Heart rate variability in non-apneic snorers and controls before and after continuous positive airway pressure

Effect of virtual reality-simulated exercise on sympathovagal balance

Discovery of therapeutic avenues to provide the benefits of exercise to patients with enforced sedentary behavior patterns would be of transformative importance to health care. Work in model organisms has demonstrated that benefits of exercise can be provided to stationary animals by daily intermittent stimulation of adrenergic signaling. Here, we examine as a proof of principle whether exposure of human participants to virtual reality (VR) simulation of exercise can alter sympathovagal balance in stationary humans. In this study, 24 participants performed 15 minutes of cycling exercise at standardized resistance, then repeated the exercise with a virtual reality helmet that provided an immersive environment. On a separate day, they each controlled a virtual environment for 15 minutes to simulate exercise without actual cycling exercise. Response to each treatment was assessed by measuring heart rate (HR), norepinephrine, and heart rate variability, and each participant's response to virtual exercise was compared internally to his/her response to the actual cycling. We found that neither post-exercise norepinephrine nor post-exercise HR was significantly increased by VR simulation. However, heart rate variability measured during virtual exercise was comparable to actual cycling in participants that engaged in moderate exercise, but not in those that engaged in high-intensity exercise. These findings suggest that virtual exercise has the potential to mimic some effects of moderate exercise. Further work will be needed to examine the longitudinal effects of chronic exposure to VR-simulated exercise.

Association between snoring and heart rate variability in adolescents: effects of gender and insufficient sleep

PURPOSE

We explored the association between subjective snoring frequency and heart rate variability (HRV) in a healthy adolescent population.

METHODS

A total of 102 healthy adolescents were recruited from high schools in South Korea, and reported their sleep habits and snoring frequency. HRV was assessed to indirectly measure autonomic function. We assessed correlations between snoring frequency and HRV indices. We also investigated the effects of sex and behaviorally induced insufficient sleep syndrome (BISS) on the associations between HRV parameters and snoring frequency.

RESULTS

Overall, significant correlations were apparent between snoring frequency and HRV indices including the standard deviation of the normal-to-normal intervals (SDNN) and the low-frequency/high-frequency (LF/HF) ratio. Associations were more evident in males and those with BISS compared to females and those without BISS.

CONCLUSIONS

Our findings suggest that snoring changes autonomic nervous system (ANS) activity in adolescents; the changes are more dramatic in males and those with insufficient sleep.

Support vector machines for automated snoring detection: proof-of-concept

BACKGROUND

Snoring has been shown to be associated with adverse physical and mental health, independent of the effects of sleep disordered breathing. Despite increasing evidence for the risks of snoring, few studies on sleep and health include objective measures of snoring. One reason for this methodological limitation is the difficulty of quantifying snoring. Conventional methods may rely on manual scoring of snore events by trained human scorers, but this process is both time- and labor-intensive, making the measurement of objective snoring impractical for large or multi-night studies.

METHODS

The current study is a proof-of-concept to validate the use of support vector machines (SVM), a form of machine learning, for the automated scoring of an objective snoring signal. An SVM algorithm was trained and tested on a set of approximately 150,000 snoring and non-snoring data segments, and F-scores for SVM performance compared to visual scoring performance were calculated using the Wilcoxon signed rank test for paired data.

RESULTS

The ability of the SVM algorithm to discriminate snore from non-snore segments of data did not differ statistically from visual scorer performance (SVM F-score = 82.46 ± 7.93 versus average visual F-score = 88.35 ± 4.61, p = 0.2786), supporting SVM snore classification ability comparable to visual scorers.

CONCLUSION

In this proof-of-concept, we established that the SVM algorithm performs comparably to trained visual scorers, supporting the use of SVM for automated snoring detection in future studies.

Intermittent hypoxia: a low-risk research tool with therapeutic value in humans

Intermittent hypoxia has generally been perceived as a high-risk stimulus, particularly in the field of sleep medicine, because it is thought to initiate detrimental cardiovascular, respiratory, cognitive, and metabolic outcomes. In contrast, the link between intermittent hypoxia and beneficial outcomes has received less attention, perhaps because it is not universally understood that outcome measures following exposure to intermittent hypoxia may be linked to the administered dose. The present review is designed to emphasize the less recognized beneficial outcomes associated with intermittent hypoxia. The review will consider the role intermittent hypoxia has in cardiovascular and autonomic adaptations, respiratory motor plasticity, and cognitive function. Each section will highlight the literature that contributed to the belief that intermittent hypoxia leads primarily to detrimental outcomes. The second segment of each section will consider the possible risks associated with experimentally rather than naturally induced intermittent hypoxia. Finally, the body of literature indicating that intermittent hypoxia initiates primarily beneficial outcomes will be considered. The overarching theme of the review is that the use of intermittent hypoxia in research investigations, coupled with reasonable safeguards, should be encouraged because of the potential benefits linked to the administration of a variety of low-risk intermittent hypoxia protocols.

Heart rate variability evaluation of Emfit sleep mattress breathing categories in NREM sleep

OBJECTIVE

Heart rate variability (HRV) analysis of obstructive sleep apnea patients reveals an increase in sympathetic activity. Sleep disordered breathing (SDB) can be also assessed with sleep mattress sensors, as the Emfit sensor, by dividing the signal into different breathing categories. In addition to normal breathing (NB) and periodic apneas/hypopneas (POB), the sleep mattress unveils a breathing category consisting of sustained partial obstruction (increased respiratory resistance, IRR). The aim of our study was to evaluate HRV during these three breathing categories in NREM sleep.

