Time-frequency analysis of heart rate variability reveals cardiolocomotor coupling during dynamic cycling exercise in humans

Sound stimulation using the individual's heart rate to improve the stability and homeostasis of the autonomic nervous system

OBJECTIVES

In this study, we explain the role of enhancing the stability and homeostasis of the autonomic nervous system (ANS) by proposing the average heart rate sound resonance (aHRSR), a sound stimulation to prevent imbalance of ANS due to dynamic movement. The effect of aHRSR on ANS was analyzed through the time and frequency domain of heart rate variability (HRV) using the photoplethysmogram data (PPG) of 22 participants (DUIRB-202109-12).

METHOD

When the subjects performed dynamic movements that could cause changes in the ANS, HRV indicators using PPG data for 5 min before and after the movements were analyzed according to the presence or absence of aHRSR. The standard deviation of the NN intervals (SDNN), the square root of the mean squared differences of the NN intervals (RMSSD), low-frequency band (LF), and high-frequency band (HF), which represent sympathetic and parasympathetic nerve activity, were used as indicators, where SNDD and LF represent total ANS and sympathetic activity, while RMSSD and HF represent parasympathetic activity.

RESULTS

As the effects of aHRSR on dynamic movement, the recovery time of RR interval was advanced by about 15 s, SDNN increased from ([44.16 ± 13.11] to [47.85 ± 15.16]) ms, and RMSSD increased from ([23.73 ± 9.95] to [31.89 ± 12.48]) ms (p < 0.05), increasing the stability of the ANS and reducing instability. The effect of homeostasis of the ANS according to aHRSR is also shown in reducing the change rate of LF from (-13.83 to -8.83) %, and the rate of change of HF from (10.59 to 3.27) %.

CONCLUSIONS

These results suggest that aHRSR can affect the cardiovascular system by assisting physiological movements that occur during dynamic movement.

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.

Information-based analysis of the coupling between brain and heart reactions to olfactory stimulation

BACKGROUND

Analysis of the heart activity is one of the important areas of research in biomedical science and engineering. For this purpose, scientists analyze the activity of the heart in various conditions. Since the brain controls the heart's activity, a relationship should exist among their activities.

OBJECTIVE

In this research, for the first time the coupling between heart and brain activities was analyzed by information-based analysis.

METHODS

Considering Shannon entropy as the indicator of the information of a system, we recorded electroencephalogram (EEG) and electrocardiogram (ECG) signals of 13 participants (7 M, 6 F, 18-22 years old) in different external stimulations (using pineapple, banana, vanilla, and lemon flavors as olfactory stimuli) and evaluated how the information of EEG signals and R-R time series (as heart rate variability (HRV)) are linked.

RESULTS

The results indicate that the changes in the information of the R-R time series and EEG signals are strongly correlated (ρ=-0.9566).

CONCLUSION

We conclude that heart and brain activities are related.

Rhythm dynamics of the aging heart: an experimental study using conscious, restrained mice

Heart rate variability (HRV) is a measure of variation in time interval between heartbeats and reflects the influence of autonomic nervous system and circulating/locally released factors on sinoatrial node discharge. Here, we tested whether electrocardiograms (ECGs) obtained in conscious, restrained mice, a condition that affects sympathovagal balance, reveal alterations of heart rhythm dynamics with aging. Moreover, based on emergence of sodium channels as modulators of pacemaker activity, we addressed consequences of altered sodium channels on heart rhythm. C57Bl/6 mice and mice with enhanced late sodium current due to Nav1.5 mutation at Ser571 (S571E) at ~4 to ~24 mo of age, were studied. HRV was assessed using time- and frequency-domain and nonlinear parameters. For C57Bl/6 and S571E mice, standard deviation of RR intervals (SDRR), total power of RR interval variation, and nonlinear standard deviation 2 (SD2) were maximal at ~4 mo and decreased at ~18 and ~24 mo, together with attenuation of indexes of sympathovagal balance. Modulation of sympathetic and/or parasympathetic divisions revealed attenuation of autonomic tone at ~24 mo. At ~4 mo, S571E mice presented lower heart rate and higher SDRR, total power, and SD2 with respect to C57Bl/6, properties reversed by late sodium current inhibition. At ~24 mo, heart rate decreased in C57Bl/6 but increased in S571E, a condition preserved after autonomic blockade. Collectively, our data indicate that aging is associated with reduced HRV. Moreover, sodium channel function conditions heart rate and its age-related adaptations, but does not interfere with HRV decline occurring with age.NEW & NOTEWORTHY We have investigated age-associated alterations of heart rate properties in mice using conscious electrocardiographic recordings. Our findings support the notion that aging is coupled with altered sympathovagal balance with consequences on heart rate variability. Moreover, by using a genetically engineered mouse line, we provide evidence that sodium channels modulate heart rate and its age-related adaptations.

