Eric Chern-Pin Chua

ANALYSIS AND AUTOMATIC IDENTIFICATION OF SLEEP STAGES USING HIGHER ORDER SPECTRA

Electroencephalogram (EEG) signals are widely used to study the activity of the brain, such as to determine sleep stages. These EEG signals are nonlinear and non-stationary in nature. It is difficult to perform sleep staging by visual interpretation and linear techniques. Thus, we use a nonlinear technique, higher order spectra (HOS), to extract hidden information in the sleep EEG signal. In this study, unique bispectrum and bicoherence plots for various sleep stages were proposed. These can be used as visual aid for various diagnostics application. A number of HOS based features were extracted from these plots during the various sleep stages (Wakefulness, Rapid Eye Movement (REM), Stage 1-4 Non-REM) and they were found to be statistically significant with p-value lower than 0.001 using ANOVA test. These features were fed to a Gaussian mixture model (GMM) classifier for automatic identification. Our results indicate that the proposed system is able to identify sleep stages with an accuracy of 88.7%.

Melanopsin and rod-cone photoreceptors play different roles in mediating pupillary light responses during exposure to continuous light in humans.

In mammals, the pupillary light reflex is mediated by intrinsically photosensitive melanopsin-containing retinal ganglion cells that also receive input from rod–cone photoreceptors. To assess the relative contribution of melanopsin and rod–cone photoreceptors to the pupillary light reflex in humans, we compared pupillary light responses in normally sighted individuals (n = 24) with a blind individual lacking rod–cone function. Here, we show that visual photoreceptors are required for normal pupillary responses to continuous light exposure at low irradiance levels, and for sustained pupillary constriction during exposure to light in the long-wavelength portion of the visual spectrum. In the absence of rod–cone function, pupillomotor responses are slow and sustained, and cannot track intermittent light stimuli, suggesting that rods/cones are required for encoding fast modulations in light intensity. In sighted individuals, pupillary constriction decreased monotonically for at least 30 min during exposure to continuous low-irradiance light, indicating that steady-state pupillary responses are an order of magnitude slower than previously reported. Exposure to low-irradiance intermittent green light (543 nm; 0.1–4 Hz) for 30 min, which was given to activate cone photoreceptors repeatedly, elicited sustained pupillary constriction responses that were more than twice as great compared with exposure to continuous green light. Our findings demonstrate nonredundant roles for rod–cone photoreceptors and melanopsin in mediating pupillary responses to continuous light. Moreover, our results suggest that it might be possible to enhance nonvisual light responses to low-irradiance exposures by using intermittent light to activate cone photoreceptors repeatedly in humans.

Extensive diversity in circadian regulation of plasma lipids and evidence for different circadian metabolic phenotypes in humans

The circadian system regulates daily rhythms in lipid metabolism and adipose tissue function. Although disruption of circadian clock function is associated with negative cardiometabolic end points, very little is known about interindividual variation in circadian-regulated metabolic pathways. Here, we used targeted lipidomics-based approaches to profile the time course of 263 lipids in blood plasma in 20 healthy individuals. Over a span of 28 h, blood was collected every 4 h and plasma lipids were analyzed by HPLC/MS. Across subjects, about 13% of lipid metabolites showed circadian variation. Rhythmicity spanned all metabolite classes examined, suggesting widespread circadian control of lipid-mediated energy storage, transport, and signaling. Intersubject agreement for lipids identified as rhythmic was only about 20%, however, and the timing of lipid rhythms ranged up to 12 h apart between individuals. Healthy subjects therefore showed substantial variation in the timing and strength of rhythms across different lipid species. Strong interindividual differences were also observed for rhythms of blood glucose and insulin, but not cortisol. Using consensus clustering with iterative feature selection, subjects clustered into different groups based on strength of rhythmicity for a subset of triglycerides and phosphatidylcholines, suggesting that there are different circadian metabolic phenotypes in the general population. These results have potential implications for lipid metabolism disorders linked to circadian clock disruption.

Diurnal regulation of lipid metabolism and applications of circadian lipidomics.

