Positive airway pressure and electrical stimulation methods for obstructive sleep apnea treatment: a patent review (2005-2014)

Producción CientíficaIntroduction. Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a major health problem with significant negative effects on the health and quality of life. Continuous positive airway pressure (CPAP) is currently the primary treatment option and it is considered the most effective therapy for OSAHS. Nevertheless, comfort issues due to improper fit to patient’s changing needs and breathing gas leakage limit the patient’s adherence to treatment. Areas covered. The present patent review describes recent innovations in the treatment of OSAHS related to optimization of the positive pressure delivered to the patient, methods and systems for continuous self-adjusting pressure during inspiration and expiration phases, and techniques for electrical stimulation of nerves and muscles responsible for the airway patency. Expert opinion. In the last years, CPAP-related inventions have mainly focused on obtaining an optimal self-adjusting pressure according to patient’s needs. Despite intensive research carried out, treatment compliance is still a major issue. Hypoglossal electrical nerve stimulation could be an effective secondary treatment option when CPAP primary therapy fails. Several patents have been granted focused on selective stimulation techniques and parameter optimization of the stimulating pulse waveform. Nevertheless, there remain important issues to address, like effectiveness and adverse events due to improper stimulation.Ministerio de Economía y Competitividad (TEC2011-22987)Junta de Castilla y León (VA059U13

Invasive and non-invasive assessment of upper airway obstruction and respiratory effort with nasal airflow and esophageal pressure analysis during sleep