Characterization and reduction of exercise-based motion influence on heart rate variability using accelerator signals and channel decoding in the time-frequency domain

OBJECTIVE

Heart rate variability (HRV) is defined as the variation of the heart's beat to beat time intervals. Although HRV has been studied for decades, its response to stress tests and off-rest measurements is still under investigation. In this paper, we studied the influence of motion on HRV throughout different exercise tests, including a maximal running of healthy recreational runners, cycling, and walking tests of healthy subjects.

APPROACH

In our proposed method, we utilized the motion trajectory (which is known to exist partially in HRV) measured by a three-channel accelerator (ACC). We then estimated their shares in HRV using a wearable electrocardiogram (ECG) and an error-correcting problem formulation. In this method, we characterized the motion components of three orthogonal directions induced into the HRV signal, and then we suppressed the estimated motion artefact to construct a motion-attenuated spectrogram. Main results and Significance: Our analysis showed that HRV in the exercise context is susceptible to motion artefacts. Furthermore, the interpretation of autonomic nervous system (ANS) activity and HRV indices throughout exercise has a high margin of error depending on the intensity level, type of exercise, and motion trajectory. Our experiment on 84 healthy subjects throughout mid-intensity cycling and walking tests showed 39% and 32% influence on average, respectively. In addition, our proposed method revealed through a maximal running test with 11 runners that motion can describe on average 20%-40% of the HRV high-frequency (HF) energy at different workloads of running.

Spectral fusion-based breathing frequency estimation; experiment on activities of daily living

BACKGROUND

We study the estimation of breathing frequency (BF) derived from wearable single-channel ECG signal in the context of mobile daily life activities. Although respiration effects on heart rate variability and ECG morphology have been well established, studies on ECG-derived respiration in daily living settings are scarce; possibly due to considerable amount of disturbances in such data. Yet, unobtrusive BF estimation during everyday activities can provide vital information for both disease management and athletic performance optimization.

METHOD AND DATA

For robust ECG-derived BF estimation, we combine the respiratory information derived from R-R interval (RRI) variability and morphological scale variation of QRS complexes (MSV), acquired from ECG signals. Two different fusion techniques are applied on MSV and RRI signals: cross-power spectral density (CPSD) estimation and power spectrum multiplication (PSM). The algorithms were tested on large sets of data collected from 67 participants during office, household and sport activities, simulating daily living activities. We use spirometer reference BF to evaluate and compare our estimations made by different models.

RESULTS AND CONCLUSION

PSM acquires the least average error of BF estimation, [Formula: see text] and [Formula: see text], compared to the reference spirometer values. PSM offers approximately 25 and 75% less error in comparison with the CPSD fusion estimation and the estimation by those two exclusive sources, respectively. Our results demonstrate the superiority of both of the fusion approaches, compared to the estimation derived from either of RRI or MSV signals exclusively.

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.

A new approach for analysis of heart rate variability and QT variability in long-term ECG recording

Background and purpose

With the emergence of long-term electrocardiogram (ECG) recordings that extend several days beyond the typical 24–48 h, the development of new tools to measure heart rate variability (HRV) and QT variability is needed to utilize the full potential of such extra-long-term ECG recordings.

