Diurnal variability of C-reactive protein in obstructive sleep apnea

OBJECTIVE: The objective of this study is to examine the diurnal variability of C-reactive protein (CRP) in obstructive sleep apnea (OSA). METHODS AND MEASUREMENTS: Participants included 44 women and men with untreated OSA (mean apnea/hypopnea index = 37.5, SD +/- 28) and 23 healthy adults with no OSA. Sleep was monitored with polysomnography in the University of California San Diego General Clinical Research Center. Over a 24-h period, blood was collected every 2 h, and CRP levels were determined. RESULTS: Adjusting for age, gender, and body mass index, a significant group by time interaction showed that patients with OSA had higher CRP levels during the daytime (8:00 a.m.-8:00 p.m.) versus the nighttime (10:00 p.m. until 6:00 p.m.; p < 0.001). Non-apneics showed no significant change in CRP levels during the 24 h. CONCLUSIONS: The findings indicate that sleep apnea patients have disproportionately elevated CRP levels in the day versus the nighttime, possibly as a result of carryover effects of nighttime arousal into the daytime.

Screening for obstructive sleep apnea on the internet: randomized trial.

BACKGROUND: Obstructive sleep apnea is underdiagnosed. We conducted a pilot randomized controlled trial of an online intervention to promote obstructive sleep apnea screening among members of an Internet weight-loss community. METHODS: Members of an Internet weight-loss community who have never been diagnosed with obstructive sleep apnea or discussed the condition with their healthcare provider were randomized to intervention (online risk assessment+feedback) or control. The primary outcome was discussing obstructive sleep apnea with a healthcare provider at 12 weeks. RESULTS: Of 4700 members who were sent e-mail study announcements, 168 (97% were female, age 39.5 years [standard deviation 11.7], body mass index 30.3 [standard deviation 7.8]) were randomized to intervention (n=84) or control (n=84). Of 82 intervention subjects who completed the risk assessment, 50 (61%) were low risk and 32 (39%) were high risk for obstructive sleep apnea. Intervention subjects were more likely than control subjects to discuss obstructive sleep apnea with their healthcare provider within 12 weeks (11% [9/84] vs 2% [2/84]; P=.02; relative risk=4.50; 95% confidence interval, 1.002-20.21). The number needed to treat was 12. High-risk intervention subjects were more likely than control subjects to discuss obstructive sleep apnea with their healthcare provider (19% [6/32] vs 2% [2/84]; P=.004; relative risk=7.88; 95% confidence interval, 1.68-37.02). One high-risk intervention subject started treatment for obstructive sleep apnea. CONCLUSION: An online screening intervention is feasible and likely effective in encouraging members of an Internet weight-loss community to discuss obstructive sleep apnea with their healthcare provider.

Impact of Acetazolamide and CPAP on Cortical Activity in Obstructive Sleep Apnea Patients

STUDY OBJECTIVES 1) To investigate the impact of acetazolamide, a drug commonly prescribed for altitude sickness, on cortical oscillations in patients with obstructive sleep apnea syndrome (OSAS). 2) To examine alterations in the sleep EEG after short-term discontinuation of continuous positive airway pressure (CPAP) therapy. DESIGN Data from two double-blind, placebo-controlled randomized cross-over design studies were analyzed. SETTING Polysomnographic recordings in sleep laboratory at 490 m and at moderate altitudes in the Swiss Alps: 1630 or 1860 m and 2590 m. PATIENTS Study 1: 39 OSAS patients. Study 2: 41 OSAS patients. INTERVENTIONS Study 1: OSAS patients withdrawn from treatment with CPAP. Study 2: OSAS patients treated with autoCPAP. Treatment with acetazolamide (500-750 mg) or placebo at moderate altitudes. MEASUREMENTS AND RESULTS An evening dose of 500 mg acetazolamide reduced slow-wave activity (SWA; approximately 10%) and increased spindle activity (approximately 10%) during non-REM sleep. In addition, alpha activity during wake after lights out was increased. An evening dose of 250 mg did not affect these cortical oscillations. Discontinuation of CPAP therapy revealed a reduction in SWA (5-10%) and increase in beta activity (approximately 25%). CONCLUSIONS The higher evening dose of 500 mg acetazolamide showed the "spectral fingerprint" of Benzodiazepines, while 250 mg acetazolamide had no impact on cortical oscillations. However, both doses had beneficial effects on oxygen saturation and sleep quality.