La estimación del esfuerzo respiratorio durante el sueño es de una importancia crítica para la identificación correcta de eventos respiratorios en los trastornos respiratorios del sueño (TRS), el diagnóstico correcto de las patologías relacionadas con los TRS y las decisiones sobre la terapia correspondiente. Hoy en día el esfuerzo respiratorio suele ser estimado mediante la polisomnografía (PSG) nocturna con técnicas imprecisas y mediante la evaluación manual por expertos humanos, lo cual es un proceso laborioso que conlleva limitaciones significativas y errores en la clasificación. El objetivo principal de esta tesis es la presentación de nuevos métodos para la estimación automático, invasiva y no-invasiva del esfuerzo respiratorio y cambios en la obstrucción de las vías aéreas superiores (VAS). En especial, la aplicación de estos métodos debería permitir, entre otras cosas, la diferenciación automática invasiva y no-invasiva de eventos centrales y obstructivos durante el sueño. Con este propósito se diseñó y se obtuvo una base de datos de PSG nocturna completamente nueva de 28 pacientes con medición sistemática de presión esofágica (Pes). La Pes está actualmente considerada como el gold-standard para la estimación del esfuerzo respiratorio y la identificación de eventos respiratorios en los TRS. Es sin embargo una técnica invasiva y altamente compleja, lo cual limita su uso en la rutina clínica. Esto refuerza el valor de nuestra base de datos y la dificultad que ha implicado su adquisición. Todos los métodos de procesado propuestos y desarrollados en esta tesis están consecuentemente validados con la señal gold-standard de Pes para asegurar su validez.En un primer paso, se presenta un sistema automático invasivo para la clasificación de limitaciones de flujo inspiratorio (LFI) en los ciclos inspiratorios. La LFI se ha definido como una falta de aumento en flujo respiratorio a pesar de un incremento en el esfuerzo respiratorio, lo cual suele resultar en un patrón de flujo respiratorio característico (flattening). Un total de 38,782 ciclos respiratorios fueron automáticamente extraídos y analizados. Se propone un modelo exponencial que reproduzca la relación entre Pes y flujo respiratorio de una inspiración y permita la estimación objetiva de cambios en la obstrucción de las VAS. La capacidad de caracterización del modelo se estima mediante tres parámetros de evaluación: el error medio cuadrado en la estimación de la resistencia en la presión pico, el coeficiente de determinación y la estimación de episodios de LFI. Los resultados del modelo son comparados a los de los dos mejores modelos en la literatura. Los resultados finales indican que el modelo exponencial caracteriza la LFI y estima los niveles de obstrucción de las VAS con la mayor exactitud y objetividad. Las anotaciones gold-standard de LFI obtenidas, fueron utilizadas para entrenar, testear y validar un nuevo clasificador automático y no-invasivo de LFI basa en la señal de flujo respiratorio nasal. Se utilizaron las técnicas de Discriminant Analysis, Support Vector Machines y Adaboost para la clasificación no-invasiva de inspiraciones con las características extraídas de los dominios temporales y espectrales de los patrones de flujo inspiratorios. Este nuevo clasificador automático no-invasivo también identificó exitosamente los episodios de LFI, alcanzando una sensibilidad de 0.87 y una especificidad de 0.85. La diferenciación entre eventos respiratorios centrales y obstructivos es una de las acciones más recurrentes en el diagnostico de los TRS. Sin embargo únicamente la medición de Pes permite la diferenciación gold-standard de este tipo de eventos. Recientemente se han propuesto nuevas técnicas para la diferenciación no-invasiva de apneas e hipopneas. Sin embargo su adopción ha sido lenta debido a su limitada validación clínica, ya que la creación manual por expertos humanos de sets gold-standard de validación representa un trabajo laborioso. En esta tesis se propone un nuevo sistema para la diferenciación gold-standard automática y objetiva entre hipopneas obstructivas y centrales. Expertos humanos clasificaron manualmente un total de 769 hypopneas en 28 pacientes para crear un set de validación gold-standard. Como siguiente paso se extrajeron características específicas de cada hipopnea para entrenar y testear clasificadores (Discriminant Analysis, Support Vector Machines y adaboost) para diferenciar entre hipopneas centrales y obstructivas mediante la señal gold-standard Pes. El sistema de diferenciación automática alcanzó resultados prometedores, obteniendo una sensibilidad, una especificad y una exactitud de 0.90. Por lo tanto este sistema parece prometedor para la diferenciación automática, gold-standard de hipopneas centrales y obstructivas. Finalmente se propone un sistema no-invasivo para la diferenciación automática de hipopneas centrales y obstructivas. Se propone utilizar la señal de flujo respiratorio para la diferenciación utilizando características de los ciclos inspiratorios de cada hipopnea, entre ellos los patrones flattening. Este sistema automático no-invasivo es una combinación de los sistemas anteriormente presentados y se valida mediante las anotaciones gold-standard obtenidas mediante la señal de Pes por expertos humanos. Los resultados de este sistema son comparados a los resultados obtenidos por expertos humanos que utilizaron un nuevo algoritmo no-invasivo para la diferenciación manual de hipopneas. Los resultados del sistema