Obstructive sleep apnea heterogeneity and autonomic function: a role for heart rate variability in therapy selection and efficacy monitoring.

Obstructive sleep apnea is a highly prevalent sleep-related breathing disorder, resulting in a disturbed breathing pattern, changes in blood gases, abnormal autonomic regulation, metabolic fluctuation, poor neurocognitive performance, and increased cardiovascular risk. With broad inter-individual differences recognised in risk factors, clinical symptoms, gene expression, physiological characteristics, and health outcomes, various obstructive sleep apnea subtypes have been identified. Therapeutic efficacy and its impact on outcomes, particularly for cardiovascular consequences, may also vary depending on these features in obstructive sleep apnea. A number of interventions such as positive airway pressure therapies, oral appliance, surgical treatment, and pharmaceutical options are available in clinical practice. Selecting an effective obstructive sleep apnea treatment and therapy is a challenging medical decision due to obstructive sleep apnea heterogeneity and numerous treatment modalities. Thus, an objective marker for clinical evaluation is warranted to estimate the treatment response in patients with obstructive sleep apnea. Currently, while the Apnea-Hypopnea Index is used for severity assessment of obstructive sleep apnea and still considered a major guide to diagnosis and managements of obstructive sleep apnea, the Apnea-Hypopnea Index is not a robust marker of symptoms, function, or outcome improvement. Abnormal cardiac autonomic modulation can provide additional insight to better understand obstructive sleep apnea phenotyping. Heart rate variability is a reliable neurocardiac tool to assess altered autonomic function and can also provide cardiovascular information in obstructive sleep apnea. Beyond the Apnea-Hypopnea Index, this review aims to discuss the role of heart rate variability as an indicator and predictor of therapeutic efficacy to different modalities in order to optimise tailored treatment for obstructive sleep apnea.

Phrenic nerve stimulation for the treatment of central sleep apnea in patients with heart failure.

OBJECTIVE: Central sleep apnea (CSA) is associated with increased morbidity and mortality in patients with heart failure (HF). We aimed to explore the effectiveness of phrenic nerve stimulation (PNS) on CSA in patients with HF. METHODS: This was a prospective and non-randomized study. The stimulation lead was inserted into the right brachiocephalic vein and attached to a proprietary neurostimulator. Monitoring was conducted during the implantation process, and all individuals underwent two-night polysomnography. RESULTS: A total of nine subjects with HF and CSA were enrolled in our center. There was a significant decrease in the apnea-hypopnea index (41 ± 18 vs 29 ± 25, p = 0.02) and an increase in mean arterial oxygen saturation (SaO2) (93% ± 1% vs 95% ± 2%, p = 0.03) after PNS treatment. We did not observe any significant differences of oxygen desaturation index (ODI) and SaO2 < 90% (T90) following PNS. Unilateral phrenic nerve stimulation might also categorically improve the severity of sleep apnea. CONCLUSION: In our non-randomized study, PNS may serve as a therapeutic approach for CSA in patients with HF.

ECG and Heart Rate Variability in Sleep-Related Breathing Disorders.

Here we discuss the current perspectives of comprehensive heart rate variability (HRV) analysis in electrocardiogram (ECG) signals as a non-invasive and reliable measure to assess autonomic function in sleep-related breathing disorders (SDB). It is a tool of increasing interest as different facets of HRV can be implemented to screen and diagnose SDB, monitor treatment efficacy, and prognose adverse cardiovascular outcomes in patients with sleep apnea. In this context, the technical aspects, pathophysiological features, and clinical applications of HRV are discussed to explore its usefulness in better understanding SDB.

Transportation noise impairs cardiovascular function without altering sleep: The importance of autonomic arousals.

