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

A Pilot Study

Background Alcohol withdrawal syndrome is a potentially life-threatening condition, which can occur when patients with alcohol use disorders undergo general anesthesia. Excitatory amino acids, such as glutamate, act as neurotransmitters and are known to play a key role in alcohol withdrawal syndrome. To understand this process better, we investigated the influence of isoflurane, sevoflurane, and desflurane anesthesia on the profile of excitatory and inhibitory amino acids in the nucleus accumbens (NAcc) of alcohol-withdrawn rats (AWR). Methods Eighty Wistar rats were randomized into two groups of 40, pair-fed with alcoholic or non-alcoholic nutrition. Nutrition was withdrawn and microdialysis was performed to measure the activity of amino acids in the NAcc. The onset time of the withdrawal syndrome was first determined in an experiment with 20 rats. Sixty rats then received isoflurane, sevoflurane, or desflurane anesthesia for three hours during the withdrawal period, followed by one hour of elimination. Amino acid concentrations were measured using chromatography and results were compared to baseline levels measured prior to induction of anesthesia. Results Glutamate release increased in the alcohol group at five hours after the last alcohol intake (p = 0.002). After 140 min, desflurane anesthesia led to a lower release of glutamate (p < 0.001) and aspartate (p = 0.0007) in AWR compared to controls. GABA release under and after desflurane anesthesia was also significantly lower in AWR than controls (p = 0.023). Over the course of isoflurane anesthesia, arginine release decreased in AWR compared to controls (p < 0.001), and aspartate release increased after induction relative to controls (p20min = 0.015 and p40min = 0.006). However, amino acid levels did not differ between the groups as a result of sevoflurane anesthesia. Conclusions Each of three volatile anesthetics we studied showed different effects on excitatory and inhibitory amino acid concentrations. Under desflurane anesthesia, both glutamate and aspartate showed a tendency to be lower in AWR than controls over the whole timecourse. The inhibitory amino acid arginine increased in AWR compared to controls, whereas GABA levels decreased. However, there were no significant differences in amino acid concentrations under or after sevoflurane anesthesia. Under isoflurane, aspartate release increased in AWR following induction, and from 40 min to 140 min arginine release in controls was elevated. The precise mechanisms through which each of the volatile anesthetics affected amino acid concentrations are still unclear and further experimental research is required to draw reliable conclusions

Método de análisis biomecánico de la marcha en pacientes portadores de prótesis de rodilla

El análisis de la marcha ha adquirido en los últimos tiempos un extraordinario desarrollo. En la actualidad la ciencia biomecánica ofrece un gran campo de actuación para el estudio de la patología de la deambulación, aplicando los conocimientos anatómicos, las leyes físicas y la alta tecnología (ordenadores, video, plataformas de fuerza, etc ...) En este estudio, se comparan por medio del análisis del movimiento en tres dimensiones, la dinámica y el comportamiento articular de la marcha normal y de la marcha en el paciente portador de protesis de rodilla unilateral y bilateral, para analizar si se aprecian diferencias en las características generales de la marcha y los cambios evolutivos que provocan estas diferencias y sus posibles repercusiones patológicas. La marcha normal tiene una fase de balanceo, seguida de una fase de apoyo con: choque de talón, apoyo del retropié, apoyo de la planta, rodadura sobre el borde extremo, despegue del talón, despegue del primer dedo. Esta dinámica se acompaña de balanceo de las extremidades superiores para mantener el equilibrio y compensar los momentos de inercia provocados por la zancada

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

Real time geotechnical field data acquistion using a distributed approach

A distributed geotechnical remote analysis of data system (Distributed G-RAD) can benefit both owners and contractors in providing better quality control and assurance on geotechnical projects. The Distributed G-RAD approach involves efficient data acquisition using PDAs with GPS capability, radio frequency identification (RFID) tags for labeling soil samples, laser scanning for measuring lift thickness and volumes of stockpiles and borrow pits. Spatial data storage is provided using a geographic information system (GIS). Portions of this system are already developed while other parts are still being considered. This paper also describes how RFID and laser scanning technologies can be used in the larger Distributed G-RAD system

Neuropsychological effects of chronic low-dose exposure to polychlorinated biphenyls (PCBs): A cross-sectional study

BACKGROUND: Exposure to indoor air of private or public buildings contaminated with polychlorinated biphenyls (PCBs) has raised health concerns in long-term users. This exploratory neuropsychological group study investigated the potential adverse effects of chronic low-dose exposure to specific air-borne low chlorinated PCBs on well-being and behavioral measures in adult humans. METHODS: Thirty employees exposed to indoor air contaminated with PCBs from elastic sealants in a school building were compared to 30 non-exposed controls matched for education and age, controlling for gender (age range 37–61 years). PCB exposure was verified by external exposure data and biological monitoring (PCB 28, 101, 138, 153, 180). Subjective complaints, learning and memory, executive function, and visual-spatial function was assessed by standardized neuropsychological testing. Since exposure status depended on the use of contaminated rooms, an objectively exposed subgroup (N = 16; PCB 28 = 0.20 μg/l; weighted exposure duration 17.9 ± 7 years) was identified and compared with 16 paired controls. RESULTS: Blood analyses indicated a moderate exposure effect size (d) relative to expected background exposure for total PCB (4.45 ± 2.44 μg/l; d = 0.4). A significant exposure effect was found for the low chlorinated PCBs 28 (0.28 ± 0.25 μg/l; d = 1.5) and 101 (0.07 ± 0.09 μg/l; d = 0.7). Although no neuropsychological effects exceeded the adjusted significance level, estimation statistics showed elevated effect sizes for several variables. The objectively exposed subgroup showed a trend towards increased subjective attentional and emotional complaints (tiredness and slowing of practical activities, emotional state) as well as attenuated attentional performance (response shifting and alertness in a cued reaction task). CONCLUSION: Chronic inhalation of low chlorinated PCBs that involved elevated blood levels was associated with a subtle attenuation of emotional well-being and attentional function. Extended research is needed to replicate the potential long-term low PCB effects in a larger sample

Técnicas de secado y resistencia a la tracción de los materiales adhesivos dentinarios

Compara y evalúa la fuerza de adhesión entre superficies dentinarias, experimentando la forma de secar, sin deshidratar la dentina y tratando de evitar a futuro, el utilizar la tradicional técnica de secado con aire comprimido. Se realizó la técnica de secado mecánica, aplicando dos tipos de elementos que absorben la humedad como son el papel tisú y espuma, para así verificar la adhesión del material en la superficie dentinaria. Por tanto, se ha comprobado la resistencia a la tracción de los materiales adhesivos dentinarios utilizando la técnica con espuma, por lo que se ha obtenido valores por encima del estrés de contracción, presentando tos valores de menor dispersión, además presenta manipulación sencilla y fácil, siendo constante el grosor y tamaño de la espuma que se necesit