automático no-invasivo son prometedores y muestran la viabilidad de la metodología empleada. Una vez haya sido validado extensivamente, se ha propuesto este algoritmo para su utilización en dispositivos de terapia de TRS desarrollados por uno de los socios cooperantes en este proyecto.The assessment of respiratory effort during sleep is of major importance for the correct identification of respiratory events in sleep-disordered breathing (SDB), the correct diagnosis of SDB-related pathologies and the consequent choice of treatment. Currently, respiratory effort is usually assessed in night polysomnography (NPSG) with imprecise techniques and manually evaluated by human experts, resulting in a laborious task with significant limitations and missclassifications.The main objective of this thesis is to present new methods for the automatic, invasive and non-invasive assessment of respiratory effort and changes in upper airway (UA) obstruction. Specifically, the application of these methods should, in between others, allow the automatic invasive and non-invasive differentiation of obstructive and central respiratory events during sleep.For this purpose, a completely new NPSG database consisting of 28 patients with systematic esophageal pressure (Pes) measurement was acquired. Pes is currently considered the gold-standard to assess respiratory effort and identify respiratory events in SDB. However, the invasiveness and complexity of Pes measurement prevents its use in clinical routine, underlining the importance of this new database. . . All the processing methods developed in this thesis will consequently be validated with the gold-standard Pes-signal in order to ensure their clinical validity.In a first step, an (invasive) automatic system for the classification of inspiratory flow limitation (IFL) in the inspiratory cycles is presented.IFL has been defined as a lack of increase in airflow despite increasing respiratory effort, which normally results in a characteristic inspiratory airflow pattern (flattening). A total of 38,782 breaths were extracted and automatically analyzed. An exponential model is proposed to reproduce the relationship between Pes and airflow of an inspiration and achieve an objective assessment of changes in upper airway obstruction. The characterization performance of the model is appraised with three evaluation parameters: mean-squared-error when estimating resistance at peakpressure,coefficient of determination and assessment of IFL episodes. The model's results are compared to the two best-performing models in the literature. The results indicated that the exponential model characterizes IFL and assesses levels of upper airway obstruction with the highest accuracy and objectivity.The obtained gold-standard IFL annotations were then employed to train, test and validate a new automatic, non-invasive IFL classification system by means of the nasal airflow signal. Discriminant Analysis, Support Vector Machines and Adaboost algorithms were employed to objectively classify breaths non-invasively with features extracted from the time and frequency domains of the breaths' flow patterns. The new non-invasive automatic classification system also succeeded identifying IFL episodes, achieving a sensitivity of 0.87 and a specificity of 0.85.The differentiation between obstructive and central respiratory events is one of the most recurrent tasks in the diagnosis of sleep disordered breathing, but only Pes measurement allows the gold-standard differentiation of these events. Recently new techniques have been proposed to allow the non-invasive differentiation of hypopneas. However, their adoption has been slow due to their limited clinical validation, as the creation of manual, gold-standard validation sets by human experts is a cumbersome procedure. In this study, a new system is proposed for an objective automatic, gold-standard differentiation between obstructive and central hypopneas with the esophageal pressure signal. An overall of 769 hypopneas of 28 patients were manually scored by human experts to create a gold-standard validation set. Then, features were extracted from each hypopnea to train and test classifiers (Discriminant Analysis, Support Vector Machines and adaboost classifiers) to differentiate between central and obstructive hypopneas with the gold-standard esophageal pressure signal. The automatic differentiation system achieved promising results, with a sensitivity of 0.82, a specificity of 0.87 and an accuracy of 0.85. Hence, this system seems promising for an automatic, goldstandard differentiation between obstructive and central hypopneas.Finally, a non-invasive system is proposed for the automatic differentiation of central and obstructive hypopneas. Only the airflow signal is used for the differentiation, as features of the inspiratory cycles of the hypopnea, such as the flattening patterns, is used. The automatic, non-invasive system represents a combination of the systems that have been presented before and it was validated with the gold-standard scorings obtained with the Pes-signal by human experts. The outcome is compared to the results obtained by human scorers that applied a new non-invasive algorithm for the manual differentiation of hypopneas. The non-invasive system's results are promising and show the viability of this technique. Once validated, this algorithm has been proposed to be used in therapy devices developed by one of the partner institutions cooperating in this project

