Unconstrained video monitoring of breathing behavior and application to diagnosis of sleep apnea

This paper presents a new real-time automated infrared video monitoring technique for detection of breathing anomalies, and its application in the diagnosis of obstructive sleep apnea. We introduce a novel motion model to detect subtle, cyclical breathing signals from video, a new 3-D unsupervised self-adaptive breathing template to learn individuals' normal breathing patterns online, and a robust action classification method to recognize abnormal breathing activities and limb movements. This technique avoids imposing positional constraints on the patient, allowing patients to sleep on their back or side, with or without facing the camera, fully or partially occluded by the bed clothes. Moreover, shallow and abdominal breathing patterns do not adversely affect the performance of the method, and it is insensitive to environmental settings such as infrared lighting levels and camera view angles. The experimental results show that the technique achieves high accuracy (94% for the clinical data) in recognizing apnea episodes and body movements and is robust to various occlusion levels, body poses, body movements (i.e., minor head movement, limb movement, body rotation, and slight torso movement), and breathing behavior (e.g., shallow versus heavy breathing, mouth breathing, chest breathing, and abdominal breathing). © 2013 IEEE

Effect of Patient Sex on the Severity of Coronary Artery Disease in Patients with Newly Diagnosis of Obstructive Sleep Apnoea Admitted by an Acute Coronary Syndrome

Background: The cardiovascular consequences of obstructive sleep apnoea (OSA) differ by sex. We hypothesized that sex influences the severity of acute coronary syndrome (ACS) in patients with OSA. OSA was defined as an apnoea–hypopnoea index (AHI)>15 events·h-1. We evaluated the severity of ACS according to the ejection fraction, Killip class, number of diseased vessels, number of stents implanted and plasma peak troponin level. Methods: We included 663 men (mean±SD, AHI 37±18 events·h-1) and 133 women (AHI 35±18 events·h-1) with OSA. Results: The men were younger than the women (59±11 versus 66±11 years, p<0.0001), exhibited a higher neck circumference (p<0.0001), and were more likely to be smokers and alcohol users than women (p<0.0001, p = 0.0005, respectively). Body mass index and percentage of hypertensive patients or diabetics were similar between sexes. We observed a slight tendency for a higher Killip classification in women, although it was not statistically significant (p = 0.055). For men, we observed that the number of diseased vessels and the number of stents implanted were higher (p = 0.02, p = 0.001, respectively), and a decrease in the ejection fraction (p = 0.002). Conclusions: This study shows that sex in OSA influences the severity of ACS. Men show a lower ejection fraction and an increased number of diseased vessels and number of stents implanted

Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks

The pattern of sleep stages across a night (sleep architecture) is influenced by biological, behavioral, and clinical variables. However, traditional measures of sleep architecture such as stage proportions, fail to capture sleep dynamics. Here we quantify the impact of individual differences on the dynamics of sleep architecture and determine which factors or set of factors best predict the next sleep stage from current stage information. We investigated the influence of age, sex, body mass index, time of day, and sleep time on static (e.g. minutes in stage, sleep efficiency) and dynamic measures of sleep architecture (e.g. transition probabilities and stage duration distributions) using a large dataset of 3202 nights from a non-clinical population. Multi-level regressions show that sex effects duration of all Non-Rapid Eye Movement (NREM) stages, and age has a curvilinear relationship for Wake After Sleep Onset (WASO) and slow wave sleep (SWS) minutes. Bayesian network modeling reveals sleep architecture depends on time of day, total sleep time, age and sex, but not BMI. Older adults, and particularly males, have shorter bouts (more fragmentation) of Stage 2, SWS, and they transition less frequently to these stages. Additionally, we showed that the next sleep stage and its duration can be optimally predicted by the prior 2 stages and age. Our results demonstrate the potential benefit of big data and Bayesian network approaches in quantifying static and dynamic architecture of normal sleep

A review of ECG-based diagnosis support systems for obstructive sleep apnea

Humans need sleep. It is important for physical and psychological recreation. During sleep our consciousness is suspended or least altered. Hence, our ability to avoid or react to disturbances is reduced. These disturbances can come from external sources or from disorders within the body. Obstructive Sleep Apnea (OSA) is such a disorder. It is caused by obstruction of the upper airways which causes periods where the breathing ceases. In many cases, periods of reduced breathing, known as hypopnea, precede OSA events. The medical background of OSA is well understood, but the traditional diagnosis is expensive, as it requires sophisticated measurements and human interpretation of potentially large amounts of physiological data. Electrocardiogram (ECG) measurements have the potential to reduce the cost of OSA diagnosis by simplifying the measurement process. On the down side, detecting OSA events based on ECG data is a complex task which requires highly skilled practitioners. Computer algorithms can help to detect the subtle signal changes which indicate the presence of a disorder. That approach has the following advantages: computers never tire, processing resources are economical and progress, in the form of better algorithms, can be easily disseminated as updates over the internet. Furthermore, Computer-Aided Diagnosis (CAD) reduces intra- and inter-observer variability. In this review, we adopt and support the position that computer based ECG signal interpretation is able to diagnose OSA with a high degree of accuracy

Impact of obstructive sleep apneas on the immune and metabolic homeostasis : The influence of the environment

Sleep is a condition with reduction or absence of life supporting mechanism like alimentation, self-defence, or reproduction. It occupies about a third of the human life span and has been found in all animals including insects. Despite the intense research in recent years, several mysteries of sleep still need to be revealed. This manuscript aims to increase our knowledge of the effect of obstructive sleep apnea (OSA) on components of human homeostasis

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.Peer Reviewe

Diagnosis of pediatric obstructive sleep apnea: Preliminary findingsusing automatic analysis of airflow and oximetry recordings obtainedat patients’ home

Producción CientíficaThe obstructive sleep apnea syndrome (OSAS) greatly affects both the health and the quality of life of chil-dren. Therefore, an early diagnosis is crucial to avoid their severe consequences. However, the standarddiagnostic test (polysomnography, PSG) is time-demanding, complex, and costly. We aim at assessinga new methodology for the pediatric OSAS diagnosis to reduce these drawbacks. Airflow (AF) and oxy-gen saturation (SpO2) at-home recordings from 50 children were automatically processed. Informationfrom the spectrum of AF was evaluated, as well as combined with 3% oxygen desaturation index (ODI3)through a logistic regression model. A bootstrap methodology was conducted to validate the results.OSAS significantly increased the spectral content of AF at two abnormal frequency bands below (BW1)and above (BW2) the normal respiratory range. These novel bands are consistent with the occurrenceof apneic events and the posterior respiratory overexertion, respectively. The spectral information fromBW1 and BW2 showed complementarity both between them and with ODI3. A logistic regression modelbuilt with 3 AF spectral features (2 from BW1 and 1 from BW2) and ODI3 achieved (mean and 95% confi-dence interval): 85.9% sensitivity [64.5–98.7]; 87.4% specificity [70.2–98.6]; 86.3% accuracy [74.9–95.4];0.947 area under the receiver-operating characteristics curve [0.826–1]; 88.4% positive predictive value[72.3–98.5]; and 85.8% negative predictive value [65.8–98.5]. The combination of the spectral informationfrom two novel AF bands with the ODI3 from SpO2is useful for the diagnosis of OSAS in children.Ministerio de Economía y Competitividad (project TEC2011-22987)Junta de Castilla y León (project VA059U13

Heart rate responses to autonomic challenges in obstructive sleep apnea.

Obstructive sleep apnea (OSA) is accompanied by structural alterations and dysfunction in central autonomic regulatory regions, which may impair dynamic and static cardiovascular regulation, and contribute to other syndrome pathologies. Characterizing cardiovascular responses to autonomic challenges may provide insights into central nervous system impairments, including contributions by sex, since structural alterations are enhanced in OSA females over males. The objective was to assess heart rate responses in OSA versus healthy control subjects to autonomic challenges, and, separately, characterize female and male patterns. We studied 94 subjects, including 37 newly-diagnosed, untreated OSA patients (6 female, age mean ± std: 52.1 ± 8.1 years; 31 male aged 54.3 ± 8.4 years), and 57 healthy control subjects (20 female, 50.5 ± 8.1 years; 37 male, 45.6 ± 9.2 years). We measured instantaneous heart rate with pulse oximetry during cold pressor, hand grip, and Valsalva maneuver challenges. All challenges elicited significant heart rate differences between OSA and control groups during and after challenges (repeated measures ANOVA, p&lt;0.05). In post-hoc analyses, OSA females showed greater impairments than OSA males, which included: for cold pressor, lower initial increase (OSA vs. control: 9.5 vs. 7.3 bpm in females, 7.6 vs. 3.7 bpm in males), OSA delay to initial peak (2.5 s females/0.9 s males), slower mid-challenge rate-of-increase (OSA vs. control: -0.11 vs. 0.09 bpm/s in females, 0.03 vs. 0.06 bpm/s in males); for hand grip, lower initial peak (OSA vs. control: 2.6 vs. 4.6 bpm in females, 5.3 vs. 6.0 bpm in males); for Valsalva maneuver, lower Valsalva ratio (OSA vs. control: 1.14 vs. 1.30 in females, 1.29 vs. 1.34 in males), and OSA delay during phase II (0.68 s females/1.31 s males). Heart rate responses showed lower amplitude, delayed onset, and slower rate changes in OSA patients over healthy controls, and impairments may be more pronounced in females. The dysfunctions may reflect central injury in the syndrome, and suggest autonomic deficiencies that may contribute to further tissue and functional pathologies