IQ Classification via Brainwave Features: Review on Artificial Intelligence Techniques

Intelligence study is one of keystone to distinguish individual differences in cognitive psychology. Conventional psychometric tests are limited in terms of assessment time, and existence of biasness issues. Apart from that, there is still lack in knowledge to classify IQ based on EEG signals and intelligent signal processing (ISP) technique. ISP purpose is to extract as much information as possible from signal and noise data using learning and/or other smart techniques. Therefore, as a first attempt in classifying IQ feature via scientific approach, it is important to identify a relevant technique with prominent paradigm that is suitable for this area of application. Thus, this article reviews several ISP approaches to provide consolidated source of information. This in particular focuses on prominent paradigm that suitable for pattern classification in biomedical area. The review leads to selection of ANN since it has been widely implemented for pattern classification in biomedical engineering

Advanced bioimpedance signal processing techniques for hemodynamic monitoring during anesthesia

Aplicat embargament des de la data de defensa fins els maig 2020.Cardiac output (CO) defines the blood flow arriving from the heart to the different organs in the body and it is thus a primary determinant of global 02 transport. Cardiac output has traditionally been measured using invasive methods, whose risk sometimes exceeds the advantages of a cardiac output monitoring. In this context, the minimization of risk in new noninvasive technologies for CO monitoring could translate into major advantages for clinicians, hospitals and patients: ease of usage and availability, reduced recovery time, and improved patient outcome. Impedance Cardiography (ICG) is a promising noninvasive technology for cardiac output monitoring but available information on the ICG signals is more scare than other physiological signals such as the electrocardiogram (ECG). The present Doctoral Thesis contributes to the development of signal treatment techniques for the ICG in order to create an innovative hemodynamic monitor. First, an extensive literature review is provided regarding the basics of the clinical background in which cardiac output monitoring is used and concerning the state of the art of cardiac output monitors on the market. This Doctoral Thesis has produced a considerable amount of clinical data which is also explained in detail. These clinical data are also useful to complement the theoretical explanation of patient indices such as heart rate variability, blood flow and blood pressure. In addition, a new method to create synthetic biomedical signals with known time-frequency characteristics is introduced. One of the first analysis in this Doctoral Thesis studies the time difference between peak points of the heart beats in the ECG and the ICG: the RC segment. This RC segment is a measure of the time delay between electrical and mechanical activity of the heart. The relationship of the RC segment with blood pressure and heart interval is analyzed. The concordance of beat durations of both the electrocardiogram and the impedance cardiogram is one of the key results to develop new artefact detection algorithms and the RC could also have an impact in describing the hemodynamics of a patient. Time-frequency distributions (TFDs) are also used to characterize how the frequency content in impedance cardiography signals change with time. Since TFDs are calculated using concrete kernels, a new method to select the best kernel by using synthetic signals is presented. Optimized TFDs of ICG signals are then calculated to extract severa! features which are used to discriminate between different anesthesia states in patients undergoing surgery. TFD-derived features are also used to describe the whole surgical operations. Relationships between TFD-derived features are analyzed and prediction models for cardiac output are designed. These prediction models prove that the TFD-derived features are related to the patients' cardiac output. Finally, a validation study for the qCO monitor is presented. The qCO monitor has been designed using sorne of the techniques which are consequence of this Doctoral Thesis. The main outputs of this work