AIMS: Chronic exposure to nocturnal transportation noise has been linked to cardiovascular disorders with sleep impairment as the main mediator. Here we examined whether nocturnal transportation noise affects the main stress pathways, and whether it relates to changes in the macro and micro structure of sleep. METHODS AND RESULTS: Twenty-six young healthy participants (12 women, 24.6 ± 0.7 years, mean ± SE) spent five consecutive 24-h days and one last morning in the laboratory. The first (baseline) and last (recovery) nights comprised a quiet ambient scenario. In-between, four different noise scenarios (low/medium/high intermittent road or rail scenarios with an identical equivalent continuous sound level of 45 dB) were randomly presented during the 8-h nights. Participants felt more annoyed from the transportation noise scenarios compared to the quiet ambient scenario played back during the baseline and recovery nights (F5,117 = 10.2, p < 0.001). Nocturnal transportation noise did not significantly impact polysomnographically assessed sleep macrostructure, blood pressure, nocturnal catecholamine levels and morning cytokine levels. Evening cortisol levels increased after sleeping with highly intermittent road noise compared to baseline (p = 0.002, noise effect: F4,83 = 4.0, p = 0.005), a result related to increased cumulative duration of autonomic arousals during the noise nights (F5,106 = 3.4, p < 0.001; correlation: rpearson = 0.64, p = 0.006). CONCLUSION: Under controlled laboratory conditions, highly intermittent nocturnal road noise exposure at 45 dB increased the cumulative duration of autonomic arousals during sleep and next-day evening cortisol levels. Our results indicate that, without impairing sleep macrostructure, nocturnal transportation noise of 45 dB is a physiological stressor that affects the hypothalamic-pituitary-adrenal axis during the following day in healthy young good sleepers.

Is dynamic desaturation better than a static index to quantify the mortality risk in heart failure patients with Cheyne-Stokes respiration?

Cheyne-Stokes respiration (CSR) is a periodic, highly dynamic, respiratory pattern and a known comorbidity in congestive heart failure (CHF) patients. It is generally seen as an indicator for a negative prognosis, even if no distinction in degree is known or understood. This paper aims to improve on existing attempts by creating a quantification of the behavior of the dynamic desaturation process of oxygen in the blood. We performed this work on a cohort of 11 subjects with CHF, reduced left ventricular ejection fraction, and CSR. The dynamic desaturation process was evaluated according to changes to peripheral capillary oxygenation S p O 2 resulting from highly nonlinear relationships in the ventilatory system perturbed by periodic breathing. Hypoxaemic burden expressed as a static index T 90 was compared to a novel relative desaturation index R D I , developed in this paper. While T 90 represents a single value calculated using a static cut-off value of 90 % S p O 2 , the R D I is more sensitive to dynamic influences as it uses the specific maximum change in saturation for each CSR episode. The threshold of T 90 = 22 min per night as suggested by Oldenburg et al. could not be confirmed to predict survival, but all central apneas resulting in a relative desaturation of S p O 2 above a cut-off value of 8 % were a 100 % positive predictor of mortality. The R D I proved sufficiently stable in intraindividual measurements across CSR epochs. Across the cohort, it showed a bimodal distribution for the deceased group, indicative of a possible aetiological difference. Hence, it is our conclusion that a dynamic approach to analyse desaturation of oxygen during Cheyne-Stokes respiration is to be strongly favoured over a static approach to analysis.

On the difference of cardiorespiratory synchronisation and coordination.

Cardiorespiratory phase synchronisation (CRS) is a type of cardiorespiratory coupling that manifests through a prediliction for heart beats to occur at specific points relative to the phase of the respiratory cycle. It has been under investigation for nearly 20 years, and while it seems to be mostly occurring in relaxed states such as deep sleep and anesthesia, no clear clinical implications have been established. Cardiorespiratory coordination (CRC) is a recent development in this field where the relationship between the respiratory onset and heart beat is analysed in the time domain and the possible relationship of each heart beat is considered for both the previous and the next respiratory onset. This ostensibly closely related effect must not only show relevant information content but also do so independent of CRS in order to be relevant for future studies. In this paper, we investigate CRC and its relation to CRS mainly using graphical and statistical methods on two exemplary datasets: measurements from a pregnant woman participating in a preeclampsia study and those from a man suffering from sleep apnea. We show fundamental differences between the results of both approaches and are able to show a formerly unknown dependency between the heart activity and respiratory rate, potentially indicating heartbeat-initiated inspiration. Despite their differences, methods developed for the quantification of CRS can be adapted to CRC. Completing the comparison is an investigation into the relationship between CRC and respiratory sinus arrhythmia. Similar to previous results for CRS, the two effects are found to be orthogonal, meaning that they can be observed independently or in conjunction.