An invasive and a noninvasive approach for the automatic differentiation of obstructive and central hypopneas

The automatic differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep-disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events. This study presents a new classifier that automatically differentiates obstructive and central hypopneas with the Pes signal and a new approach for an automatic noninvasive classifierwith nasal airflow. An overall of 28 patients underwent night polysomnography with Pes recording, and a total of 769 hypopneas were manually scored by human experts to create a gold-standard annotation set. Features were automatically extracted fromthe Pes signal to train and test the classifiers (discriminant analysis, support vector machines, and adaboost). After a significantly (p < 0.01) higher incidence of inspiratory flow limitation episodes in obstructive hypopneas was objectively, invasively assessed compared to central hypopneas, the feasibility of an automatic noninvasive classifier with features extracted from the airflow signal was demonstrated. The automatic invasive classifier achieved a mean sensitivity, specificity, and accuracy of 0.90 after a 100-fold cross validation. The automatic noninvasive feasibility study obtained similar hypopnea differentiation results as a manual noninvasive classification algorithm. Hence, both systems seem promising for the automatic differentiation of obstructive and central hypopneas.Peer ReviewedPostprint (published version

Multichannel analysis of normal and continuous adventitious respiratory sounds for the assessment of pulmonary function in respiratory diseases

Premi extraordinari doctorat UPC curs 2015-2016, àmbit d’Enginyeria IndustrialRespiratory sounds (RS) are produced by turbulent airflows through the airways and are inhomogeneously transmitted through different media to the chest surface, where they can be recorded in a non-invasive way. Due to their mechanical nature and airflow dependence, RS are affected by respiratory diseases that alter the mechanical properties of the respiratory system. Therefore, RS provide useful clinical information about the respiratory system structure and functioning. Recent advances in sensors and signal processing techniques have made RS analysis a more objective and sensitive tool for measuring pulmonary function. However, RS analysis is still rarely used in clinical practice. Lack of a standard methodology for recording and processing RS has led to several different approaches to RS analysis, with some methodological issues that could limit the potential of RS analysis in clinical practice (i.e., measurements with a low number of sensors, no controlled airflows, constant airflows, or forced expiratory manoeuvres, the lack of a co-analysis of different types of RS, or the use of inaccurate techniques for processing RS signals). In this thesis, we propose a novel integrated approach to RS analysis that includes a multichannel recording of RS using a maximum of five microphones placed over the trachea and the chest surface, which allows RS to be analysed at the most commonly reported lung regions, without requiring a large number of sensors. Our approach also includes a progressive respiratory manoeuvres with variable airflow, which allows RS to be analysed depending on airflow. Dual RS analyses of both normal RS and continuous adventitious sounds (CAS) are also proposed. Normal RS are analysed through the RS intensity–airflow curves, whereas CAS are analysed through a customised Hilbert spectrum (HS), adapted to RS signal characteristics. The proposed HS represents a step forward in the analysis of CAS. Using HS allows CAS to be fully characterised with regard to duration, mean frequency, and intensity. Further, the high temporal and frequency resolutions, and the high concentrations of energy of this improved version of HS, allow CAS to be more accurately characterised with our HS than by using spectrogram, which has been the most widely used technique for CAS analysis. Our approach to RS analysis was put into clinical practice by launching two studies in the Pulmonary Function Testing Laboratory of the Germans Trias i Pujol University Hospital for assessing pulmonary function in patients with unilateral phrenic paralysis (UPP), and bronchodilator response (BDR) in patients with asthma. RS and airflow signals were recorded in 10 patients with UPP, 50 patients with asthma, and 20 healthy participants. The analysis of RS intensity–airflow curves proved to be a successful method to detect UPP, since we found significant differences between these curves at the posterior base of the lungs in all patients whereas no differences were found in the healthy participants. To the best of our knowledge, this is the first study that uses a quantitative analysis of RS for assessing UPP. Regarding asthma, we found appreciable changes in the RS intensity–airflow curves and CAS features after bronchodilation in patients with negative BDR in spirometry. Therefore, we suggest that the combined analysis of RS intensity–airflow curves and CAS features—including number, duration, mean frequency, and intensity—seems to be a promising technique for assessing BDR and improving the stratification of BDR levels, particularly among patients with negative BDR in spirometry. The novel approach to RS analysis developed in this thesis provides a sensitive tool to obtain objective and complementary information about pulmonary function in a simple and non-invasive way. Together with spirometry, this approach to RS analysis could have a direct clinical application for improving the assessment of pulmonary function in patients with respiratory diseases.Los sonidos respiratorios (SR) se generan con el paso del flujo de aire a través de las vías respiratorias y se transmiten de forma no homogénea hasta la superficie torácica. Dada su naturaleza mecánica, los SR se ven afectados en gran medida por enfermedades que alteran las propiedades mecánicas del sistema respiratorio. Por lo tanto, los SR proporcionan información clínica relevante sobre la estructura y el funcionamiento del sistema respiratorio. La falta de una metodología estándar para el registro y procesado de los SR ha dado lugar a la aparición de diferentes estrategias de análisis de SR con ciertas limitaciones metodológicas que podrían haber restringido el potencial y el uso de esta técnica en la práctica clínica (medidas con pocos sensores, flujos no controlados o constantes y/o maniobras forzadas, análisis no combinado de distintos tipos de SR o uso de técnicas poco precisas para el procesado de los SR). En esta tesis proponemos un método innovador e integrado de análisis de SR que incluye el registro multicanal de SR mediante un máximo de cinco micrófonos colocados sobre la tráquea yla superficie torácica, los cuales permiten analizar los SR en las principales regiones pulmonares sin utilizar un número elevado de sensores . Nuestro método también incluye una maniobra respiratoria progresiva con flujo variable que permite analizar los SR en función del flujo respiratorio. También proponemos el análisis combinado de los SR normales y los sonidos adventicios continuos (SAC), mediante las curvas intensidad-flujo y un espectro de Hilbert (EH) adaptado a las características de los SR, respectivamente. El EH propuesto representa un avance importante en el análisis de los SAC, pues permite su completa caracterización en términos de duración, frecuencia media e intensidad. Además, la alta resolución temporal y frecuencial y la alta concentración de energía de esta versión mejorada del EH permiten caracterizar los SAC de forma más precisa que utilizando el espectrograma, el cual ha sido la técnica más utilizada para el análisis de SAC en estudios previos. Nuestro método de análisis de SR se trasladó a la práctica clínica a través de dos estudios que se iniciaron en el laboratorio de pruebas funcionales del hospital Germans Trias i Pujol, para la evaluación de la función pulmonar en pacientes con parálisis frénica unilateral (PFU) y la respuesta broncodilatadora (RBD) en pacientes con asma. Las señales de SR y flujo respiratorio se registraron en 10 pacientes con PFU, 50 pacientes con asma y 20 controles sanos. El análisis de las curvas intensidad-flujo resultó ser un método apropiado para detectar la PFU , pues encontramos diferencias significativas entre las curvas intensidad-flujo de las bases posteriores de los pulmones en todos los pacientes , mientras que en los controles sanos no encontramos diferencias significativas. Hasta donde sabemos, este es el primer estudio que utiliza el análisis cuantitativo de los SR para evaluar la PFU. En cuanto al asma, encontramos cambios relevantes en las curvas intensidad-flujo yen las características de los SAC tras la broncodilatación en pacientes con RBD negativa en la espirometría. Por lo tanto, sugerimos que el análisis combinado de las curvas intensidad-flujo y las características de los SAC, incluyendo número, duración, frecuencia media e intensidad, es una técnica prometedora para la evaluación de la RBD y la mejora en la estratificación de los distintos niveles de RBD, especialmente en pacientes con RBD negativa en la espirometría. El método innovador de análisis de SR que se propone en esta tesis proporciona una nueva herramienta con una alta sensibilidad para obtener información objetiva y complementaria sobre la función pulmonar de una forma sencilla y no invasiva. Junto con la espirometría, este método puede tener una aplicación clínica directa en la mejora de la evaluación de la función pulmonar en pacientes con enfermedades respiratoriasAward-winningPostprint (published version