Do optic nerve head and visual field parameters in patients with obstructive sleep apnea syndrome differ from those in control individuals?

BACKGROUND It has been suggested that sleep apnea syndrome may play a role in normal-tension glaucoma contributing to optic nerve damage. The purpose of this study was to evaluate if optic nerve and visual field parameters in individuals with sleep apnea syndrome differ from those in controls. PATIENTS AND METHODS From the records of the sleep laboratory at the University Hospital in Bern, Switzerland, we recruited consecutive patients with severe sleep apnea syndrome proven by polysomnography, apnea-hypopnea index >20, as well as no sleep apnea controls with apnea-hypopnea index <10. Participants had to be unknown to the ophtalmology department and had to have no recent eye examination in the medical history. All participants underwent a comprehensive eye examination, scanning laser polarimetry (GDx VCC, Carl Zeiss Meditec, Dublin, California), scanning laser ophthalmoscopy (Heidelberg Retina Tomograph II, HRT II), and automated perimetry (Octopus 101 Programm G2, Haag-Streit Diagnostics, Koeniz, Switzerland). Mean values of the parameters of the two groups were compared by t-test. RESULTS The sleep apnea group consisted of 69 eyes of 35 patients; age 52.7 ± 9.7 years, apnea-hypopnea index 46.1 ± 24.8. As controls served 38 eyes of 19 patients; age 45.8 ± 11.2 years, apnea-hypopnea index 4.8 ± 1.9. A difference was found in mean intraocular pressure, although in a fully overlapping range, sleep apnea group: 15.2 ± 3.1, range 8-22 mmHg, controls: 13.6 ± 2.3, range 9-18 mmHg; p<0.01. None of the extended visual field, optic nerve head (HRT) and retinal nerve fiber layer (GDx VCC) parameters showed a significant difference between the groups. CONCLUSION Visual field, optic nerve head, and retinal nerve fiber layer parameters in patients with sleep apnea did not differ from those in the control group. Our results do not support a pathogenic relationship between sleep apnea syndrome and glaucoma.

Adaptive servo-ventilation as treatment of persistent central sleep apnea in post-acute ischemic stroke patients.

BACKGROUND Adaptive servo-ventilation (ASV) is a well-established treatment of central sleep apnea (CSA) related to congestive heart failure (CHF). Few studies have evaluated the effectiveness and adherence in patients with CSA of other etiologies, and even less is known about treatment of CSA in patients of post ischemic stroke. METHODS A single-centre retrospective analysis of ASV treatment for CSA in post-acute ischemic stroke patients without concomitant CHF was performed. Demographics, clinical data, sleep studies, ventilator settings, and adherence data were evaluated. RESULTS Out of 154 patients on ASV, 15 patients had CSA related to ischemic stroke and were started on ASV a median of 11 months after the acute cerebrovascular event. Thirteen out of the 15 patients were initially treated with continuous positive airway pressure (11/15) and bilevel positive airway pressure (2/15) therapy with unsatisfactory control of CSA. ASV significantly improved AHI (46.7 ± 24.3 vs 8.5 ± 12/h, P = 0.001) and reduced ESS (8.7 ± 5.7 vs 5.6 ± 2.5, P = 0.08) with a mean nightly use of ASV of 5.4 ± 2.4 h at 3 months after the initiation of treatment. Results were maintained at 6 months. CONCLUSION ASV was well tolerated and clinically effective in this group of patients with persistent CSA after ischemic stroke.

Patent Foramen Ovale Closure in Obstructive Sleep Apnea Improves Blood Pressure and Cardiovascular Function.