Methods

In this report, we propose a new nonlinear time–frequency analysis approach, the concentration of frequency and time (ConceFT), to study the HRV QT variability from extra-long-term ECG recordings. This approach is a generalization of Short Time Fourier Transform and Continuous Wavelet Transform approaches.

Results

As proof of concept, we used 14-day ECG recordings to show that the ConceFT provides a sharpened and stabilized spectrogram by taking the phase information of the time series and the multitaper technique into account.

Conclusion

The ConceFT has the potential to provide a sharpened and stabilized spectrogram for the heart rate variability and QT variability in 14-day ECG recordings.

Electronic supplementary material

The online version of this article (10.1186/s12938-018-0490-8) contains supplementary material, which is available to authorized users.

Contribution of body movements on the heart rate variability during high intensity running

We studied the association between the heart rate variability (HRV) and the subject's movement during high intensity running. HRV is affected by movement, and this phenomena is known as cardiolocomotor coupling (CLC). Characterization of movement related components on the HRV spectrogram is a principal step toward meaningful interpretation of autonomic nervous system (ANS) activity. According to the literature, the aliases of the first and second harmonics of the cadence frequency are the main contributors affecting HRV. Instead, we found out that there is another aliasing component containing significant power in the HRV spectrogram. The source of this component might be the arm swings, torso movement or any other mechanical movement along the horizontal axis, orthogonal to the cadence direction. Our results show that in 13 out of 22 subjects the spectral HRV component arising from the alias of the second harmonic of cadence frequency (vertical acceleration) accommodates significantly less energy than the component related to the alias of the first harmonic of horizontal acceleration. Therefore, neglecting this component and/or considering the second harmonic of the cadence frequency as more dominant one is not always a valid assumption.

An investigation into the relationship between heart rate variability and the ventilatory threshold in healthy moderately trained males

BACKGROUND

During incremental exercise, heart rate variability (HRV) has been shown to display distinct stabilization and inflection points, which have been used to indirectly detect the ventilatory threshold (VT).

METHODS

Ten moderately trained males (26·5 ± 5·9 years: VO_2peak 48·7 ± 4·1 ml min^-1  kg^-1 ) performed an incremental test on a cycle ergometer until volitional exhaustion with both R-R intervals and respiratory indices recorded. HRV was quantified using both nonlinear (Poincare plot; short-term variability SD1) and spectral analysis of the R-R intervals (high-frequency component; HFp). The VT was identified using the V-slope method. The relationship between HRV parameters and the VT was assessed using both a paired t-test and Pearson's product correlation. In addition, Bland and Altman plots were used to quantify the mean difference along with a 95% confidence interval.

RESULTS

When expressed as the corresponding heart rate values, both the SD1 and the HFp stabilization points revealed a strong (r = 0·86 and 0·087, respectively) correlation with the VT. However, only for SD1 this relationship was different to the VT (t-test). The Bland-Altman plots supported these findings showing wide limits of agreement present for SD1 and the VT whilst the relationship between HFp and the VT revealed narrower limits.

CONCLUSION

There does not appear to be a relationship present between the VT and the SD1 stabilization point in moderately trained healthy males, whereas the HFp stabilization point revealed a strong relationship with the VT when expressed as heart rate.

Effects of different stresses on cardiac autonomic control and cardiovascular coupling