The circadian timing system plays a key role in orchestrating lipid metabolism. In concert with the solar cycle, the circadian system ensures that daily rhythms in lipid absorption, storage, and transport are temporally coordinated with rest-activity and feeding cycles. At the cellular level, genes involved in lipid synthesis and fatty acid oxidation are rhythmically activated and repressed by core clock proteins in a tissue-specific manner. Consequently, loss of clock gene function or misalignment of circadian rhythms with feeding cycles (e.g., in shift work) results in impaired lipid homeostasis. Herein, we review recent progress in circadian rhythms research using lipidomics, i.e., large-scale profiling of lipid metabolites, to characterize circadian-regulated lipid pathways in mammals. In mice, novel regulatory circuits involved in fatty acid metabolism have been identified in adipose tissue, liver, and muscle. Extensive diversity in circadian regulation of plasma lipids has also been revealed in humans using lipidomics and other metabolomics approaches. In future studies, lipidomics platforms will be increasingly used to better understand the effects of genetic variation, shift work, food intake, and drugs on circadian-regulated lipid pathways and metabolic health.

Heart Rate Variability Can Be Used to Estimate Sleepiness-related Decrements in Psychomotor Vigilance during Total Sleep Deprivation

STUDY OBJECTIVES To assess whether changes in psychomotor vigilance during sleep deprivation can be estimated using heart rate variability (HRV). DESIGN HRV, ocular, and electroencephalogram (EEG) measures were compared for their ability to predict lapses on the Psychomotor Vigilance Task (PVT). SETTING Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore. PARTICIPANTS Twenty-four healthy Chinese men (mean age ± SD = 25.9 ± 2.8 years). INTERVENTIONS Subjects were kept awake continuously for 40 hours under constant environmental conditions. Every 2 hours, subjects completed a 10-minute PVT to assess their ability to sustain visual attention. MEASUREMENTS AND RESULTS During each PVT, we examined the electrocardiogram (ECG), EEG, and percentage of time that the eyes were closed (PERCLOS). Similar to EEG power density and PERCLOS measures, the time course of ECG RR-interval power density in the 0.02-0.08-Hz range correlated with the 40-hour profile of PVT lapses. Based on receiver operating characteristic curves, RR-interval power density performed as well as EEG power density at identifying a sleepiness-related increase in PVT lapses above threshold. RR-interval power density (0.02-0.08 Hz) also classified subject performance with sensitivity and specificity similar to that of PERCLOS. CONCLUSIONS The ECG carries information about a persons vigilance state. Hence, HRV measures could potentially be used to predict when an individual is at increased risk of attentional failure. Our results suggest that HRV monitoring, either alone or in combination with other physiologic measures, could be incorporated into safety devices to warn drowsy operators when their performance is impaired.

Automated detection of sleep apnea from electrocardiogram signals using nonlinear parameters

Sleep apnoea is a very common sleep disorder which can cause symptoms such as daytime sleepiness, irritability and poor concentration. To monitor patients with this sleeping disorder we measured the electrical activity of the heart. The resulting electrocardiography (ECG) signals are both non-stationary and nonlinear. Therefore, we used nonlinear parameters such as approximate entropy, fractal dimension, correlation dimension, largest Lyapunov exponent and Hurst exponent to extract physiological information. This information was used to train an artificial neural network (ANN) classifier to categorize ECG signal segments into one of the following groups: apnoea, hypopnoea and normal breathing. ANN classification tests produced an average classification accuracy of 90%; specificity and sensitivity were 100% and 95%, respectively. We have also proposed unique recurrence plots for the normal, hypopnea and apnea classes. Detecting sleep apnea with this level of accuracy can potentially reduce the need of polysomnography (PSG). This brings advantages to patients, because the proposed system is less cumbersome when compared to PSG.

Sustained Attention Performance during Sleep Deprivation Associates with Instability in Behavior and Physiologic Measures at Baseline

STUDY OBJECTIVES To identify baseline behavioral and physiologic markers that associate with individual differences in sustained attention during sleep deprivation. DESIGN In a retrospective study, ocular, electrocardiogram, and electroencephalogram (EEG) measures were compared in subjects who were characterized as resilient (n = 15) or vulnerable (n = 15) to the effects of total sleep deprivation on sustained attention. SETTING Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore. PARTICIPANTS Healthy volunteers aged 22-32 years from the general population. INTERVENTIONS Subjects were kept awake for at least 26 hours under constant environmental conditions. Every 2 hours, sustained attention was assessed using a 10-minute psychomotor vigilance task (PVT). MEASUREMENTS AND RESULTS During baseline sleep and recovery sleep, EEG slow wave activity was similar in resilient versus vulnerable subjects, suggesting that individual differences in vulnerability to sleep loss were not related to differences in homeostatic sleep regulation. Rather, irrespective of time elapsed since wake, subjects who were vulnerable to sleep deprivation exhibited slower and more variable PVT response times, lower and more variable heart rate, and higher and more variable EEG spectral power in the theta frequency band (6.0-7.5 Hz). CONCLUSIONS Performance decrements in sustained attention during sleep deprivation associate with instability in behavioral and physiologic measures at baseline. Small individual differences in sustained attention that are present at baseline are amplified during prolonged wakefulness, thus contributing to large between-subjects differences in performance and sleepiness.