Effect of phrenic nerve stimulation on patients with central sleep apnea: A meta-analysis.

Patients with central sleep apnea (CSA) have a lower quality of life and higher morbidity and mortality. Phrenic nerve stimulation (PNS) is a novel treatment for CSA that has been shown to be safe. However, the effects of PNS on sleep changes are still under debate. This meta-analysis was performed to evaluate the efficacy of PNS in patients with CSA. PubMed, Scopus, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL) and Web of Science databases were searched for relevant studies published. We performed random-effects meta-analyses of the changes in apnea-hypopnea index (AHI), central apnea index (CAI), Arousal Index, percent of sleep with O2 saturation <90% (T90), Epworth Sleepiness Scale (ESS) and sleep efficiency. Ten studies with a total of 580 subjects were analyzed. Overall meta-analysis showed AHI [SMD: -2.24, 95% confidence interval (CI): was -3.11 to -1.36(p＜0.00001)], CAI [SMD: -2.32, 95% CI: -3.17 to -1.47 (p＜0.00001)] and Arousal Index (p = 0.0002, SMD (95% CI) -1.79 (-2.74 to -0.85)) significantly reduced after PNS. No significant changes were observed in T90, ESS and sleep efficiency (p > 0.05). Meta-analysis of observational studies demonstrated AHI, CAI and Arousal Index had a decreasing trend between before and after PNS (all, p＜0.05). However, ESS and T90 did not change significantly after PNS (p > 0.05). Meta-analysis of RCTs showed that CSA patients had trends of a lower AHI (I2 = 0%), CAI (I2 = 74%), Arousal Index (I2 = 0%), T90 (I2 = 0%) and ESS (I2 = 0%) after PNS (all, p＜0.05). The use of PNS appears to be safe and feasible in patients with CSA. However, larger, independent RCTs are required to investigate the efficacy and long-term effect of PNS and more attention should be paid to T90 and ESS.

The Different Facets of Heart Rate Variability in Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA), a heterogeneous and multifactorial sleep related breathing disorder with high prevalence, is a recognized risk factor for cardiovascular morbidity and mortality. Autonomic dysfunction leads to adverse cardiovascular outcomes in diverse pathways. Heart rate is a complex physiological process involving neurovisceral networks and relative regulatory mechanisms such as thermoregulation, renin-angiotensin-aldosterone mechanisms, and metabolic mechanisms. Heart rate variability (HRV) is considered as a reliable and non-invasive measure of autonomic modulation response and adaptation to endogenous and exogenous stimuli. HRV measures may add a new dimension to help understand the interplay between cardiac and nervous system involvement in OSA. The aim of this review is to introduce the various applications of HRV in different aspects of OSA to examine the impaired neuro-cardiac modulation. More specifically, the topics covered include: HRV time windows, sleep staging, arousal, sleepiness, hypoxia, mental illness, and mortality and morbidity. All of these aspects show pathways in the clinical implementation of HRV to screen, diagnose, classify, and predict patients as a reasonable and more convenient alternative to current measures.

Automatic Sleep Staging in Children with Sleep Apnea using Photoplethysmography and Convolutional Neural Networks.