METHODS

53 patients with suspected SDB underwent an overnight polysomnography with an Emfit mattress. The Emfit signal was scored in 3-min epochs according to the established rules. The NB, POB, and IRR epochs were combined to as long NB, POB and IRR periods as possible and HRV was calculated from at least 6-min epochs.

RESULTS

The meanHR did not differ between the breathing categories. HRV parameters revealed an increase in sympathetic activity during POB. The mean LF/HF ratio was highest during POB (3.0) and lowest during IRR (1.3). During NB it was 1.7 (all p-values ⩽ 0.001). Interestingly sympathetic activity decreased and parasympathetic activity increased during IRR as compared to NB (the mean HF power was 1113.8 ms(2) during IRR and 928.4 ms(2) during NB).

CONCLUSIONS

The HRV findings during POB resembled HRV results of sleep apnea patients but during sustained prolonged partial obstruction a shift towards parasympathetic activity was achieved.

SIGNIFICANCE

The findings encourage the use of sleep mattresses in SDB diagnostics. In addition the findings suggest that sustained partial obstruction represents its own SDB entity.

Simple snoring: not quite so simple after all?

Simple snoring (SS), in the absence of obstructive sleep apnoea (OSA), is a common problem, yet our understanding of its causes and consequences is incomplete. Our understanding is blurred by the lack of consistency in the definition of snoring, methods of assessment, and degree of concomitant complaints. Further, it remains contentious whether SS is independently associated with daytime sleepiness, or adverse health outcomes including cardiovascular disease and metabolic syndrome. Regardless of this lack of clarity, it is likely that SS exists on one end of a continuum, with OSA at its polar end. This possibility highlights the necessity of considering an otherwise 'annoying' complaint, as a serious risk factor for the development and progression of sleep apnoea, and consequent poor health outcomes. In this review, we: 1) highlight variation in prevalence estimates of snoring; 2) review the literature surrounding the distinctions between SS, upper airway resistance syndrome (UARS) and OSA; 3) present the risk factors for SS, in as far as it is distinguishable from UARS and OSA; and 4) describe common correlates of snoring, including cardiovascular disease, metabolic syndrome, and daytime sleepiness.

Increased sympathetic and decreased parasympathetic cardiac tone in patients with sleep related alveolar hypoventilation

OBJECTIVE

To assess autonomic function by heart rate variability (HRV) during sleep in patients with sleep related alveolar hypoventilation (SRAH) and to compare it with that of patients with obstructive sleep apnea (OSA) and control patients.

DESIGN

Cross-sectional study.

SETTING

Sleep Unit, University Hospital of University of Navarra.

PATIENTS

Fifteen idiopathic and obesity related-SRAH patients were studied. For each patient with SRAH, a patient with OSA, matched in age, sex, body mass index (BMI), minimal oxygen saturation (SatO2), and mean SatO2 was selected. Control patients were also matched in age, sex, and BMI with patients with OSA and those with SRAH, and in apnea/hypopnea index (AHI) with patients with SRAH.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

Time- and frequency-domain HRV measures (R-R, standard deviation of normal-to-normal RR interval [SDNN], very low frequency [VLF], low frequency [LF], high frequency [HF], LF/HF ratio) were calculated across all sleep stages as well as during wakefulness just before and after sleep during a 1-night polysomnography. In patients with SRAH and OSA, LF was increased during rapid eye movement (REM) when compared with control patients, whereas HF was decreased during REM and N1-N2 sleep stages. The LF/HF ratio was equally increased in patients with SRAH and OSA during REM and N1-N2. Correlation analysis showed that LF and HF values during REM sleep were correlated with minimal SatO2 and mean SatO2.

CONCLUSIONS

Patients with SRAH exhibited an abnormal cardiac tone during sleep. This fact appears to be related to the severity of nocturnal oxygen desaturation. Moreover, there were no differences between OSA and SRAH, supporting the hypothesis that autonomic changes in OSA are primarily related to a reduced nocturnal oxygen saturation, rather than a consequence of other factors such as nocturnal respiratory events.

Changes in the heart rate variability in patients with obstructive sleep apnea and its response to acute CPAP treatment

Introduction

Obstructive Sleep Apnea (OSA) is a major risk factor for cardiovascular disease. The goal of this study was to demonstrate whether the use of CPAP produces significant changes in the heart rate or in the heart rate variability of patients with OSA in the first night of treatment and whether gender and obesity play a role in these differences.

Methods

Single-center transversal study including patients with severe OSA corrected with CPAP. Only patients with total correction after CPAP were included. Patients underwent two sleep studies on consecutive nights: the first night a basal study, and the second with CPAP. We also analyzed the heart rate changes and their relationship with CPAP treatment, sleep stages, sex and body mass index. Twenty-minute segments of the ECG were selected from the sleep periods of REM, no-REM and awake. Heart rate (HR) and heart rate variability (HRV) were studied by comparing the R-R interval in the different conditions. We also compared samples from the basal study and CPAP nights.

Results

39 patients (15 females, 24 males) were studied. The mean age was 50.67 years old, the mean AHI was 48.54, and mean body mass index was 33.41 kg/m² (31.83 males, 35.95 females). Our results showed that HRV (SDNN) decreased after the use of CPAP during the first night of treatment, especially in non-REM sleep. Gender and obesity did not have any influence on our results.

Conclusions

These findings support that cardiac variability improves as an acute effect, independently of gender or weight, in the first night of CPAP use in severe OSA patients, supporting the idea of continuous use and emphasizing that noncompliance of CPAP treatment should be avoided even if it is just once.

Heart rate variability: a review

Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.

Heart rate variability: a review

Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.

Heart rate variability: a review

Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.