UNLABELLED Obstructive sleep apnea (OSA) is a frequent syndrome characterized by intermittent hypoxemia and increased prevalence of arterial hypertension and cardiovascular morbidity. In OSA, the presence of patent foramen ovale (PFO) is associated with increased number of apneas and more severe oxygen desaturation. We hypothesized that PFO closure improves sleep-disordered breathing and, in turn, has favorable effects on vascular function and arterial blood pressure. In 40 consecutive patients with newly diagnosed OSA, we searched for PFO. After initial cardiovascular assessment, the 14 patients with PFO underwent initial device closure and the 26 without PFO served as control group. Conventional treatment for OSA was postponed for 3 months in both groups, and polysomnographic and cardiovascular examinations were repeated at the end of the follow-up period. PFO closure significantly improved the apnea-hypopnea index (ΔAHI -7.9±10.4 versus +4.7±13.1 events/h, P=0.0009, PFO closure versus control), the oxygen desaturation index (ΔODI -7.6±16.6 versus +7.6±17.0 events/h, P=0.01), and the number of patients with severe OSA decreased significantly after PFO closure (79% versus 21%, P=0.007). The following cardiovascular parameters improved significantly in the PFO closure group, although remained unchanged in controls: brachial artery flow-mediated vasodilation, carotid artery stiffness, nocturnal systolic and diastolic blood pressure (-7 mm Hg, P=0.009 and -3 mm Hg, P=0.04, respectively), blood pressure dipping, and left ventricular diastolic function. In conclusion, PFO closure in OSA patients improves sleep-disordered breathing and nocturnal oxygenation. This translates into an improvement of endothelial function and vascular stiffening, a decrease of nighttime blood pressure, restoration of the dipping pattern, and improvement of left ventricular diastolic function. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT01780207.

Three-year changes of prothrombotic factors in a cohort of South Africans with a high clinical suspicion of obstructive sleep apnea.

A hypercoagulable state might be one important mechanism linking obstructive sleep apnea (OSA) with incident myocardial infarction and stroke. However, previous studies on prothrombotic factors in OSA are not uniform and cross-sectional. We longitudinally studied prothrombotic factors in relation to OSA risk, adjusting for baseline levels of prothrombotic factors, demographics, metabolic parameters, aspirin use, and life style factors. The Berlin Questionnaire and/or neck circumference were used to define high OSA risk in 329 South African teachers (48.0 % male, 44.6 % black) at baseline and at three-year follow-up. Von Willebrand factor (VWF), fibrinogen, D-dimer, plasminogen activator inhibitor-1, clot lysis time (CLT), and soluble urokinase-type plasminogen activator receptor (suPAR) were measured in plasma. At baseline 35.7 % of participants had a high risk of OSA. At follow-up, persistently high OSA risk, persistently low OSA risk, OSA risk remission, and new-onset OSA risk were present in 26.1 %, 53.2 %, 9.4 %, and 11.3 % of participants, respectively. New-onset OSA risk was associated with a significant and longitudinal increase in VWF, fibrinogen, CLT, and suPAR relative to persistently low OSA risk; in VWF, fibrinogen, and suPAR relative to remitted OSA risk; and in VWF relative to persistently high OSA risk. Persistently high OSA risk was associated with an increase in CLT and suPAR relative to persistently low OSA risk and in D-dimer relative to remitted OSA risk. Remitted OSA risk was associated with D-dimer decrease relative to persistently low OSA risk. In OSA, hypercoagulability is a dynamic process with a most prominent three-year increase in individuals with new-onset OSA risk.

Introducing non-linear analysis into sustained speech characterization to improve sleep apnea detection

We present a novel approach for detecting severe obstructive sleep apnea (OSA) cases by introducing non-linear analysis into sustained speech characterization. The proposed scheme was designed for providing additional information into our baseline system, built on top of state-of-the-art cepstral domain modeling techniques, aiming to improve accuracy rates. This new information is lightly correlated with our previous MFCC modeling of sustained speech and uncorrelated with the information in our continuous speech modeling scheme. Tests have been performed to evaluate the improvement for our detection task, based on sustained speech as well as combined with a continuous speech classifier, resulting in a 10% relative reduction in classification for the first and a 33% relative reduction for the fused scheme. Results encourage us to consider the existence of non-linear effects on OSA patients' voices, and to think about tools which could be used to improve short-time analysis.