Sleep staging is of paramount importance in children with suspicion of pediatric obstructive sleep apnea (OSA). Complexity, cost, and intrusiveness of overnight polysomnography (PSG), the gold standard, have led to the search for alternative tests. In this sense, the photoplethysmography signal (PPG) carries useful information about the autonomous nervous activity associated to sleep stages and can be easily acquired in pediatric sleep apnea home tests with a pulse oximeter. In this study, we use the PPG signal along with convolutional neural networks (CNN), a deep-learning technique, for the automatic identification of the three main levels of sleep: wake (W), rapid eye movement (REM), and non-REM sleep. A database of 366 PPG recordings from pediatric OSA patients is involved in the study. A CNN architecture was trained using 30-s epochs from the PPG signal for three-stage sleep classification. This model showed a promising diagnostic performance in an independent test set, with 78.2% accuracy and 0.57 Cohen's kappa for W/NREM/REM classification. Furthermore, the percentage of time in wake stage obtained for each subject showed no statistically significant differences with the manually scored from PSG. These results were superior to the only state-of-the-art study focused on the analysis of the PPG signal in the automated detection of sleep stages in children suffering from OSA. This suggests that CNN can be used along with PPG recordings for sleep stages scoring in pediatric home sleep apnea tests.

Heart rate variability during wakefulness as a marker of obstructive sleep apnea severity.

STUDY OBJECTIVES: Patients with obstructive sleep apnea (OSA) exhibit heterogeneous heart rate variability (HRV) during wakefulness and sleep. We investigated the influence of OSA severity on HRV parameters during wakefulness in a large international clinical sample. METHODS: 1247 subjects (426 without OSA and 821 patients with OSA) were enrolled from the Sleep Apnea Global Interdisciplinary Consortium. HRV parameters were calculated during a 5-minute wakefulness period with spontaneous breathing prior to the sleep study, using time-domain, frequency-domain and nonlinear methods. Differences in HRV were evaluated among groups using analysis of covariance, controlling for relevant covariates. RESULTS: Patients with OSA showed significantly lower time-domain variations and less complexity of heartbeats compared to individuals without OSA. Those with severe OSA had remarkably reduced HRV compared to all other groups. Compared to non-OSA patients, those with severe OSA had lower HRV based on SDNN (adjusted mean: 37.4 vs. 46.2 ms; p < 0.0001), RMSSD (21.5 vs. 27.9 ms; p < 0.0001), ShanEn (1.83 vs. 2.01; p < 0.0001), and Forbword (36.7 vs. 33.0; p = 0.0001). While no differences were found in frequency-domain measures overall, among obese patients there was a shift to sympathetic dominance in severe OSA, with a higher LF/HF ratio compared to obese non-OSA patients (4.2 vs. 2.7; p = 0.009). CONCLUSIONS: Time-domain and nonlinear HRV measures during wakefulness are associated with OSA severity, with severe patients having remarkably reduced and less complex HRV. Frequency-domain measures show a shift to sympathetic dominance only in obese OSA patients. Thus, HRV during wakefulness could provide additional information about cardiovascular physiology in OSA patients. CLINICAL TRIAL INFORMATION: A Prospective Observational Cohort to Study the Genetics of Obstructive Sleep Apnea and Associated Co-Morbidities (German Clinical Trials Register - DKRS, DRKS00003966) https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00003966.

Instantaneous Cardiac Baroreflex Sensitivity: xBRS Method Quantifies Heart Rate Blood Pressure Variability Ratio at Rest and During Slow Breathing.

Spontaneous baroreflex sensitivity (BRS) is a widely used tool for the quantification of the cardiovascular regulation. Numerous groups use the xBRS method, which calculates the cross-correlation between the systolic beat-to-beat blood pressure and the R-R interval (resampled at 1 Hz) in a 10 s sliding window, with 0-5 s delays for the interval. The delay with the highest correlation is selected and, if significant, the quotient of the standard deviations of the R-R intervals and the systolic blood pressures is recorded as the corresponding xBRS value. In this paper we test the hypothesis that the xBRS method quantifies the causal interactions of spontaneous BRS from non-invasive measurements at rest. We use the term spontaneous BRS in the sense of the sensitivity curve is calculated from non-interventional, i.e., spontaneous, baroreceptor activity. This study includes retrospective analysis of 1828 measurements containing ECG as well as continues blood pressure under resting conditions. Our results show a high correlation between the heart rate - systolic blood pressure variability (HRV/BPV) quotient and the xBRS (r = 0.94, p < 0.001). For a deeper understanding we conducted two surrogate analyses by substituting the systolic blood pressure by its reversed time series. These showed that the xBRS method was not able to quantify causal relationships between the two signals. It was not possible to distinguish between random and baroreflex controlled sequences. It appears xBRS rather determines the HRV/BPV quotient. We conclude that the xBRS method has a potentially large bias in characterizing the capacity of the arterial baroreflex under resting conditions. During slow breathing, estimates for xBRS are significantly increased, which clearly shows that measurements at rest only involve limited baroreflex activity, but does neither challenge, nor show the full range of the arterial baroreflex regulatory capacity. We show that xBRS is exclusively dominated by the heart rate to systolic blood pressure ratio (r = 0.965, p < 0.001). Further investigations should focus on additional autonomous testing procedures such as slow breathing or orthostatic testing to provide a basis for a non-invasive evaluation of baroreflex sensitivity.