The objective of this study was to investigate the impacts of different stresses on time-varying autonomic reactivity and cardiovascular coupling. In total, 25 male subjects were recruited. RR intervals (RRI), systolic and diastolic blood pressure (SBP, DBP), stroke volume (SV), cardiac output (CO), and systemic vascular resistance (SVR) values were collected during rest, mental arithmetic task (MAT), and cold pressor test (CPT). Baroreflex sensitivity (BRS) was derived using the transfer function method. Continuous wavelet transformation of RRI was used to describe the time-variant patterns of autonomic neural activities. Wavelet cross correlation and phase synchronization were used to estimate the amplitude and phase coupling between RRI and SBP. MAT was characterized by increased heart rate (HR), SBP, DBP, and CO with decreased BRS attributable to prolonged parasympathetic withdrawal. Moreover, cardiovascular coupling was disrupted in MAT. These results indicated that baroreflex was depressed, and the top-down system started to take action under mental stress. In CPT, SBP, DBP, and SVR increased significantly, whereas HR and BRS remained unchanged. The increase of sympathetic activity was transient, and cardiovascular coupling did not change in CPT. Intriguingly, the frequency of the maximum cross-correlation coefficient in the low-frequency band (0.04-0.15 Hz) was significantly decreased in CPT, which may be due to the change of resonance frequency of the baroreflex loop.NEW & NOTEWORTHY The study is the first to compare the time-variant pattern of autonomic nervous activities and cardiovascular coupling between the mental arithmetic task (MAT) and the cold pressor test (CPT). Our results demonstrated that MAT and CPT elicited different time-varying patterns of autonomic neural activities and cardiovascular synchronization. Both the amplitude and phase consistency of blood pressure and heart rate decreased in MAT. CPT may affect the harmonic frequency of the baroreflex loop.

Attenuation of the influence of cardiolocomotor coupling in heart rate variability interpretation during exercise test

During exercise test, cardiolocomotor coupling related components appear in heart rate variability (HRV), blurring its interpretation as autonomic nervous system (ANS) marker. These cardiolocomotor coupling related components are centered at the pedalling and running stride frequency, as well as at their aliases, and may overlap with the low frequency (LF) and high frequency (HF) components of HRV. In this work cardiolocomotor-related HRV components are studied during maximal exercise test on treadmill and cycle ergometer. Power in the bands related to cardiolocomotor coupling increases with exercise intensity in cycle ergometer but not in treadmill exercise test, where it displays higher values for all exercise intensities. A method is proposed to reduce the effect of this coupling in the interpretation of HRV. Evolution of the power in the low frequency (LF) and high frequency (HF) bands are studied after the proposed reduction of cardiolocomotor coupling, showing more significant changes with exercise intensity than before the method is applied.

Assessment of Heart Rate Variability Thresholds from Incremental Treadmill Tests in Five Cross-Country Skiing Techniques

The assessment of heart rate variability (HRV) thresholds (HRVTs) as an alternative of Ventilatory thresholds (VTs) is a relatively new approach with increasing popularity which has not been conducted in cross-country (XC) skiing yet. The main purpose of the present study was to assess HRVTs in the five main XC skiing-related techniques, double poling (DP), diagonal striding (DS), Nordic walking (NW), V1 skating (V1), and V2 skating (V2).Ten competitive skiers completed these incremental treadmill tests until exhaustion with a minimum of one to two recovery days in between each test. Ventilatory gases, HRV and poling frequencies were measured. The first HRV threshold (HRVT₁) was assessed using two time-domain analysis methods, and the second HRV threshold (HRVT₂) was assessed using two non-time varying frequency-domain analysis methods. HRVT₁ was assessed by plotting the mean successive difference (MSD) and standard deviation (SD) of normalized R-R intervals to workload. HRVT₁ was assessed by plotting high frequency power (HFP) and the HFP relative to respiratory sinus arrhythmia (HFP_RSA) with workload. HRVTs were named after their methods (HRVT_1-SD; HRVT_1-MSD; HRVT_2-HFP; HRVT_2-HFP-RSA). The results showed that the only cases where the proposed HRVTs were good assessors of VTs were the HRVT_1-SD of the DS test, the HRVT_1-MSD of the DS and V2 tests, and the HRVT_2-HFP-RSA of the NW test. The lack of a wider success of the assessment of HRVTs was reasoned to be mostly due to the high entrainment between the breathing and poling frequencies. As secondary finding, a novel Cardiolocomotor coupling mode was observed in the NW test. This new Cardiolocoomtor coupling mode corresponded to the whole bilateral poling cycle instead of corresponding to each poling action as it was reported to the date by the existing literature.

