ObjectiveThe aim of this pilot study was to evaluate the feasibility of surface electromyographic signal derived indexes for the prediction of weaning outcomes among mechanically ventilated subjects after cardiac surgery.MethodsA sample of 10 postsurgical adult subjects who received cardiovascular surgery that did not meet the criteria for early extubation were included. Surface electromyographic signals from diaphragm and ventilatory variables were recorded during the weaning process, with the moment determined by the medical staff according to their expertise. Several indexes of respiratory muscle expenditure from surface electromyography using linear and non-linear processing techniques were evaluated. Two groups were compared: successfully and unsuccessfully weaned patients.ResultsThe obtained indexes allow estimation of the diaphragm activity of each subject, showing a correlation between high expenditure and weaning test failure.ConclusionSurface electromyography is becoming a promising procedure for assessing the state of mechanically ventilated patients, even in complex situations such as those that involve a patient after cardiovascular surgery.
Electroencephalographic analysis techniques have become a very useful tool to assess brain activity and interactions between cerebral regions, that is, the so-called cerebral connectivity analysis. The effects of some drugs have, so far, been studied using spectral analysis and, to a lesser extent, some linear and nonlinear connectivity techniques. New indexes have recently been designed based on assumptions that make them more robust against volume conduction effects that could yield to spurious connectivity results.\ud These new indexes such as the imaginary coherence (IC) [Nolte et al., 2004], the phase-lag index (PLI) [Stam et al., 2007] and the weighted phase-lag index (WPLI) [Vinck et al., 2011] have proven very useful in several fields, for example in characterizing electroencephalographic (EEG) and magnetoencephalographic (MEG) activity of Alzheimer’s Disease patients compared to healthy controls.\ud However, these techniques have not been applied to study the effect of drugs on the brain. The main purpose of the current work was to assess the suitability and effectiveness of these innovative indexes to study the brain connectivity under psychoactive drug treatment, and concretely, the effects of a single dose of alprazolam, a short-acting drug of the benzodiazepine family. \ud Alprazolam is extensively prescribed for the treatment of anxiety and panic disorders, and peak plasma concentrations are obtained between 0.5 and 2 hours after intake [Greenblat and Wright, 1993]. Being a benzodiazepines, alprazolam induces an enhancement of the inhibitory pathways through their activity on the GABA A receptor complex, favouring the entrance to chloride ions into the neurons [Haefely, 1990]. Due to the enhancement of the inhibitory pathways a weakening or even an impairment of functional connectivity could be hypothesizedPostprint (author's final draft
Most biological systems are complex and consist of several interconnected parts whose links can contain additional information which can be hidden from the observer. As a result of the interactions between elements, emergent properties that cannot be explained by the characteristics of isolated elements can arise. Current clinical applications record a high number of different signals that contain information about these physiological systems, providing multichannel data whose interactions can be studied by classical reference methods, generally linear, as the correlation analysis and spectral coherence, and other nonlinear methods that are being defined and developed during recent years, such as nonlinear prediction, entropies, mutual information and phase synchronization. The development, improvement and application of new analytical techniques is a field with obvious social and technological interest, especially when performed by noninvasive techniques, which can improve the processes of rehabilitation and clinical therapy, and also help the development of new diagnostic tools. In this thesis new indexes have been defined in order to evaluate: * The coordination of respiratory muscles in healthy subjects and patients with obstructive sleep apnea syndrome (OSAS) during an effort ventilatory protocol. * The effect on functional connectivity of the brain after administration of a psychoactive drug. * The changes caused by Alzheimer's disease (AD) in the connectivity of the brain. Respiratory muscles provide the mechanical energy that supports respiration. The evaluation of interactions between electromyographic (EMG) and mechanomiographic (MMG) signals of