Improving automatic detection of obstructive sleep apnea through nonlinear analysis of sustained speech

We present a novel approach for the detection of severe obstructive sleep apnea (OSA) based on patients' voices introducing nonlinear measures to describe sustained speech dynamics. Nonlinear features were combined with state-of-the-art speech recognition systems using statistical modeling techniques (Gaussian mixture models, GMMs) over cepstral parameterization (MFCC) for both continuous and sustained speech. Tests were performed on a database including speech records from both severe OSA and control speakers. A 10 % relative reduction in classification error was obtained for sustained speech when combining MFCC-GMM and nonlinear features, and 33 % when fusing nonlinear features with both sustained and continuous MFCC-GMM. Accuracy reached 88.5 % allowing the system to be used in OSA early detection. Tests showed that nonlinear features and MFCCs are lightly correlated on sustained speech, but uncorrelated on continuous speech. Results also suggest the existence of nonlinear effects in OSA patients' voices, which should be found in continuous speech.

Evaluación de la contribución y el impacto de las tecnologías del habla en la detección automática del Síndrome de la Apnea Obstructiva del Sueño = Contributions and impact assessment of speech technologies on the automatic detection of severe Obstructive Sleep Apnea syndrome

La presente Tesis analiza las posibilidades que ofrecen en la actualidad las tecnologías del habla para la detección de patologías clínicas asociadas a la vía aérea superior. El estudio del habla que tradicionalmente cubre tanto la producción como el proceso de transformación del mensaje y las señales involucradas, desde el emisor hasta alcanzar al receptor, ofrece una vía de estudio alternativa para estas patologías. El hecho de que la señal emitida no solo contiene este mensaje, sino también información acerca del locutor, ha motivado el desarrollo de sistemas orientados a la identificación y verificación de la identidad de los locutores. Estos trabajos han recibido recientemente un nuevo impulso, orientándose tanto hacia la caracterización de rasgos que son comunes a varios locutores, como a las diferencias existentes entre grabaciones de un mismo locutor. Los primeros resultan especialmente relevantes para esta Tesis dado que estos rasgos podrían evidenciar la presencia de características relacionadas con una cierta condición común a varios locutores, independiente de su identidad. Tal es el caso que se enfrenta en esta Tesis, donde los rasgos identificados se relacionarían con una de la patología particular y directamente vinculada con el sistema de físico de conformación del habla. El caso del Síndrome de Apneas Hipopneas durante el Sueno (SAHS) resulta paradigmático. Se trata de una patología con una elevada prevalencia mundo, que aumenta con la edad. Los pacientes de esta patología experimentan episodios de cese involuntario de la respiración durante el sueño, que se prolongan durante varios segundos y que se reproducen a lo largo de la noche impidiendo el correcto descanso. En el caso de la apnea obstructiva, estos episodios se deben a la imposibilidad de mantener un camino abierto a través de la vía aérea, de forma que el flujo de aire se ve interrumpido. En la actualidad, el diagnostico de estos pacientes se realiza a través de un estudio polisomnográfico, que se centra en el análisis de los episodios de apnea durante el sueño, requiriendo que el paciente permanezca en el hospital durante una noche. La complejidad y el elevado coste de estos procedimientos, unidos a las crecientes listas de espera, han evidenciado la necesidad de contar con técnicas rápidas de detección, que si bien podrían no obtener tasas tan elevadas, permitirían reorganizar las listas de espera en función del grado de severidad de la patología en cada paciente. Entre otros, los sistemas de diagnostico por imagen, así como la caracterización antropométrica de los pacientes, han evidenciado la existencia de patrones anatómicos que tendrían influencia directa sobre el habla. Los trabajos dedicados al estudio del SAHS en lo relativo a como esta afecta al habla han sido escasos y algunos de ellos incluso contradictorios. Sin embargo, desde finales de la década de 1980 se conoce la existencia de patrones específicos relativos a la articulación, la fonación y la resonancia. Sin embargo, su descripción resultaba difícilmente aprovechable a través de un sistema de reconocimiento automático, pero apuntaba la existencia de un nexo entre voz y SAHS. En los últimos anos las técnicas de procesado automático han permitido el desarrollo de sistemas automáticos que ya son capaces de identificar diferencias significativas en el habla de los pacientes del SAHS, y que los distinguen de los locutores sanos. Por contra, poco se conoce acerca de la conexión entre estos nuevos resultados, los sé que habían obtenido en el pasado y la patogénesis del SAHS. Esta Tesis continua la labor desarrollada en este ámbito considerando específicamente: el estudio de la forma en que el SAHS afecta el habla de los pacientes, la mejora en las tasas de clasificación automática y la combinación de la información obtenida con los predictores utilizados por los especialistas clínicos en sus evaluaciones preliminares. Las dos primeras tareas plantean problemas simbióticos, pero diferentes. Mientras el estudio de la conexión entre el SAHS y el habla requiere de modelos acotados que puedan ser interpretados con facilidad, los sistemas de reconocimiento se sirven de un elevado número de dimensiones para la caracterización y posterior identificación de patrones. Así, la primera tarea debe permitirnos avanzar en la segunda, al igual que la incorporación de los predictores utilizados por los especialistas clínicos. La Tesis aborda el estudio