resting sympathovagal activity and healthy CV function.

Reflection-type photoplethysmography pulse sensor based on an integrated optoelectronic chip with a ring structure

Reflection-type photoplethysmography (PPG) pulse sensors are widely used in consumer markets to measure cardiovascular signals. Different from off-chip package solutions in which the light-emitting diode (LED) and photodetector (PD) are in separate chips, a GaN integrated optoelectronic chip with a novel ring structure is proposed to realize a PPG pulse sensor. The integrated optoelectronic chip consists of two multiple-quantum well (MQW) diodes. For higher sensitivities, the central and peripheral MQW diodes are suitable as the LED and PD, respectively. The results indicate that the integrated optoelectronic chip based on a blue LED epitaxial wafer is more suitable for the integrated PPG sensor based on device performance. Moreover, the amplitude of the PPG pulse signal collected from fingertips is higher than that from a wrist. The feasibility of the reflection-type PPG pulse sensor based on a GaN integrated optoelectronic chip is fully verified with the advantages of smaller sizes and lower costs.

Positive Relationship Between Precompetitive Sympathetic Predominance and Competitive Performance in Elite Extreme Sports Athletes

Elite athletes achieve superior performance under high pressure in competitive situations. Although it is known that such situations affect the precompetitive activity of their autonomic nervous system (ANS), the relationship between precompetitive ANS activity and performance remains controversial. Especially in extreme sports, it has been shown that cardiac sympathetic tone occurs in athletes before competition attempts. However, the relationship between precompetitive sympathetic tone and performance is unclear. To investigate this relationship in extreme sports, we organized a freestyle snowboard jumping competition and examined competitors' physiological states and performance during this event. The electrocardiograms (ECGs) of 20 elite snowboarders were measured 10 min before each jump in different competitive situations: practice, qualifying, and final sessions. The mean heart rate (HR), the low-frequency to high-frequency component ratio (LF/HF ratio), the logarithm of the HF (lnHF) component of the frequency-domain of the heart rate variability (HRV), the ratio of the standard deviation of all R-R intervals to the root mean square of successive differences of R-R intervals (SDNN/rMSSD ratio), and the rMSSD of the time-domain of the HRV were calculated from the ECG data. The results showed a significant increase in the mean HR as well as significant decreases in the lnHF component and rMSSD of the HRV as the sessions progressed. Interestingly, the mean HR, LF/HF ratio and SDNN/rMSSD ratio of the HRV showed significant positive correlations with competitive scores, and the lnHF component and rMSSD of the HRV showed significant negative correlations with the scores. Our results indicate that precompetitive ANS activity becomes predominantly sympathetic in elite extreme athletes, such as freestyle snowboarders, when the competition intensifies, and that this sympathetic predominance is positively related to competitive performance.

Applying Heart Rate Variability to Monitor Health and Performance in Tactical Personnel: A Narrative Review

Human performance optimization of tactical personnel requires accurate, meticulous, and effective monitoring of biological adaptations and systemic recovery. Due to an increased understanding of its importance and the commercial availability of assessment tools, the use of heart rate variability (HRV) to address this need is becoming more common in the tactical community. Measuring HRV is a non-invasive, practical method for objectively assessing a performer's readiness, workload, and recovery status; when combined with additional data sources and practitioner input, it provides an affordable and scalable solution for gaining actionable information to support the facilitation and maintenance of operational performance. This narrative review discusses the non-clinical use of HRV for assessing, monitoring, and interpreting autonomic nervous system resource availability, modulation, effectiveness, and efficiency in tactical populations. Broadly, HRV metrics represent a complex series of interactions resulting from internal and external stimuli; therefore, a general overview of HRV applications in tactical personnel is discussed, including the influence of occupational specific demands, interactions between cognitive and physical domains, and recommendations on implementing HRV for training and recovery insights into critical health and performance outcomes.

Can Reactivity of Heart Rate Variability Be a Potential Biomarker and Monitoring Tool to Promote Healthy Aging? A Systematic Review With Meta-Analyses