Time-frequency analysis of heart rate variability during the cold pressor test using a time-varying autoregressive model

Heart rate variability is a useful clinical tool for autonomic function assessment and cardiovascular disease diagnosis. To investigate the dynamic changes of sympathetic and parasympathetic activities during the cold pressor test, we used a time-varying autoregressive model for the time-frequency analysis of heart rate variability in 101 healthy subjects. We found that there were two sympathetic peaks (or two parasympathetic valleys) when the abrupt changes of temperature (ACT) occurred at the beginning and the end of the cold stimulus and that the sympathetic and parasympathetic activities returned to normal in about the last 2 min of the cold stimulus. These findings suggested that the ACT rather than the low temperature was the major cause of the sympathetic excitation and parasympathetic withdrawal. We also found that the onsets of the sympathetic peaks were 4-26 s prior to the ACT and the returns to normal were 54-57 s after the ACT, which could be interpreted as the feedforward and adaptation of the autonomic regulation process in the human body, respectively. These results might be helpful for understanding the regulatory mechanisms of the autonomic system and its effects on the cardiovascular system.

Stochastic cardiac pacing increases ventricular electrical stability--a computational study

The ventricular tissue is activated in a stochastic rather than in a deterministic rhythm due to the inherent heart rate variability (HRV). Low HRV is a known predictor for arrhythmia events and traditionally is attributed to autonomic nervous system tone damage. Yet, there is no model that directly assesses the antiarrhythmic effect of pacing stochasticity per se. One-dimensional (1D) and two-dimensional (2D) human ventricular tissues were modeled, and both deterministic and stochastic pacing protocols were applied. Action potential duration restitution (APDR) and conduction velocity restitution (CVR) curves were generated and analyzed, and the propensity and characteristics of action potential duration (APD) alternans were investigated. In the 1D model, pacing stochasticity was found to sustain a moderating effect on the APDR curve by reducing its slope, rendering the tissue less arrhythmogenic. Moreover, stochasticity was found to be a significant antagonist to the development of concordant APD alternans. These effects were generally amplified with increased variability in the pacing cycle intervals. In addition, in the 2D tissue configuration, stochastic pacing exerted a protective antiarrhythmic effect by reducing the spatial APD heterogeneity and converting discordant APD alternans to concordant ones. These results suggest that high cardiac pacing stochasticity is likely to reduce the risk of cardiac arrhythmias in patients.

Heart rate variability and blood pressure during dynamic and static exercise at similar heart rate levels

Aim was to elucidate autonomic responses to dynamic and static (isometric) exercise of the lower limbs eliciting the same moderate heart rate (HR) response. Method: 23 males performed two kinds of voluntary exercise in a supine position at similar heart rates: static exercise (SE) of the lower limbs (static leg press) and dynamic exercise (DE) of the lower limbs (cycling). Subjective effort, systolic (SBP) and diastolic blood pressure (DBP), mean arterial pressure (MAP), rate pressure product (RPP) and the time between consecutive heart beats (RR-intervals) were measured. Time-domain (SDNN, RMSSD), frequency-domain (power in the low and high frequency band (LFP, HFP)) and geometric measures (SD1, SD2) as well as non-linear measures of regularity (approximate entropy (ApEn), sample entropy (SampEn) and correlation dimension D2) were calculated. Results: Although HR was similar during both exercise conditions (88±10 bpm), subjective effort, SBP, DBP, MAP and RPP were significantly enhanced during SE. HRV indicators representing overall variability (SDNN, SD 2) and vagal modulated variability (RMSSD, HFP, SD 1) were increased. LFP, thought to be modulated by both autonomic branches, tended to be higher during SE. ApEn and SampEn were decreased whereas D₂ was enhanced during SE. It can be concluded that autonomic control processes during SE and DE were qualitatively different despite similar heart rate levels. The differences were reflected by blood pressure and HRV indices. HRV-measures indicated a stronger vagal cardiac activity during SE, while blood pressure response indicated a stronger sympathetic efferent activity to the vessels. The elevated vagal cardiac activity during SE might be a response mechanism, compensating a possible co-activation of sympathetic cardiac efferents, as HR and LF/HF was similar and LFP tended to be higher. However, this conclusion must be drawn cautiously as there is no HRV-marker reflecting “pure” sympathetic cardiac activity.