tanto del habla continua como del habla sostenida, con el fin de aprovechar las sinergias y diferencias existentes entre ambas. En el análisis del habla continua se tomo como punto de partida un esquema que ya fue evaluado con anterioridad, y sobre el cual se ha tratado la evaluación y optimización de la representación del habla, así como la caracterización de los patrones específicos asociados al SAHS. Ello ha evidenciado la conexión entre el SAHS y los elementos fundamentales de la señal de voz: los formantes. Los resultados obtenidos demuestran que el éxito de estos sistemas se debe, fundamentalmente, a la capacidad de estas representaciones para describir dichas componentes, obviando las dimensiones ruidosas o con poca capacidad discriminativa. El esquema resultante ofrece una tasa de error por debajo del 18%, sirviéndose de clasificadores notablemente menos complejos que los descritos en el estado del arte y de una única grabación de voz de corta duración. En relación a la conexión entre el SAHS y los patrones observados, fue necesario considerar las diferencias inter- e intra-grupo, centrándonos en la articulación característica del locutor, sustituyendo los complejos modelos de clasificación por el estudio de los promedios espectrales. El resultado apunta con claridad hacia ciertas regiones del eje de frecuencias, sugiriendo la existencia de un estrechamiento sistemático en la sección del tracto en la región de la orofaringe, ya prevista en la patogénesis de este síndrome. En cuanto al habla sostenida, se han reproducido los estudios realizados sobre el habla continua en grabaciones de la vocal /a/ sostenida. Los resultados son cualitativamente análogos a los anteriores, si bien en este caso las tasas de clasificación resultan ser más bajas. Con el objetivo de identificar el sentido de este resultado se reprodujo el estudio de los promedios espectrales y de la variabilidad inter e intra-grupo. Ambos estudios mostraron importantes diferencias con los anteriores que podrían explicar estos resultados. Sin embargo, el habla sostenida ofrece otras oportunidades al establecer un entorno controlado para el estudio de la fonación, que también había sido identificada como una fuente de información para la detección del SAHS. De su estudio se pudo observar que, en el conjunto de datos disponibles, no existen variaciones que pudieran asociarse fácilmente con la fonación. Únicamente aquellas dimensiones que describen la distribución de energía a lo largo del eje de frecuencia evidenciaron diferencias significativas, apuntando, una vez más, en la dirección de las resonancias espectrales. Analizados los resultados anteriores, la Tesis afronta la fusión de ambas fuentes de información en un único sistema de clasificación. Con ello es posible mejorar las tasas de clasificación, bajo la hipótesis de que la información presente en el habla continua y el habla sostenida es fundamentalmente distinta. Esta tarea se realizo a través de un sencillo esquema de fusión que obtuvo un 88.6% de aciertos en clasificación (tasa de error del 11.4%), lo que representa una mejora significativa respecto al estado del arte. Finalmente, la combinación de este clasificador con los predictores utilizados por los especialistas clínicos ofreció una tasa del 91.3% (tasa de error de 8.7%), que se encuentra dentro del margen ofrecido por esquemas más costosos e intrusivos, y que a diferencia del propuesto, no pueden ser utilizados en la evaluación previa de los pacientes. Con todo, la Tesis ofrece una visión clara sobre la relación entre el SAHS y el habla, evidenciando el grado de madurez alcanzado por la tecnología del habla en la caracterización y detección del SAHS, poniendo de manifiesto que su uso para la evaluación de los pacientes ya sería posible, y dejando la puerta abierta a futuras investigaciones que continúen el trabajo aquí iniciado. ABSTRACT This Thesis explores the potential of speech technologies for the detection of clinical disorders connected to the upper airway. The study of speech traditionally covers both the production process and post processing of the signals involved, from the speaker up to the listener, offering an alternative path to study these pathologies. The fact that utterances embed not just the encoded message but also information about the speaker, has motivated the development of automatic systems oriented to the identification and verificaton the speaker’s identity. These have recently been boosted and reoriented either towards the characterization of traits that are common to several speakers, or to the differences between records of the same speaker collected under different conditions. The first are particularly relevant to this Thesis as these patterns could reveal the presence of features that are related to a common condition shared among different speakers, regardless of their identity. Such is the case faced in this Thesis, where the traits identified would relate to a particular pathology, directly connected to the speech production system. The Obstructive Sleep Apnea syndrome (OSA) is a paradigmatic case for analysis. It is a disorder with high prevalence among adults and affecting a larger number of them as they grow older. Patients suffering from this disorder experience episodes of involuntary cessation of breath during sleep that may last a few seconds and reproduce throughout the night, preventing proper rest. In the case of obstructive apnea, these episodes are related to the collapse of the pharynx, which interrupts the air flow. Currently, OSA diagnosis is done through a polysomnographic study, which focuses on the analysis of apnea episodes during sleep, requiring the patient to stay at the hospital for the whole night. The complexity and high cost of the procedures involved, combined with the waiting lists, have evidenced the need for screening techniques, which perhaps