Cardiac Autonomic Dysfunction and Incidence of de novo Atrial Fibrillation: Heart Rate Variability vs. Heart Rate Complexity.

BACKGROUND: The REACT DX registry evaluates standard therapies to episodes of long-lasting atrial tachyarrhythmias and assesses the quality of sensing and stability of the lead and the implantable cardioverter-defibrillator (ICD) (BIOTRONIK Lumax VR-T DX and successors) over at least a 1-year follow-up period. OBJECTIVE: To study the association between the risk of de novo device-detected atrial fibrillation (AF), the autonomic perturbations before the onset of paroxysmal AF and a 7-days heart rate variability (7dHRV) 1 month after ICD implantation. METHODS: The registry consists of 234 patients implanted with an ICD, including 10 with de novo long-lasting atrial tachyarrhythmias with no prior history of AF. The patients were matched via the propensity-score methodology as well as for properties directly influencing the ECGs recorded using GE CardioMem CM 3000. Heart rate variability (HRV) analysis was performed using standard parameters from time- and frequency-domains, and from non-linear dynamics. RESULTS: No linear HRV was associated with an increased risk of AF (p = n.s.). The only significant approach was derived from symbolic dynamics with the parameter "forbidden words" which distinguished both groups on all 7 days of measurements (p < 0.05), thereby quantifying the heart rate complexity (HRC) as drastically lower in the de novo AF group. CONCLUSION: Cardiac autonomic dysfunction denoted by low HRC may be associated with higher AF incidence. For patients with mild to moderate heart failure, standard HRV parameters are not appropriate to quantify cardiac autonomic perturbations before the onset of AF. Further studies are needed to determine the individual risk for AF that would enable interventions to restore autonomic balance in the general population.

Screening for Obstructive Sleep Apnea in Commercial Drivers Using EKG-Derived Respiratory Power Index.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is common in commercial motor vehicle operators (CMVOs); however, polysomnography (PSG), the gold-standard diagnostic test, is expensive and inconvenient for screening. OSA is associated with changes in heart rate and voltage on electrocardiography (EKG). We evaluated the utility of EKG parameters in identifying CMVOs at greater risk for sleepiness-related crashes (apnea-hypopnea index [AHI] ≥ 30 events/h). METHODS: In this prospective study of CMVOs, we performed EKGs with concurrent PSG, and calculated the respiratory power index (RPI) on EKG, a surrogate for AHI calculated from PSG. We evaluated the utility of two-stage predictive models using simple clinical measures (age, body mass index [BMI], neck circumference, Epworth Sleepiness Scale score, and the Multi-Variable Apnea Prediction [MVAP] score) in the first stage, followed by RPI in a subset as the second-stage. We assessed area under the receiver operating characteristic curve (AUC), sensitivity, and negative posttest probability (NPTP) for this two-stage approach and for RPI alone. RESULTS: The best-performing model used the MVAP, which combines BMI, age, and sex with three OSA symptoms, in the first stage, followed by RPI in the second. The model yielded an estimated (95% confidence interval) AUC of 0.883 (0.767-0.924), sensitivity of 0.917 (0.706-0.962), and NPTP of 0.034 (0.015-0.133). Predictive characteristics were similar using a model with only BMI as the first-stage screen. CONCLUSIONS: A two-stage model that combines BMI or the MVAP score in the first stage, with EKG in the second, had robust discriminatory power to identify severe OSA in CMVOs.