have been protected with a patent which has already been filed. As a conclusion, this Doctoral Thesis has produced a considerable amount of clinical data and a variety of analysis and processing techniques of impedance cardiography signals which have been included into commercial medical devices already available on the market.El gasto cardíaco (GC) define el flujo de sangre que llega desde el corazón a los distintos órganos del cuerpo y es, por tanto, un determinante primario del transporte global de oxígeno. Se ha medido tradicionalmente usando métodos invasivos cuyos riesgos excedían en ocasiones las ventajas de su monitorización. En este contexto, la minimización del riesgo de la monitorización del gasto cardíaco en nuevas tecnologías no invasivas podría traducirse en mayores ventajas para médicos, hospitales y pacientes: facilidad de uso, disponibilidad del equipamiento y menor tiempo de recuperación y mejores resultados en el paciente. La impedancio-cardiografía o cardiografía de impedancia (ICG} es una prometedora tecnología no invasiva para la monitorización del gasto cardíaco. Sin embargo, la información disponible sobre las señales de ICG es más escasa que otras señales fisiológicas como el electrocardiograma (ECG). La presente Tesis Doctoral contribuye al desarrollo de técnicas de tratamiento de señal de ICG para así crear un monitor hemodinámico innovador. En primer lugar, se proporciona una extensa revisión bibliográfica sobre los aspectos básicos del contexto clínico en el que se utiliza la monitorización del gasto cardíaco así como sobre el estado del arte de los monitores de gasto cardíaco que existen en el mercado. Esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos que también se explican en detalle. Dichos datos clínicos también son útiles para complementar las explicaciones teóricas de los índices de paciente de variabilidad cardíaca y el flujo y la presión sanguíneos. Además, se presenta un nuevo método de creación de señales sintéticas biomédicas con características de tiempo-frecuencia conocidas. Uno de los primeros análisis de esta Tesis Doctoral estudia la diferencia temporal entre los picos de los latidos cardíacos del ECG y del ICG: el segmento RC. Este segmento RC es una medida del retardo temporal entre la actividad eléctrica y mecánica del corazón. Se analiza la relación del segmento RC con la presión arterial y el intervalo cardíaco. La concordancia entre la duración de los latidos del ECG y del ICG es uno de los resultados claves para desarrollar nuevos algoritmos de detección de artefactos y el segmento RC también podría ser relevante en la descripción de la hemodinámica de los pacientes. Las distribuciones de tiempo-frecuencia (TFD, por sus siglas en inglés) se utilizan para caracterizar cómo el contenido de las señales de impedancia cardiográfica cambia con el tiempo. Dado que las TFDs deben calcularse usando núcleos (kernels, en inglés) concretos, se presenta un nuevo método para seleccionar el mejor núcleo mediante el uso de señales sintéticas. Las TFDs de ICG optimizadas se calculan para extraer distintas características que son usadas para discriminar entre los diferentes estados de anestesia en pacientes sometidos a procesos quirúrgicos. Las características derivadas de las distribuciones de tiempo-frecuencia también son utilizadas para describir las operaciones quirúrgicas durante toda su extensión temporal. La relación entre dichas características son analizadas y se proponen distintos modelos de predicción para el gasto cardíaco. Estos modelos de predicción demuestran que las características derivadas de las distribuciones tiempo-frecuencia de señales de ICG están relacionadas con el gasto cardíaco de los pacientes. Finalmente, se presenta un estudio de validación del monitor qCO, diseñado con alguna de las técnicas que son consecuencia de esta Tesis Doctoral. Las principales conclusiones de este trabajo han sido protegidas con una patente que ya ha sido registrada. Como conclusión, esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos y una variedad de técnicas de procesado y análisis de señales de cardiografía de impedancia que han sido incluidas en dispositivos biomédicos disponibles en el mercadoPostprint (published version

Advanced bioimpedance signal processing techniques for hemodynamic monitoring during anesthesia