would not achieve outstanding performance rates but would allow clinicians to reorganize these lists ranking patients according to the severity of their condition. Among others, imaging diagnosis and anthropometric characterization of patients have evidenced the existence of anatomical patterns related to OSA that have direct influence on speech. Contributions devoted to the study of how this disorder affects scpeech are scarce and somehow contradictory. However, since the late 1980s the existence of specific patterns related to articulation, phonation and resonance is known. By that time these descriptions were virtually useless when coming to the development of an automatic system, but pointed out the existence of a link between speech and OSA. In recent years automatic processing techniques have evolved and are now able to identify significant differences in the speech of OSAS patients when compared to records from healthy subjects. Nevertheless, little is known about the connection between these new results with those published in the past and the pathogenesis of the OSA syndrome. This Thesis is aimed to progress beyond the previous research done in this area by addressing: the study of how OSA affects patients’ speech, the enhancement of automatic OSA classification based on speech analysis, and its integration with the information embedded in the predictors generally used by clinicians in preliminary patients’ examination. The first two tasks, though may appear symbiotic at first, are quite different. While studying the connection between speech and OSA requires simple narrow models that can be easily interpreted, classification requires larger models including a large number dimensions for the characterization and posterior identification of the observed patterns. Anyhow, it is clear that any progress made in the first task should allow us to improve our performance on the second one, and that the incorporation of the predictors used by clinicians shall contribute in this same direction. The Thesis considers both continuous and sustained speech analysis, to exploit the synergies and differences between them. On continuous speech analysis, a conventional speech processing scheme, designed and evaluated before this Thesis, was taken as a baseline. Over this initial system several alternative representations of the speech information were proposed, optimized and tested to select those more suitable for the characterization of OSA-specific patterns. Evidences were found on the existence of a connection between OSA and the fundamental constituents of the speech: the formants. Experimental results proved that the success of the proposed solution is well explained by the ability of speech representations to describe these specific OSA-related components, ignoring the noisy ones as well those presenting low discrimination capabilities. The resulting scheme obtained a 18% error rate, on a classification scheme significantly less complex than those described in the literature and operating on a single speech record. Regarding the connection between OSA and the observed patterns, it was necessary to consider inter-and intra-group differences for this analysis, and to focus on the articulation, replacing the complex classification models by the long-term average spectra. Results clearly point to certain regions on the frequency axis, suggesting the existence of a systematic narrowing in the vocal tract section at the oropharynx. This was already described in the pathogenesis of this syndrome. Regarding sustained speech, similar experiments as those conducted on continuous speech were reproduced on sustained phonations of vowel / a /. Results were qualitatively similar to the previous ones, though in this case perfomance rates were found to be noticeably lower. Trying to derive further knowledge from this result, experiments on the long-term average spectra and intraand inter-group variability ratios were also reproduced on sustained speech records. Results on both experiments showed significant differences from the previous ones obtained from continuous speech which could explain the differences observed on peformance. However, sustained speech also provided the opportunity to study phonation within the controlled framework it provides. This was also identified in the literature as a source of information for the detection of OSA. In this study it was found that, for the available dataset, no sistematic differences related to phonation could be found between the two groups of speakers. Only those dimensions which relate energy distribution along the frequency axis provided significant differences, pointing once again towards the direction of resonant components. Once classification schemes on both continuous and sustained speech were developed, the Thesis addressed their combination into a single classification system. Under the assumption that the information in continuous and sustained speech is fundamentally different, it should be possible to successfully merge the two of them. This was tested through a simple fusion scheme which obtained a 88.6% correct classification (11.4% error rate), which represents a significant improvement over the state of the art. Finally, the combination of this classifier with the variables used by clinicians obtained a 91.3% accuracy (8.7% error rate). This is within the range of alternative, but costly and intrusive schemes, which unlike the one proposed can not be used in the preliminary assessment of patients’ condition. In the end, this Thesis has shed new light on the underlying connection between OSA and speech, and evidenced the degree of maturity reached by speech technology on OSA characterization and detection, leaving the door open for future research which shall continue in the multiple directions that have been pointed out and left as future work.