Angiotensin-(1-7) Receptor Mas in Hemodynamic and Thermoregulatory Dysfunction After High-Level Spinal Cord Injury in Mice: A Pilot Study.

Spinal cord injury (SCI) above mid-thoracic levels leads to autonomic dysfunction affecting both the cardiovascular system and thermoregulation. The renin-angiotensin system (RAS) which is a potent regulator of blood pressure, including its novel beneficial arm with the receptor Mas could be an interesting target in post-SCI hemodynamics. To test the hypothesis that hemodynamics, activity and diurnal patterns of those are more affected in the Mas deficient mice post-SCI we used a mouse model of SCI with complete transection of spinal cord at thoracic level 4 (T4-Tx) and performed telemetric monitoring of blood pressure (BP) and heart rate (HR). Our data revealed that hypothermia deteriorated physiological BP and HR control. Preserving normothermia by keeping mice at 30°C prevented severe hypotension and bradycardia post-SCI. Moreover, it facilitated rapid return of diurnal regulation of BP, HR and activity in wild type (WT) mice. In contrast, although Mas deficient mice had comparable reacquisition of diurnal HR rhythm, they showed delayed recovery of diurnal rhythmicity in BP and significantly lower nocturnal activity. Exposing mice with T4-Tx (kept in temperature-controlled cages) to 23°C room temperature for one hour at different time-points post-SCI, demonstrated their inability to maintain core body temperature, Mas deficient mice being significantly more impaired than WT littermates. We conclude that Mas deficient mice were more resistant to acute hypotension, delayed nocturnal recovery, lower activity and more severely impaired thermoregulation. The ambient temperature had significant effect on hemodynamics and, thus it should be taken into account when assessing cardiovascular parameters post-SCI in mice.

Increased cardiorespiratory coordination in preeclampsia.

Preeclampsia is one of the main sources of morbidity in pregnancy with a high mortality rate without a known ultimate cause. Using a corpus including 927 measurements of pregnant women with and without different hypertonic diseases at multiple stages of pregnancy, we utilised a new approach to analyse cardiorespiratory coordination. Since the recording quality of respiratory effort was limited due to a high signal to noise ratio, we applied an ECG derived respiration approach to create an ersatz respiratory signal. After applying the few available recordings with a sufficiently high quality of the respiratory signal to validate the substitute, coordigrams were calculated and quantified by utilising an epsilon method. We showed significant (p < 0.05) differences in the coordination in a matched (BMI, age, gestational week) comparison of preeclamptic and healthy subjects. Hopefully future applications of and improvements on these methods are able to create a fast and convenient prediction methodology to reduce the impact of this disease as well as help in the determination of its underlying cause.

Quantifying Effects of Pharmacological Blockers of Cardiac Autonomous Control Using Variability Parameters.

Objective: The aim of this study was to identify the most sensitive heart rate and blood pressure variability (HRV and BPV) parameters from a given set of well-known methods for the quantification of cardiovascular autonomic function after several autonomic blockades. Methods: Cardiovascular sympathetic and parasympathetic functions were studied in freely moving rats following peripheral muscarinic (methylatropine), ß1-adrenergic (metoprolol), muscarinic + ß1-adrenergic, α1-adrenergic (prazosin), and ganglionic (hexamethonium) blockades. Time domain, frequency domain and symbolic dynamics measures for each of HRV and BPV were classified through paired Wilcoxon test for all autonomic drugs separately. In order to select those variables that have a high relevance to, and stable influence on our target measurements (HRV, BPV) we used Fisher's Method to combine the p-value of multiple tests. Results: This analysis led to the following best set of cardiovascular variability parameters: The mean normal beat-to-beat-interval/value (HRV/BPV: meanNN), the coefficient of variation (cvNN = standard deviation over meanNN) and the root mean square differences of successive (RMSSD) of the time domain analysis. In frequency domain analysis the very-low-frequency (VLF) component was selected. From symbolic dynamics Shannon entropy of the word distribution (FWSHANNON) as well as POLVAR3, the non-linear parameter to detect intermittently decreased variability, showed the best ability to discriminate between the different autonomic blockades. Conclusion: Throughout a complex comparative analysis of HRV and BPV measures altered by a set of autonomic drugs, we identified the most sensitive set of informative cardiovascular variability indexes able to pick up the modifications imposed by the autonomic challenges. These indexes may help to increase our understanding of cardiovascular sympathetic and parasympathetic functions in translational studies of experimental diseases.