Estimation of the anaerobic threshold from heart rate variability in an incremental swimming test

This study aimed to evaluate, in swimming, the agreement between the anaerobic threshold (AT) as determined from the analysis of blood lactate concentration ([La]) and from a new method based on the heart rate (HR) variability (HRV). Fourteen high-level swimmers completed an incremental 7 × 200-m front crawl test, during which the HRV was measured continuously and [La] was collected after each step. To individuate the AT, the trends of the high-frequency HRV spectral power (HFPOW) and of the fraction of HFPOW relative to the respiratory sinus arrhythmia (HFPOW-RSA) were analyzed. In all the subjects, an abrupt increase of both HFPOW and HFPOW-RSA was observed and associated with the AT. The AT parameters determined, respectively, from [La] and HFPOW-RSA were similar (p > 0.05) and highly correlated (HR: 182.0 ± 8.1 vs. 181.1 ± 8.2 b·min, r = 0.93, 95% limits of agreement [LoA]: -6.7 to 4.9 b·min; velocity: 1.47 ± 0.11 vs. 1.47 ± 0.11 m·s, r = 0.98, 95% LoA: -0.05 to 0.05 m·s). Instead, the AT HR and velocity obtained from HFPOW (179.2 ± 8.4 b·min; 1.45 ± 0.11 m·s) were correlated to the corresponding parameters determined from [La] (HR: r = 0.84; velocity: r = 0.94) but underestimated them slightly (95% LoA: -11.9 to 6.3 b·min and -0.11 to 0.05 m·s). These results demonstrate that the AT can be assessed from the HRV in swimming, providing an important testing tool for coaches. Furthermore, using the actual respiratory spectral component, rather than the total HF spectral power, allows us to obtain a more accurate estimate of AT parameters.

Second ventilatory threshold from heart-rate variability: valid when the upper body is involved?

To determine the most accurate method based on spectral analysis of heart-rate variability (SA-HRV) during an incremental and continuous maximal test involving the upper body, the authors tested 4 different methods to obtain the heart rate (HR) at the second ventilatory threshold (VT(2)). Sixteen ski mountaineers (mean ± SD; age 25 ± 3 y, height 177 ± 8 cm, mass 69 ± 10 kg) performed a roller-ski test on a treadmill. Respiratory variables and HR were continuously recorded, and the 4 SA-HRV methods were compared with the gas-exchange method through Bland and Altman analyses. The best method was the one based on a time-varying spectral analysis with high frequency ranging from 0.15 Hz to a cutoff point relative to the individual's respiratory sinus arrhythmia. The HR values were significantly correlated (r(2) = .903), with a mean HR difference with the respiratory method of 0.1 ± 3.0 beats/min and low limits of agreements (around -6 /+6 beats/min). The 3 other methods led to larger errors and lower agreements (up to 5 beats/min and around -23/+20 beats/min). It is possible to accurately determine VT(2) with an HR monitor during an incremental test involving the upper body if the appropriate HRV method is used.