Background: Monitoring phasic responses of heart rate variability (HRV) in terms of HRV reactivity [i. e., the absolute change from resting state to on-task (i.e., absolute values of HRV measured during exercise)] might provide useful insights into the individual psychophysiological responses of healthy middle-aged to older adults (HOA) to cognitive and physical exercises. Objectives: To summarize the evidence of phasic HRV responses to cognitive and physical exercises, and to evaluate key moderating factors influencing these responses. Methods: A systematic review with meta-analyses was performed. Publications up to May 2020 of the databases Medline (EBSCO), Embase, Cochrane Library, CINAHL, Psycinfo, Web of Science, Scopus, and Pedro were considered. Controlled clinical trials and observational studies measuring phasic HRV responses to cognitive and/or physical exercises in HOA (≥50 years) were included. Results: The initial search identified 6,828 articles, of which 43 were included into the systematic review. Compared to resting state, vagally-mediated HRV indices were significantly reduced during all types of exercises [Hedge's g = -0.608, 95 % CI (-0.999 to -0.218), p = 0.002] indicating a significant parasympathetic withdrawal compared to rest. The key moderating variables of these responses identified included exercise intensity for physical exercises, and participant characteristics (i.e., level of cognitive functioning, physical fitness), task demands (i.e., task complexity and modality) and the individual responses to these cognitive challenges for cognitive exercises. In particular, higher task demands (task complexity and physical exercise intensity) were related to larger HRV reactivities. Better physical fitness and cognition were associated with lower HRV reactivities. Additionally, HRV reactivity appeared to be sensitive to training-induced cognitive and neural changes. Conclusion: HRV reactivity seems to be a promising biomarker for monitoring internal training load and evaluating neurobiological effects of training interventions. Further research is warranted to evaluate the potential of HRV reactivity as a monitoring parameter to guide cognitive-motor training interventions and/or as a biomarker for cognitive impairment. This may facilitate the early detection of cognitive impairment as well as allow individualized training adaptations that, in turn, support the healthy aging process by optimizing individual exercise dose and progression of cognitive-motor training.

Short-term exposure to particulate matter on heart rate variability in humans: a systematic review of crossover and controlled studies

As an indicator of cardiac autonomic function, heart rate variability (HRV) has been proven to decrease after short-term exposure to particulate matters (PM) based on controlled animal studies. In this study, we conducted a systematic review to investigate short-term effects of exposure with different particle sizes on HRV in humans. Both crossover and controlled studies of human which were published prior to February 2020 were searched on four electronic databases. The HRV parameters included standard deviation of normal-to-normal intervals (SDNN), root mean square of successive normal-to-normal intervals (RMSSD), percent of normal-to-normal intervals that differ by more than 50 milliseconds (PNN50), low frequency (LF), high frequency (HF), and LF/HF. This review included 14 studies with 300 participants. The short-term effects of PM exposure on HRV in humans are inconclusive. For time-domain parameters, one study showed higher SDNN values with 2-h exposure to PM, whereas another one showed lower SDNN values. One study found RMSSD increased after PM exposure. One study found PNN50 decreased after PM exposure. For frequency-domain parameters, two studies showed LF increased with 2-h exposure to PM, and two studies showed an increase of LF/HF after PM exposure. Four studies showed lower HF values after PM exposure, whereas two studies showed higher HF values. Five studies did not find statistically significant results for any HRV parameters. We could not conclude that short-term exposure to PM can influence autonomic nervous function. The inconsistent changes of HRV in response to PM exposure may have complex mechanisms, which remains to be elucidated.

Heart rate variability and chronotype - a systematic review

There is a scarcity of evidence on the association between heart rate variability (HRV) and chronotype, i.e., morningness and eveningness. The aim of this systematic review was to examine the association between chronotype, HRV, mood and stress response. We searched PubMed, Web of Science, Scopus, Cinahl, PsycINFO and Google Scholar for peer-reviewed articles published in English between January 2000 and June 2020. A total of 11 articles met the inclusion criteria and were on study population, assessment of HRV and chronotype, main results and study limitations. Seven of the included studies were experimental and four were crossovers. The sample size varied from 9 to 221 participants, and both females and males were included. HRV was assessed using mostly time-domain and frequency-domain parameters; nonlinear parameters were used in only one study. The most used assessments for measuring chronotype were the Horne-Östberg Morningness-Eveningness Questionnaire (MEQ) and the Munich Chronotype Questionnaire (MCTQ). The results showed that chronotype was associated with HRV, but the study designs were situation-specific, focusing, for example, on the effects of shiftwork, stressful situations, exercise, or sleep deprivation on HRV. In addition, some studies showed that evening types (E-type) performed better during evening or nighttime tasks, whereas morning types (M-type) performed better during morning activities. Specifically, E-types showed decreased HRV and HRV recovery in relation to tasks performed during morning or daytime when compared to M-types. As the findings are somewhat contradictory and include some methodological limitations (e.g., small sample sizes, age groups), it is important for future studies to evaluate the association between chronotype and HRV in a longitudinal setting. In addition, further research is needed to determine how chronotype can be optimally and individually utilized to increase the health and well-being of M-type and E-type individuals.