Effects of Exposure to Intermittent versus Continuous Red Light on Human Circadian Rhythms, Melatonin Suppression, and Pupillary Constriction

Exposure to light is a major determinant of sleep timing and hormonal rhythms. The role of retinal cones in regulating circadian physiology remains unclear, however, as most studies have used light exposures that also activate the photopigment melanopsin. Here, we tested the hypothesis that exposure to alternating red light and darkness can enhance circadian resetting responses in humans by repeatedly activating cone photoreceptors. In a between-subjects study, healthy volunteers (n = 24, 21–28 yr) lived individually in a laboratory for 6 consecutive days. Circadian rhythms of melatonin, cortisol, body temperature, and heart rate were assessed before and after exposure to 6 h of continuous red light (631 nm, 13 log photons cm−2 s−1), intermittent red light (1 min on/off), or bright white light (2,500 lux) near the onset of nocturnal melatonin secretion (n = 8 in each group). Melatonin suppression and pupillary constriction were also assessed during light exposure. We found that circadian resetting responses were similar for exposure to continuous versus intermittent red light (P = 0.69), with an average phase delay shift of almost an hour. Surprisingly, 2 subjects who were exposed to red light exhibited circadian responses similar in magnitude to those who were exposed to bright white light. Red light also elicited prolonged pupillary constriction, but did not suppress melatonin levels. These findings suggest that, for red light stimuli outside the range of sensitivity for melanopsin, cone photoreceptors can mediate circadian phase resetting of physiologic rhythms in some individuals. Our results also show that sensitivity thresholds differ across non-visual light responses, suggesting that cones may contribute differentially to circadian resetting, melatonin suppression, and the pupillary light reflex during exposure to continuous light.

Changes in Plasma Lipids during Exposure to Total Sleep Deprivation.

STUDY OBJECTIVES The effects of sleep loss on plasma lipids, which play an important role in energy homeostasis and signaling, have not been systematically examined. Our aim was to identify lipid species in plasma that increase or decrease reliably during exposure to total sleep deprivation. DESIGN Twenty individuals underwent sleep deprivation in a laboratory setting. Blood was drawn every 4 h and mass spectrometry techniques were used to analyze concentrations of 263 lipid species in plasma, including glycerolipids, glycerophospholipids, sphingolipids, and sterols. SETTING Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School. PARTICIPANTS Healthy ethnic-Chinese males aged 21-28 y (n = 20). INTERVENTIONS Subjects were kept awake for 40 consecutive hours. MEASUREMENTS AND RESULTS Each metabolite time series was modeled as a sum of sinusoidal (circadian) and linear components, and we assessed whether the slope of the linear component differed from zero. More than a third of all individually analyzed lipid profiles exhibited a circadian rhythm and/or a linear change in concentration during sleep deprivation. Twenty-five lipid species showed a linear and predominantly unidirectional trend in concentration levels that was consistent across participants. Choline plasmalogen levels decreased, whereas several phosphatidylcholine (PC) species and triacylglycerides (TAG) carrying polyunsaturated fatty acids increased. CONCLUSIONS The decrease in choline plasmalogen levels during sleep deprivation is consistent with prior work demonstrating that these lipids are susceptible to degradation by oxidative stress. The increase in phosphatidylcholines and triacylglycerides suggests that sleep loss might modulate lipid metabolism, which has potential implications for metabolic health in individuals who do not achieve adequate sleep.

Risk Scoring for Prediction of Acute Cardiac Complications from Imbalanced Clinical Data

Fast and accurate risk stratification is essential in the emergency department (ED) as it allows clinicians to identify chest pain patients who are at high risk of cardiac complications and require intensive monitoring and early intervention. In this paper, we present a novel intelligent scoring system using heart rate variability, 12-lead electrocardiogram (ECG), and vital signs where a hybrid sampling-based ensemble learning strategy is proposed to handle data imbalance. The experiments were conducted on a dataset consisting of 564 chest pain patients recruited at the ED of a tertiary hospital. The proposed ensemble-based scoring system was compared with established scoring methods such as the modified early warning score and the thrombolysis in myocardial infarction score, and showed its effectiveness in predicting acute cardiac complications within 72 h in terms of the receiver operation characteristic analysis.