Detection and Assessment of Sleep-Disordered Breathing with Special Interest of Prolonged Partial Obstruction

Sleep-disordered breathing (SDB) has become more common and puts more strain on public health services than ever before. Obstructive sleep apnea (OSA) and its health consequences such as different cardiovascular diseases are nowadays well recognized. In addition to OSA, attention has recently been paid to another SDB; prolonged partial obstruction. However, it is often undiagnosed and easily left untreated because of the low number of respiratory events during polysomnography recording. This patient group has found to present with more atypical subjective symptoms than OSA patients.Polysomnography (PSG) is considered to be the gold standard in reference methods in SDB diagnostics. PSG is a demanding and laborious multichannel recording method and often requires subjects to spend one night in a sleep laboratory. There is long tradition in Finland to use mattress sensors in SDB diagnostics. Recently, smaller electromechanical film transducer (Emfit) mattresses have replaced the old Static Charge-Sensitive Bed (SCSB) mattresses. However, a proper clinical validation of Emfit mattresses in SDB diagnostics has not been carried out.In this work, the use of Emfit recording in the detection of sleep apneas, hypopneas, and prolonged partial obstruction with increased respiratory effort was evaluated. The general aim of the thesis is to develop and improve the diagnostic methods for sleep-related breathing disorders.Comparisons with both PSG with nasal pressure recording and transesophageal pressure were made. Special attention was paid to the existence of the spiking phenomenon in the Emfit mattress in relation to changes in negative intrathoracic pressure in estimating increased respiratory effort. This entails monitoring the esophageal pressure as a part of nocturnal polysomnography. The recording method is demanding and uncomfortable and is usually not used with ordinary sleep laboratory patients. Thus, reliable and easy indirect quantification methods for respiratory effort are needed in clinical work. According to the results presented in this work, the Emfit signal reveals increased respiratory effort as well as apneas/hypopneas.To find out the prevalence and consequences of prolonged partial obstruction among sleep laboratory patients was another aim of this thesis. This was done by retrospective analyses of sleep laboratory patients from one year. The prevalence of patients with prolonged partial obstruction was 11%. They were as sleepy as OSA patients, but their life quality was worse, as assessed by a survey. These results, along with the findings of the heart rate variation evaluation carried out in this thesis, suggest that prolonged partial obstruction and OSA should be considered as different entities of SDB.With the Emfit mattress sensor, the SDB types can be differentiated, which is expected to enhance the accuracy of diagnostics. However, there is increasing need for easy and cheap screening methods to evaluate nocturnal breathing. In this respect, the usability of compressed tracheal sound signal scoring in SDB screening was estimated. The method reveals apneas and hypopneas but, according to the present findings, it can also be used in the detection of prolonged partial obstruction. The findings encourage the use of compressed tracheal sound analysis in screening different SDB.The analysis of sleep recordings is still based on a doctor’s subjective and visual estimation. To date, no generally accepted and sufficiently reliable automatic analysis method exists. Robust, automatic quantification methods with easier techniques for non-invasive sleep recording would enable the analysis methods to be also used for screening purposes. In this technology-orientated world, people could take much more responsibility and take care of themselves better by following their own biosignals and by changing their health habits earlier. The need for good sleep as a necessity for good life and health is widely recognized