Heart rate variability feature selection in the presence of sleep apnea: An expert system for the characterization and detection of the disorder.

We introduce a sleep apnea characterization and classification approach based on a Heart Rate Variability (HRV) feature selection process, thus focusing on the characterization of the underlying process from a cardiac rate point of view. Therefore, we introduce linear and nonlinear variables, namely Cepstrum Coefficients (CC), Filterbanks (Fbank) and Detrended Fluctuation Analysis (DFA). Logistic Regression, Linear Discriminant Analysis and Quadratic Discriminant Analysis were used for classification purposes. The experiments were carried out using two databases. We achieved a per-segment accuracy of 84.76% (sensitivity = 81.45%, specificity = 86.82%, AUC = 0.92) in the Apnea-ECG Physionet database, whereas in the HuGCDN2014 database, provided by the Dr. Negrín University Hospital (Las Palmas de Gran Canaria, Spain), the best results were: accuracy = 81.96%, sensitivity = 70.95%, specificity = 85.47%, AUC = 0.87. The former results were comparable or better than those obtained by other methods for the same database in the recent literature. We have concluded that the selected features that best characterize the underlying process are common to both databases. This supports the fact that the conclusions reached are potentially generalizable. The best results were obtained when the three kinds of features were jointly used. Another notable fact is the small number of features needed to describe the phenomenon. Results suggest that the two first Fbanks, the first CC and the first DFA coefficient are the variables that best describe the RR pattern in OSA and, therefore, are especially relevant to extract discriminative information for apnea screening purposes.

Causality in physiological signals.

Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The scope of this review, as opposed to various other excellent reviews like (Hlavácková-Schindler et al Phys. Rep. 441 1-46, Kramer et al 2004 Phys. Rev. E 70 1-10, Lombardi 2000 Circulation 101 8-10, Porta et al 2000 Am. J. Physiol.: Heart and Circulatory Physiol. 279 H2558-67, Schelter et al 2006 J. Neurosci. Methods 152 210-9), is to give a broader overview over existing coupling measures and where to look to find the most appropriate tool for a given situation. The review will comprise a test of one representative of the most important coupling measure groups using a simple toy model to illustrate some essential features of the tools. At the end we will summarise the performance of each measure and offer some advice on when to use which method.

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography.

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).

Cardio-respiratory coordination increases during sleep apnea.

Cardiovascular diseases are the main source of morbidity and mortality in the United States with costs of more than $170 billion. Repetitive respiratory disorders during sleep are assumed to be a major cause of these diseases. Therefore, the understanding of the cardio-respiratory regulation during these events is of high public interest. One of the governing mechanisms is the mutual influence of the cardiac and respiratory oscillations on their respective onsets, the cardio-respiratory coordination (CRC). We analyze this mechanism based on nocturnal measurements of 27 males suffering from obstructive sleep apnea syndrome. Here we find, by using an advanced analysis technique, the cardiogram, not only that the occurrence of CRC is significantly more frequent during respiratory sleep disturbances than in normal respiration (p-value<10(-51)) but also more frequent after these events (p-value<10(-15)). Especially, the latter finding contradicts the common assumption that spontaneous CRC can only be observed in epochs of relaxed conditions, while our newly discovered epochs of CRC after disturbances are characterized by high autonomic stress. Our findings on the connection between CRC and the appearance of sleep-disordered events require a substantial extension of the current understanding of obstructive sleep apneas and hypopneas.