Mitigating the effect of non-stationarity in spectral analysis-an application to neonate heart rate analysis

In order to mitigate the effect of non-stationarity in frequency domain analysis of data, we propose a modification to the power spectral estimation, a widely used technique to characterize physiological signals. Spectral analysis requires partitioning data into smaller epochs determined by the desired frequency resolution. The modified approach proposed here involves dividing the data within each epoch by the standard deviation of the data for that epoch. We applied this modified approach to cardiac beat-to-beat interval data recorded from a newborn infant undergoing hypothermia treatment for birth asphyxia. The critically ill infant had episodes of tachyarrhythmia, distributed sporadically throughout the study, which affected the stationarity of the heart rate. Over the period of continuous heart rate recording, the infant's clinical course deteriorated progressively culminating in death. Coinciding with this clinical deterioration, the heart rate signal showed striking changes in both low-frequency and high-frequency power indicating significant impairment of the autonomic nervous system. The standard spectral approach failed to capture these phenomena because of the non-stationarity of the signal. Conversely, the modified approach proposed here captured the deteriorating physiology of the infant clearly.

Heart rate variability reproducibility during exercise

The use of heart rate variability (HRV) parameters during exercise is not supported by appropriate reliability studies. In 80 healthy adults, ECG was recorded during three 6 min bouts of exercise, separated by 6 min of unloaded cycling. Two bouts were at a moderate intensity while the final bout was at a heavy exercise intensity. This protocol was repeated under the same conditions on three occasions, with a controlled start time (pre-determined at the first visit). Standard time and frequency domain indices of HRV were derived. Reliability was assessed by Bland–Altman plots, 95% limits of agreement and intraclass correlation coefficients (ICC). The sample size required to detect a mean difference ≥30% of the between-subject standard deviation was also estimated. There was no systematic change between days. All HRV parameters demonstrated a high degree of reproducibility during baseline (ICC range: 0.58–0.75), moderate (ICC: 0.58–0.85) and heavy intensity exercise (ICC range: 0.40–0.76). The reproducibility was slightly diminished during heavy intensity exercise relative to both unloaded baseline cycling and moderate exercise. This study indicates that HRV parameters can be reliably determined during exercise, and it underlines the importance of standardizing exercise intensity with regard to fitness levels if HRV is to be reliably determined.

Relationship between changes in pulmonary V̇O₂ kinetics and autonomic regulation of blood flow

Various regulatory mechanisms of pulmonary oxygen uptake (V̇O2) kinetics have been postulated. The purpose of this study was to investigate the relationship between vagal withdrawal, measured using RMSSDRR, the root mean square of successive differences in cardiac interval (RR) kinetics, a mediator of oxygen delivery, and V̇O2 kinetics. Forty-nine healthy adults (23 ± 3 years; 72 ± 13 kg; 1.80 ± 0.08 m) performed multiple repeat transitions to moderate- and heavy-intensity exercise. Electrocardiography, impedance cardiography, and pulmonary gas exchange parameters were measured throughout; time domain measures of heart rate variability were subsequently derived. The parameters describing the dynamic response of V̇O2, cardiac output (Q) and RMSSDRR were determined using a mono-exponential model. During heavy-intensity exercise, the phase II τ of V̇O2 was significantly correlated with the τ of RR (r = 0.36, P < 0.05), Q (r = 0.67, P < 0.05), and RMSSDRR (r = 0.38, P < 0.05). The τ describing the rise in Q explained 47% of the variation in V̇O2 τ, with 30% of the rate of this rise in Q explained by the τ of RR and RMSSDRR. No relationship was evident between V̇O2 kinetics and those of Q, RR, or RMSSDRR during moderate exercise. Vagal withdrawal kinetics support the concept of a centrally mediated oxygen delivery limitation partly regulating V̇O2 kinetics during heavy-, but not moderate-, intensity exercise.