Airway surgery for obstructive sleep apnea and partial upper airway obstruction during sleep

This study analyzed the feasibility and efficacy of surgical therapies in patients with sleep-disordered breathing ranging from partial upper airway obstruction during sleep to severe obstructive sleep apnea syndrome. The surgical procedures evaluated were tracheostomy, laser-assisted uvulopalatoplasty (LUPP) and uvulopalatopharyngoplasty (UPPP) with laser or ultrasound scalpel. Obstructive sleep apnea and partial upper airway obstruction during sleep were measured with the static charge-sensitive bed (SCSB) and pulse oximeter. The patients with severe obstructive sleep apnea syndrome were treated with tracheostomy. Palatal surgery was performed only if the upper airway narrowing occurred exclusively at the soft palate level in patients with partial upper airway obstruction during sleep. The ultrasound scalpel technique was compared to laser-assisted UPPP. The efficacy of LUPP to reduce partial upper airway obstruction during sleep was assessed and histology of uvulopalatal specimen was compared to body fat distributional parameters and sleep study findings. Tracheostomy was effective therapy in severe obstructive sleep apnea. Partial upper airway obstruction and arterial oxyhemoglobin desaturation index during sleep decreased significantly after LUPP. The minimal retropalatal airway dimension increased and soft palate collapsibility decreased at the level where the velopharyngeal obstruction had occurred before the surgery. Ultrasound scalpel did not offer any significant benefits over the laser-assisted technique, except fewer postoperative haemorrhage events. The loose connective tissue as a manifestation of edema was the only histological finding showing correlation with partial upper airway obstruction parameters of SCSB. Tracheostomy remains a life-saving therapy and also long-term option when adherence to CPAP fails in patients with obstructive sleep apnea syndrome. LUPP effectively reduces partial upper airway obstruction during sleep provided that obstruction at the other levels than the soft palate and uvula were preoperatively excluded. Technically the ultrasound scalpel or laser surgeries are equal. In patients with partial upper airway obstruction the loose connective tissue is more important than fat accumulation in the soft palate. This supports the hypothesis that edema is a primary trigger for aggravation of upper airway narrowing during sleep at the soft palate level and evolution towards partial or complete upper airway obstruction during sleep.Siirretty Doriast

Gender Differences in Obstructive Sleep Apnea

The overall aim of this thesis was to understand gender differences in obstructive sleep apnea (OSA) and use this information to develop a tailored therapy for female patients. Specific aims were to determine whether gender differences commonly reported in the literature are present in mild OSA and upper airway resistance syndrome (UARS) patient groups, and whether symptoms could be linked to respiratory parameters in these groups. The final aim was to develop, test and validate a new AutoSet treatment for female OSA patients. CHAPTER 1 of this thesis provides a detailed review of gender differences in the prevalence, symptoms, clinical experience, and health outcomes of OSA and UARS patients, with a focus on the implications of different scoring rules. CHAPTER 2 reviews of quality of life questionnaires from 259 untreated patients with mild OSA. Females reported statistically significantly higher levels of sleepiness, fatigue, insomnia, and anxiety/depression compared to males. CHAPTER 3 of this thesis reviews polygraphy data from patients with mild OSA. Male patients were found to have significantly more breathing disturbances than females, however many of these difference disappeared when updated scoring criteria were used. Some weak correlations were found between respiratory parameters and symptoms; however, no clear conclusions could be drawn. CHAPTER 4 outlines the development of a new AutoSet device designed for female- specific breathing patterns. The remaining chapters (CHAPTER 5, and CHAPTER 6) of this thesis describe the testing and validation activities undertaken on the AutoSet F, including a clinical trial to test efficacy; a bench test to compare performance against other commercially available devices; a controlled product launch to validate the features of the algorithm; and finally a clinical trial which demonstrated improvements in sleep efficacy and quality of life over a three-month usage period. In summary, this thesis has shown that at the mild end of the OSA spectrum females are more symptomatic than males, even though respiratory differences in the genders are less pronounced than those described in moderate-to-severe patients. An AutoSet designed specifically for female OSA patients was successful in demonstrating efficacy and clinical effectiveness