A perspective on automated rapid eye movement sleep assessment.

Rapid eye movement sleep is associated with distinct changes in various biomedical signals that can be easily captured during sleep, lending themselves to automated sleep staging using machine learning systems. Here, we provide a perspective on the critical characteristics of biomedical signals associated with rapid eye movement sleep and how they can be exploited for automated sleep assessment. We summarise key historical developments in automated sleep staging systems, having now achieved classification accuracy on par with human expert scorers and their role in the clinical setting. We also discuss rapid eye movement sleep assessment with consumer sleep trackers and its potential for unprecedented sleep assessment on a global scale. We conclude by providing a future outlook of computerised rapid eye movement sleep assessment and the role AI systems may play.

Comparison of single-lead and multi-lead ECG for QT variability assessment using autoregressive modelling.

Objective. Beat-to-beat fluctuations in the QT interval-QT variability (QTV)-have been shown to vary amongst the different ECG leads. This study aims to compare the utility of single and multi-lead ECG to disentangle the mechanisms contributing to QTV.Approach. Twelve-lead ECG was analysed in 57 coronary artery disease patients before and after an elective percutaneous transluminal coronary angiography (PTCA) procedure. QT, RR and respiration time series were extracted. QTV was decomposed into contributions by heart rate, respiration and QTV independent of heart rate and respiration using parametric autoregressive modelling. Signal-to-noise ratio, model goodness-of-fit, mean QT, corrected QT, QT variability and RR variability were also computed. Results from two single leads (Lead II and V5) and three one-dimensional representations of 12-lead ECG (principal component analysis (PCA), vector magnitude (VM), and root mean square of the 8 independent leads of the standard 12 leads (RMS8)) were compared during resting conditions, before and after PTCA, and between patients with myocardial infarction and those without.Main results. At baseline, mean QT and corrected QT were significantly lower in VM and RMS8 compared to single leads. While overall QT variability was not different between the leads, QT independent of heart rate and respiration was significantly lower in VM and RMS8. Following PTCA, changes in these variables were similar in all leads. Differences between patients with MI and those without MI were consistent in all leads.Significance. Despite the differences in some QTV components amongst various leads, single-lead ECG could be sufficient for analyzing QTV in populations with pathological cardiovascular conditions compared to those without, or for quantification of intervention effects.

Mobile app-based symptom-rhythm correlation assessment in patients with persistent atrial fibrillation.

BACKGROUND: The assessment of symptom-rhythm correlation (SRC) in patients with persistent atrial fibrillation (AF) is challenging. Therefore, we performed a novel mobile app-based approach to assess SRC in persistent AF. METHODS: Consecutive persistent AF patients planned for electrical cardioversion (ECV) used a mobile app to record a 60-s photoplethysmogram (PPG) and report symptoms once daily and in case of symptoms for four weeks prior and three weeks after ECV. Within each patient, SRC was quantified by the SRC-index defined as the sum of symptomatic AF recordings and asymptomatic non-AF recordings divided by the sum of all recordings. RESULTS: Of 88 patients (33% women, age 68 ± 9 years) included, 78% reported any symptoms during recordings. The overall SRC-index was 0.61 (0.44-0.79). The study population was divided into SRC-index tertiles: low (<0.47), medium (0.47-0.73) and high (≥0.73). Patients within the low (vs high) SRC-index tertile had more often heart failure and diabetes mellitus (both 24.1% vs 6.9%). Extrasystoles occurred in 19% of all symptomatic non-AF PPG recordings. Within each patient, PPG recordings with the highest (vs lowest) tertile of pulse rates conferred an increased risk for symptomatic AF recordings (odds ratio [OR] 1.26, 95% coincidence interval [CI] 1.04-1.52) and symptomatic non-AF recordings (OR 2.93, 95% CI 2.16-3.97). Pulse variability was not associated with reported symptoms. CONCLUSIONS: In patients with persistent AF, SRC is relatively low. Pulse rate is the main determinant of reported symptoms. Further studies are required to verify whether integrating mobile app-based SRC assessment in current workflows can improve AF management.

Assessment and interpretation of sleep disordered breathing severity in cardiology: Clinical implications and perspectives.

Sleep disordered breathing (SDB) is highly prevalent in patients with atrial fibrillation, heart failure and hypertension and is associated with increased risk of mortality, cardiovascular (CV) events and arrhythmias. Current assessment of the severity of SDB is mainly based on the apnea-hypopnea index (AHI) representing the number of hypopneas and apneas per hour of sleep. However, this event-based parameter alone may not sufficiently reflect the complex pathophysiological mechanisms underlying SDB potentially contributing to CV outcome risk. In this review article, we highlight important limitations and pitfalls of current assessment, quantification and interpretation of SDB-severity in patients with CV disease and will discuss pathophysiological considerations from preclinical and clinical mechanistic studies and possible clinical implications.

A network physiology approach to the assessment of the link between sinoatrial and ventricular cardiac controls.

OBJECTIVE: A network physiology approach to evaluate the strength of the directed interactions among cardiac controls at sinoatrial and ventricular levels and respiration (R) is proposed. APPROACH: The network is composed of three nodes (i.e. sinoatrial and ventricular cardiac controls and R) and their activity is exemplified by the variability of heart period (HP), the variability of the duration of the electrical activity of the heart approximated as the temporal distance between Q-wave onset and T-wave end or apex (i.e. QTe or QTa) and thoracic movements respectively. Model-based transfer entropy provided the estimate of the strength of the causal link from the source to the destination conditioned on the remaining node activity. The interactions were monitored in 15 healthy subjects aged from 24 to 54 years (9 males). Increasing levels of sympathetic activity were induced by graded head-up tilt with table inclination of 0, 15, 30, 45, 60, 75°. MAIN RESULTS: We found that: (i) the strength of the causal link from HP to QTe gradually decreases with tilt table angle, while that in the reverse direction is weak, even though significant, and constant; (ii) the action of R on HP is stronger than that from R to QTe; (iii) the strength of the relation from R to HP is weakly related to tilt table inclination, while that from R to QTe does not depend on it; (iv) while QTe cannot affect R, a weak causal dependence of R on HP is detected; (v) the network computed over QTa is qualitatively similar to that over QTe, even though the strength of the causal relations might be different. SIGNIFICANCE: The proposed network physiology approach provides a comprehensive picture of the directed links among relevant cardiac regulatory mechanisms and their evolution with sympathetic tone usable to identify pathological conditions.

Joint symbolic dynamics for the assessment of cardiovascular and cardiorespiratory interactions.

Beat-to-beat variations in heart period provide information on cardiovascular control and are closely linked to variations in arterial pressure and respiration. Joint symbolic analysis of heart period, systolic arterial pressure and respiration allows for a simple description of their shared short-term dynamics that are governed by cardiac baroreflex control and cardiorespiratory coupling. In this review, we discuss methodology and research applications. Studies suggest that analysis of joint symbolic dynamics provides a powerful tool for identifying physiological and pathophysiological changes in cardiovascular and cardiorespiratory control.