Pedaling time variability is increased in dropped riding position

Variability of cycle-to-cycle duration during a pedaling task is probably related to the rhythmic control of the lower limb muscles as in gait. Although walking variability has been extensively studied for its clinical and physiological implications, pedaling variability has received little attention. The present contribution determines the variability of the cycling time during a 10-min exercise as a function of upper body position. Nine healthy males were required to pedal on cycle-ergometer at a self-selected speed for 10 min in two different upper body positions [hands on upper handlebars (UP) or lower handlebars (DP)]. Time domain measures of cycling variability [total standard deviation (SDtot), mean standard deviation cycle-to-cycle intervals over 100 cycles (SD100), standard deviation of the average cycle-to-cycle intervals over 100 cycles (SDA100)] were measured. Moreover, the same time domain measures were also calculated for heart rate in order to discriminate possible involvements of autonomic regulation. Finally, the structure of the cycle variations has been analyzed in the framework of deterministic chaos calculating the maximum Lyapunov exponents. Significant increases in cycle-to-cycle variability were found for SDtot, SD100 in DP compared to UP, whereas cardiac parameters and other cycling parameters were not changed in the two positions. Moreover, the maximum Lyapunov exponent was significantly more negative in DP. The results suggest that small perturbations of upper body position can influence the control of cycling rhythmicity by increasing the variability in a dissipative deterministic regimen.

Cycling cadence affects heart rate variability

The purpose of this study was to examine the effect different cycling cadences have on heart rate variability (HRV) when exercising at constant power outputs. Sixteen males had ECG and respiratory measurements recorded at rest and during 8, 10 min periods of cycling at four different cadences (40, 60, 80 and 100 revs min(-1)) and two power outputs (0 W (unloaded) and 100 W (loaded)). The cycling periods were performed following a Latin square design. Spectral analyses of R-R intervals by fast Fourier transforms were used to quantify absolute frequency domain HRV indices (ms(2)) during the final 5 min of each bout, which were then log transformed using the natural logarithm (Ln). HRV indices of high frequency (HF) power were reduced when cadence was increased (during unloaded cycling (0 W) log transformed HF power decreased from a mean [SD] of 6.3 [1.4] Ln ms(2) at 40 revs min(-1) to 3.9 [1.3] Ln ms(2) at 100 revs min(-1)). During loaded cycling (at 100 W), the low to high frequency (LF:HF) ratio formed a 'J' shaped curve as cadence increased from 40 revs min(-1) (1.4 [0.4]) to 100 revs min(-1) (1.9 [0.7]), but dipped below the 40 revs min(-1) values during the 60 revs min(-1) 1.1 (0.3) and 80 revs min(-1) 1.2 (0.6) cadence conditions. Cardiac frequency (f(C)) and ventilatory variables were strongly correlated with frequency domain HRV indices (r = -0.80 to -0.95). It is concluded that HRV indices are influenced by both cycling cadence and power output; this is mediated by the f(C) and ventilatory changes that occur as cadence or exercise intensity is increased. Consequently, if HRV is assessed during exercise, both power output/exercise intensity and cadence should be standardized.

The integral pulse frequency modulation model with time-varying threshold: application to heart rate variability analysis during exercise stress testing

In this paper, an approach for heart rate variability analysis during exercise stress testing is proposed based on the integral pulse frequency modulation (IPFM) model, where a time-varying threshold is included to account for the nonstationary mean heart rate. The proposed technique allows the estimation of the autonomic nervous system (ANS) modulating signal using the methods derived for the IPFM model with constant threshold plus a correction, which is shown to be needed to take into account the time-varying mean heart rate. On simulations, this technique allows the estimation of the ANS modulation on the heart from the beat occurrence time series with lower errors than the IPFM model with constant threshold (1.1% ± 1.3% versus 15.0% ± 14.9%). On an exercise stress testing database, the ANS modulation estimated by the proposed technique is closer to physiology than that obtained from the IPFM model with constant threshold, which tends to overestimate the ANS modulation during the recovery and underestimate it during the initial rest.

Analysis and processing of heart rate variability by time-frequency representation: quantification of the pedaling frequency modulation

It has been shown that a pedaling frequency component can be extracted from the heart rate variability (HRV) signal using a time-varying filter. It is shown that this filter can be implemented directly in the time-frequency plane with different approaches. The need of resampling the data is also discussed with regard to the artifacts produced when the shanon condition is not fulfilled. In order to interpret the similar amplitude profiles of the pedaling component for untrained and trained subjects, an attempt for the model parameters setting is proposed. Consistent results on a large data set illustrate the feasibility of such processing.