Cardiac output (CO) defines the blood flow arriving from the heart to the different organs in the body and it is thus a primary determinant of global 02 transport. Cardiac output has traditionally been measured using invasive methods, whose risk sometimes exceeds the advantages of a cardiac output monitoring. In this context, the minimization of risk in new noninvasive technologies for CO monitoring could translate into major advantages for clinicians, hospitals and patients: ease of usage and availability, reduced recovery time, and improved patient outcome. Impedance Cardiography (ICG) is a promising noninvasive technology for cardiac output monitoring but available information on the ICG signals is more scare than other physiological signals such as the electrocardiogram (ECG). The present Doctoral Thesis contributes to the development of signal treatment techniques for the ICG in order to create an innovative hemodynamic monitor. First, an extensive literature review is provided regarding the basics of the clinical background in which cardiac output monitoring is used and concerning the state of the art of cardiac output monitors on the market. This Doctoral Thesis has produced a considerable amount of clinical data which is also explained in detail. These clinical data are also useful to complement the theoretical explanation of patient indices such as heart rate variability, blood flow and blood pressure. In addition, a new method to create synthetic biomedical signals with known time-frequency characteristics is introduced. One of the first analysis in this Doctoral Thesis studies the time difference between peak points of the heart beats in the ECG and the ICG: the RC segment. This RC segment is a measure of the time delay between electrical and mechanical activity of the heart. The relationship of the RC segment with blood pressure and heart interval is analyzed. The concordance of beat durations of both the electrocardiogram and the impedance cardiogram is one of the key results to develop new artefact detection algorithms and the RC could also have an impact in describing the hemodynamics of a patient. Time-frequency distributions (TFDs) are also used to characterize how the frequency content in impedance cardiography signals change with time. Since TFDs are calculated using concrete kernels, a new method to select the best kernel by using synthetic signals is presented. Optimized TFDs of ICG signals are then calculated to extract severa! features which are used to discriminate between different anesthesia states in patients undergoing surgery. TFD-derived features are also used to describe the whole surgical operations. Relationships between TFD-derived features are analyzed and prediction models for cardiac output are designed. These prediction models prove that the TFD-derived features are related to the patients' cardiac output. Finally, a validation study for the qCO monitor is presented. The qCO monitor has been designed using sorne of the techniques which are consequence of this Doctoral Thesis. The main outputs of this work have been protected with a patent which has already been filed. As a conclusion, this Doctoral Thesis has produced a considerable amount of clinical data and a variety of analysis and processing techniques of impedance cardiography signals which have been included into commercial medical devices already available on the market.El gasto cardíaco (GC) define el flujo de sangre que llega desde el corazón a los distintos órganos del cuerpo y es, por tanto, un determinante primario del transporte global de oxígeno. Se ha medido tradicionalmente usando métodos invasivos cuyos riesgos excedían en ocasiones las ventajas de su monitorización. En este contexto, la minimización del riesgo de la monitorización del gasto cardíaco en nuevas tecnologías no invasivas podría traducirse en mayores ventajas para médicos, hospitales y pacientes: facilidad de uso, disponibilidad del equipamiento y menor tiempo de recuperación y mejores resultados en el paciente. La impedancio-cardiografía o cardiografía de impedancia (ICG} es una prometedora tecnología no invasiva para la monitorización del gasto cardíaco. Sin embargo, la información disponible sobre las señales de ICG es más escasa que otras señales fisiológicas como el electrocardiograma (ECG). La presente Tesis Doctoral contribuye al desarrollo de técnicas de tratamiento de señal de ICG para así crear un monitor hemodinámico innovador. En primer lugar, se proporciona una extensa revisión bibliográfica sobre los aspectos básicos del contexto clínico en el que se utiliza la monitorización del gasto cardíaco así como sobre el estado del arte de los monitores de gasto cardíaco que existen en el mercado. Esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos que también se explican en detalle. Dichos datos clínicos también son útiles para complementar las explicaciones teóricas de los índices de paciente de variabilidad cardíaca y el flujo y la presión sanguíneos. Además, se presenta un nuevo método de creación de señales sintéticas biomédicas con características de tiempo-frecuencia conocidas. Uno de los primeros análisis de esta Tesis Doctoral estudia la diferencia temporal entre los picos de los latidos cardíacos del ECG y del ICG: el segmento RC. Este segmento RC es una medida del retardo temporal entre la actividad eléctrica y mecánica del corazón. Se analiza la relación del segmento RC con la presión arterial y el intervalo cardíaco. La concordancia entre la duración de los latidos del ECG y del ICG es uno de los resultados claves para desarrollar nuevos algoritmos de detección de artefactos y el segmento RC también podría ser relevante en la descripción de la hemodinámica de los pacientes. Las distribuciones de tiempo-frecuencia (TFD, por sus siglas en inglés) se utilizan para caracterizar cómo el contenido de las señales de impedancia cardiográfica cambia con el tiempo. Dado que las TFDs deben calcularse usando núcleos (kernels, en inglés) concretos, se presenta un nuevo método para seleccionar el mejor núcleo mediante el uso de señales sintéticas. Las TFDs de ICG optimizadas se calculan para extraer distintas características que son usadas para discriminar entre los diferentes estados de anestesia en pacientes sometidos a procesos quirúrgicos. Las características derivadas de las distribuciones de tiempo-frecuencia también son utilizadas para describir las operaciones quirúrgicas durante toda su extensión temporal. La relación entre dichas características son analizadas y se proponen distintos modelos de predicción para el gasto cardíaco. Estos modelos de predicción demuestran que las características derivadas de las distribuciones tiempo-frecuencia de señales de ICG están relacionadas con el gasto cardíaco de los pacientes. Finalmente, se presenta un estudio de validación del monitor qCO, diseñado con alguna de las técnicas que son consecuencia de esta Tesis Doctoral. Las principales conclusiones de este trabajo han sido protegidas con una patente que ya ha sido registrada. Como conclusión, esta Tesis Doctoral ha producido una considerable cantidad de datos clínicos y una variedad de técnicas de procesado y análisis de señales de cardiografía de impedancia que han sido incluidas en dispositivos biomédicos disponibles en el mercad