different respiratory muscles, genioglossus, sternomastoid and diaphragm, has allowed the discrimination of coordination patterns of OSAS patients with respect to healthy subjects at low, medium and high respiratory effort during while awake. Analysis and characterization of the electroencephalographic (EEG) and magnetoencephalographic (MEG) signals allows the understanding of brain function to assist in the process of clinical diagnosis of disorders in neurology, psychiatry and pharmacology. In this thesis the interactions within and between different brain regions have been assessed, using new nonlinear indexes which have managed to reflect changes over time in the brain after administration of alprazolam, and to characterize andto differentiate brain connectivity of AD patients with respect to healthy subjects. La mayoría de sistemas biológicos son sistemas complejos que constan de diversas partes interconectadas cuyos vínculos pueden contener información adicional y oculta al observador. Como resultado de estas interacciones entre elementos surgen propiedades emergentes, que no pueden explicarse a partir de las características de los elementos aislados. Las aplicaciones clínicas actuales registran un elevado número de señales diferentes que contienen información sobre estos sistemas fisiológicos, cosa que permite disponer de datos multicanal, cuyas interacciones pueden ser estudiadas mediante métodos clásicos de referencia generalmente lineales, como el análisis de correlación y la coherencia espectral, u otros métodos no lineales que están siendo definidos y desarrollados durante los últimos años, como la predicción no lineal, las entropías, la información mutua o la sincronización de fase. El desarrollo, mejora y aplicación de nuevas técnicas de análisis constituye un campo con evidente interés social y tecnológico, en especial cuando se realiza mediante técnicas no invasivas, que puede proporcionar mejoras en los procesos de rehabilitación y terapia clínica, así como contribuir a desarrollar herramientas de ayuda al diagnóstico. En esta tesis se han definido nuevos índices no lineales que han permitido evaluar: * La coordinación de los músculos respiratorios en sujetos sanos y pacientes con síndrome de apnea obstructiva del sueño (SAOS) durante un protocolo ventilatorio de esfuerzo. * El efecto en la conectividad funcional del cerebro tras la administración de un fármaco psicoactivo. * Los cambios provocados por la enfermedad de Alzheimer (EA) en la conectividad del cerebro. La musculatura respiratoria proporciona la energía mecánica que soporta la respiración. La evaluación de las interacciones entre señales electromiográficas (EMG) y mecanomiográficas (MMG) de diferentes músculos respiratorios -geniogloso, esternocleidomastoideo y diafragma- ha permitido diferenciar el patrón de coordinación de los pacientes con SAOS de los sujetos sanos a niveles bajos, medios y altos de esfuerzo respiratorio durante vigilia. El análisis y caracterización de las señales electroencefalográficas (EEG) y magnetoencefalográficas (MEG) permite la comprensión de la función cerebral para ayudar en el proceso de diagnóstico clínico de disfunciones en neurología, psiquiatría y farmacología. En esta tesis se han evaluado las interacciones en y entre diferentes regiones cerebrales mediante nuevos índices no lineales que han conseguido reflejar los cambios producidos a lo largo del tiempo en el cerebro tras la administración del fármaco alprazolam, así como caracterizar y diferenciar la conectividad cerebral de los pacientes con EA con respecto a sujetos sanos. Las herramientas utilizadas en las aplicaciones mencionadas se basan en las siguientes técnicas de análisis no lineal: * La función de información mutua cruzada, el equivalente no lineal de la función de correlación cruzada, que cuantifica la información compartida entre dos variables aleatorias. * La entropía condicional corregida cruzada, una medida que cuantifica la información restante contenida en una variable aleatoria cuando se conoce totalmente otra variable relacionada, y por lo tanto es una medida complementaria de la información mutua. * La predicción no lineal basada en modelos localmente lineales, una herramienta matemática que permite deducir la evolución de una serie temporal en función de muestras anteriores. Los nuevos índices desarrollados han demostrado la necesidad de evaluar las interacciones en los sistemas biológicos y fisiológicos tanto con métodos lineales como no lineales, para obtener una evaluación más completa de la dinámica subyacente y ayudar en los procesos de diagnóstico de patologías y en el procedimiento de evaluación psicofarmacológica.
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