Vocal tract settings in speakers suffering from obstructive sleep apnea síndrome

Automatic systems based on speech signal analysis for the early dete ction of obstructive sleep apnea (OSA) have achieved fairly high performance rates in recent years. However, a satisfactory explanation of these results has not been available. This presentation aims at explaining via an examination of the long-term spectra of OSA patients and normal control speakers these systems’ ability to discover OSA speakers on the base of all-purpose cepstral coefficients. An in terpretation of the long- term spectra in terms of the underlying tract settings suggests that the speech of OSA patients is characterized by a pharyngeal narrowing that may be captured by acoustic cues of the spectral contour of windowed speech frames. A novel interpretation of long-term spectra in terms of the first principal component of the temporal sequence of short-term amplitude-spectra is also discussed.

GMM-based classifiers for the automatic detection of obstructive sleep apnea

The aim of automatic pathological voice detection systems is to serve as tools, to medical specialists, for a more objective, less invasive and improved diagnosis of diseases. In this respect, the gold standard for those system include the usage of a optimized representation of the spectral envelope, either based on cepstral coefficients from the mel-scaled Fourier spectral envelope (Mel-Frequency Cepstral Coefficients) or from an all-pole estimation (Linear Prediction Coding Cepstral Coefficients) forcharacterization, and Gaussian Mixture Models for posterior classification. However, the study of recently proposed GMM-based classifiers as well as Nuisance mitigation techniques, such as those employed in speaker recognition, has not been widely considered inpathology detection labours. The present work aims at testing whether or not the employment of such speaker recognition tools might contribute to improve system performance in pathology detection systems, specifically in the automatic detection of Obstructive Sleep Apnea. The testing procedure employs an Obstructive Sleep Apnea database, in conjunction with GMM-based classifiers looking for a better performance. The results show that an improved performance might be obtained by using such approach.