Advancing practice in critical care nursing.

This thesis presents a body of publications in the area of critical care nursing, for the consideration of the award Doctor of Philosophy by publication. The publications and their dissemination herein contribute to a new and original body of knowledge within critical care nursing practice. This thesis aims to demonstrate how an original contribution to the advancement of critical care practice has developed through an on-going integration of academic and practice work and has led to the development of a model for advancing practice. Based on the know-that and know-how framework of advanced knowledge, consideration is given how this approach could be better developed to incorporate other dimensions attributed to experiential learning, namely pattern recognition and an exemplar of the knowing-how knowing-that framework is offered. However, it emerged that there are problems with advancing practice because it is considered the work of the advanced practitioner, yet it is contended that there needs to be a process which allows individuals to advance their own practice. Therefore, it was necessary to develop a working definition of advancing practice not only to map professional advancement of critical care nursing practice and how published works illustrate this, but to offer model of knowledge integration based around theoretical, practical, reflective and reflexive practice and supervisory support to enable individual practitioners the framework to advance practice. This thesis is presented in three chapters: Introduction, Body of Work and The Way Forward. In the first chapter, an overview of the origins and trends of advanced nursing practice and the emergence of advancing nursing practice in critical care. The purpose of this first section, however, is not to engage in the politico-professional debate on the meaning of advanced practice, because this is well developed within the literature, but is to set the scene in the context of published work. By using a narrative approach as a journey of personal discovery, a description of how published works illustrate progress in this respect and show the advancing of critical care practice.The second chapter not only comprises publications with regard to critical care nursing practice but also presents a detailed critique of these publications and their contribution to advancing critical care nursing practice and knowledge. Moreover this discussion identifies three themes which are further developed into the classification of knowledge attributable to advancing practice. In the concluding chapter, recommendations for the way forward are discussed with the development of a critical care nursing knowledge integration model. An exemplar of the model demonstrates that advancing practice in critical care is a continual process of development, analysis and practice that advances the knowledge and skill of critical care nursing. More importantly, it is the integration of all these facets that allows for the growth of the individual to become an advanced practitioner. In summary, this thesis represents a portfolio of work that makes an original contribution to critical care nursing knowledge. The product of this thesis is the development of a knowledge integration model as the basis for advancing practice: