In recent years, sleep medicine has attracted many interests. Among many sleep disorder problems, the sleep apnea syndrome is of great importance. One of its side effects is its negative influences on cardiovascular system whose function can be monitored by ECG. The regulation of the heart rate is extremely important for human body. In general, the heart rate variability is controlled by the balance of the sympathetic and the parasympathetic systems whose functions can be influenced by sleep apnea. This work tries to establish the relation between the heart rate variability and AHI (Apnea & hypopnea index). Through the statistical methods, we analyze how the sleep apnea influences the low frequency (LF) and high frequency components of the RR intervals. With BMI, age and AHI as the independent variables, we set up the regression model to predict LF/HF Our results demonstrate that, for men, the linear relationship between the LF/HF and AHI is statistically significant when AHI is higher than 45. This results may shed some light on developing HRV based diagnosis method for sleep apnea.

SAS has became an increasingly important public-health problem since 1970. It can adversely affect neurocognitive, cardiovascular, respiratory diseases and can also cause behavior disorder. Moreover, up to 90% of these cases are obstructive sleep apnea (OSA). Presently, Polysomnography is considered as the gold standard for diagnosing sleep apnea syndrome (SAS). However, Polysomnography-based sleep studies are expensive and time-consuming because they require overnight evaluation in sleep laboratories with dedicated systems and attending personnel. In this study, based on the nocturnal oxygen saturation (SpO2) signals, this work develops a method to classify patients with different levels of respiratory disturbance index (RDI) values. To achieve this goal, this study uses neural network in conjunction with different sets of feature variables to perform classification.

Snores are breath sounds that most people produce during sleep and they are reported to be a risk factor for various sleep disorders, such as obstructive sleep apnea syndrome (OSAS). Diagnosis of sleep disorders relies on the expertise of the clinician that inspects whole night polysomnography recordings. This inspection is time consuming and uncomfortable for the patient. There are surgical and therapeutic treatments. However, evaluation of the success of these methods also relies on subjective criteria and the expertise of the clinician. Thus, there is a strong need for a tool to analyze the snore sounds automatically, and to produce objective criteria and to assess the success of the applied treatment by comparing these criteria obtained before and after the treatment. In this thesis, we proposed a new algorithm to detect snoring episodes from the sleep sound recordings of the individuals, and created a user friendly interface to process snore recordings and to produce simple objective criteria to evaluate the results. The algorithm classifies sleep sound segments as snores and nonsnores according to their subband energy distributions. It was observed that inter- and intra-individual spectral energy distributions of snore sounds show significant similarities. This observation motivated the representation of the feature vectors in a lower dimensional space which was achieved using principal component analysis. Sleep sounds can be efficiently represented and classified as snore or nonsnore in a two dimensional space. The sound recordings were taken from patients that are suspected of OSAS pathology while they were connected to the polysomnography in G&uuml / lhane Military Medical Academy Sleep Studies Laboratory. The episodes taken from 30 subjects (18 simple snorers and 12 OSA patients) with different apnea/hypopnea indices were classified using the proposed algorithm. The system was tested by using the manual annotations of an ENT specialist as a reference. The system produced high detection rates both in simple snorers and OSA patients.

The physiological signals of human are very important for the diagnosis of diseases. There are two different applications of physiological signals in this study. One is using oxyhemoglobin saturation to diagnose the obstructive sleep apnea hypopnea syndrome (OSAS); the other is to determine the association between dermatoglyphics and schizophrenia by using fingerprint asymmetry measures. The objective of the first part is to comprehensively evaluate the capablity and reliability of the previously proposed oxyhemoglobin indices derived automatically for predicting the severity of OSAS. Patients with a diagnosis of OSAS by standard polysomnography were recruited from China Medical University Hospital Sleep Center. The result revealed that when AHI cutoff value was set to 30/h, ODI achieves 87.8% sensitivity and 96.6% specificity. Another important finding is that, for both apnea and hypopnea, probability of oxyhemoglobin desaturation increases with increases of body mass index (BMI) and neck circumference (NC). Early detection and intervention strategies for schizophrenia are receiving increasingly more attention. Dermatoglyphic patterns have been hypothesized to be indirect measures for early abnormal developmental processes that can lead to later psychiatric disorders such as schizophrenia. However, previous results have been inconsistent in trying to establish the association between dermatoglyphics and schizophrenia. The goal of second part of this work is to try to resolve this problem by borrowing well developed techniques from the field of fingerprint matching. Fingerprint images were acquired digitally from 40 schizophrenic patients and 51 normal individuals. Based on these images, the sample means of the proposed measures consistently identified the patient group as having a higher degree of asymmetry than the control group.

published_or_final_version / Dentistry / Master / Master of Orthodontics

Obstructive sleep apnea (OSA) is a disease characterized by nighttime airflow limitation, hypoxemia, arousal from sleep, and elevated sympathetic activity and blood pressure. With time, this nighttime dysfunction gives rise to daytime hypertension and a heightened risk for cardiovascular disease. Current treatment options for OSA are not always effective for all patients and the gold-standard intervention, continuous positive airway pressure, has discouraging compliance rates. The work set forth in this dissertation has as its focus a novel intervention for sleep apnea known as inspiratory muscle training (IMT). IMT improves respiratory function and cardiovascular health but has not been implemented previously as a treatment for OSA. As such, Study 1 implements IMT in individuals with mild and moderate OSA, with the objective of assessing the effects of training on the cardio- respiratory parameters of this disease. We randomly assigned 24 individuals with mild- moderate OSA into one of two groups: training vs. placebo, to assess the effects of 6 weeks of training on overnight polysomnography, subjective sleep quality, blood pressure, circulating inflammatory T cells, and plasma catecholamine content. Our results show IMT- related improvements in sleep quality, reduction in the number of arousals from sleep and in periodic limb movements following 6 weeks of training. Most important, IMT was associated with a significant reduction in systolic (~12 mmHg) and diastolic (~5 mmHg) blood pressure, relative to sleep apneics who undertook 6 weeks of placebo training. Additionally, individuals in the training group exhibited ~30% lower levels of sympathetic activity, as measured by plasma catecholamines, relative to placebo trained peers. The mechanism(s) that underlie the IMT-related reductions in blood pressure and sympathetic activity remain to be determined. However, in an effort to determine the precise respiratory stimulus that contributes to the results obtained in Study 1, we subsequently assessed the specific respiratory components of IMT to determine which component (large intrathoracic pressures and/or large lung volumes) likely contributes to the reduction in blood pressure in Study 1. The results of this study conducted in normotensive adults show that respiratory training that entails either large negative or positive intrathoracic pressures reduces systolic and diastolic blood pressure in healthy young adults. Importantly, neither the generation of large lung volumes alone nor performance of daily paced breathing is sufficient to lower blood pressure. Study 3 is a methodologic study that has as its focus upper airway electromyography (EMG) and the utility of assessing EMG activity across a range of conditions and breathing tasks in wakefulness. Because OSA traditionally has been viewed as the result of neuromuscular dysfunction of the upper airway that occurs during sleep, the aim of this work was to develop a "fingerprint" of healthy electromyographic activities during the day in healthy adults across a range of breathing tasks, body positions, and from two different muscle compartments of the upper airway. The findings from this study demonstrate regional differences in muscle activity that vary as a function of body position and task. These data from healthy subjects provide the basis of comparison for subsequent studies in individuals with obstructive sleep apnea.

No description available.

The current study investigated the relationship between obstructive sleep apnea (OSA) and depressive symptoms on neuropsychological functioning and academic achievement in a sample of ethnically diverse school-aged children in the Southwest United States. A total of 38 participants aged 6 - 12 were studied as part of an ongoing randomized clinical trial (SleepCATS) investigating the neurocognitive impact of continuous positive airway pressure therapy (CPAP) on neurobehavioral outcomes. Children were identified as having primary snoring, mild OSA, or Moderate-Severe OSA based on in-lab nocturnal polysomnography and were assessed for depressive symptoms using the parent report of the Child Behavior Checklist (CBCL). Neuropsychological testing was conducted using the Cambridge Automated Neuropsychological Test Battery (CANTAB) to assess executive functioning, working memory, and motor control. The Grooved Pegboard Test (GPT) was used to assess fine motor speed and dexterity and academic achievement was assessed on the Woodcock-Johnson Test of Academic Achievement Third Edition (WJ-ACH III). The study identified 39% of the sample as having clinical depressive symptoms and mean depressive symptoms for the sample was nearly one standard deviation above the norms. Multivariate analysis of covariance models (MANCOVA) were used to determine differences in neuropsychological test performance by neurocognitive constructs. Results from the study found significant main effects for OSA severity on the CANTAB Spatial Span Test and a significant interaction of off clinical depressive symptoms and OSA severity on the Applied Problems test of the WJ ACH III. When groups were compared between children with primary snoring and OSA (Mild and Moderate-Severe combined) there were no longer significant effects for academic achievement or working memory, however, there was a significant main effect for motor control on the CANTAB with children with OSA exhibiting lower performance compared to those with primary snoring. The results from this study suggest children with moderate-severe OSA may exhibit increased difficulties in working memory and fine-motor control, and also have increased difficulties with academic math achievement when children with moderate-severe OSA also have depressive symptoms. These findings suggest children with higher severities of OSA may experience increased learning and academic challenges, which may be further exacerbated when accompanied by depression.

There is evidence that non-surgical treatment of OSA improves blood pressure (BP) in patients with obstructive sleep apnea (OSA). The objective of this study is to determine the effect of maxillomandibular advancement (MMA) surgery for OSA on BP. 15 patients undergoing MMA surgery for treatment of OSA were enrolled. Ambulatory BP, and BMI were recorded pre- and post-operatively. The average age of the patients was 48.9 years and they had mean preoperative AHI of 40.8 and a mean baseline BMI of 30.8 kg/m2. There were no statistically significant reductions in mean systolic or diastolic BP postoperatively. The BMI was found to decrease on average from 30.8 kg/m2 to 29.3 kg/m2 at follow up (p = 0.01). There were no identifiable relationships between OSA severity and BP. Given the prevalence of OSA and it’s adverse medical consequences, more studies to determine the effect of MMA on BP are warranted.

We hypothesized that temporal features of EEG are altered in sleep apnea subjects comparedto normal subjects. The initial aim was to develop a measure to discriminate sleep stages innormals. The longer-term goal was to apply these methods to identify differences in EEGactivity in sleep apnea subjects from normals. We analyzed the C3A2 EEG and anelectrooculogram (EOG) recorded from 9 normal adults awake and in rapid eye movement(REM) and non-REM sleep. The EEG signals were filtered to remove EOG contamination. Twomeasures of the irregularity of EEG signals, Sample Entropy (SpEn) and Tsallis Entropy, wereevaluated for their ability to discriminate sleep stages. SpEn changes with sleep state, beinglargest in Wake. Stage 3/4 had the smallest SpEn (0.57??0.11) normalized to Wake values,followed by Stage 2 (0.72??0.09), REM (0.75??0.1) and Stage 1 (0.89??0.05). This pattern wasconsistent in all the polysomnogram records analyzed. Similar pattern was observed in leadO1A2 as well. We conclude that SpEn may be useful as part of a montage for assessing sleepstate. We analyzed data from sleep apnea subjects having obstructive and central apnea eventsand have made some preliminary observations; the SpEn values were more similar across sleepstages and also high correlation with oxygen saturation was observed.