Modelado dinámico del sistema respiratorio ante incrementos de demanda ventilatoria, enfermedades pulmonares y ventilación mecánica asistida

Respiratory diseases remain one of the leading causes of death and illness in Europe and worldwide. One of the most important is Chronic Obstructive Pulmonary Disease (COPD) associated mainly with chronic bronchitis and pulmonary emphysema. Patients with COPD during acute respiratory failure (ARF) require mechanical ventilation to assist or replace their lung function, where the selection of ventilatory mode and its configuration is an essential step for patient's treatment and recovery.The development of pathophysiological knowledge and technology has generated a wide variety of ventilation modes designed to increase alveolar ventilation, reduce respiratory work, improve the coupling between ventilation and perfusion and optimize oxygenation of arterial blood. In clinical practice, however, many of the benefits they provide are often unused because of: 1) the complexity and diversity of ventilatory modalities and ventilator brands, and 2) the lack of tools to assist in the proper selection and configuration of the ventilatory modes according to the specific characteristics of each patient.Several models of the respiratory system have been studied to enhance knowledge about the mechanism of ventilatory control that the system adopts in normal and pathological conditions and to predict its cardiorespiratory response. However, the connection between the respiratory control system and mechanical ventilators remains an open research field, since it is essential to know and predict properly the respiratory pattern and the parameters that affect it before to set up the ventilator.The main objective of this doctoral thesis is the developed and evaluation of new computational simulators that allow predicting appropriately the respiratory dynamic response of healthy subjects and respiratory patients under ventilatory demands and assisted mechanical ventilation.In this thesis, different models of the respiratory system are analyzed. Modifications in their modeling, adjustments in their parameters and comparative studies were performed in order to properly predict the response of the respiratory system in healthy and pathological subjects during increased ventilatory demand. In addition, a computational and interactive tool, based on a model that integrates the most relevant characteristics of the analyzed models and a model of a mechanical ventilator, has been developed to simulate the interaction between a respiratory patient and a mechanical ventilator.The main contributions of the thesis are:1) A new estimate of respiratory mechanical work with a better physiological meaning and whose minimization allows better prediction of the system control response. 2) A complete respiratory system model that properly predicts both transient and stationary response of a healthy subject under incremental ventilatory demands. This model uses an improved gas exchange and sensing respiratory plant and more appropriate optimization algorithms.3) A complete model of the respiratory system that adequately predicts the response of obstructive and restrictive lung diseases. This model incorporates the simplification of a well-known, detailed and complete respiratory mechanical plant that is approximated quadratically for its computational integration in the model of the previous healthy subject. Mechanical parameters of three submodels for each disease are also proposed. 5) A computer simulator with a friendly and interactive user's interface, which includes the previous analyzed models and a mechanical ventilator model. This tool, which has already been tested for usability, has been successfully used in courses for physicians, researchers and students. With all these tools, it is expected to provide resources that assist physicians in the configuration of mechanical ventilators and understanding the interaction patient-ventilator.Las enfermedades respiratorias son una de las causas principales de muerte y enfermedad en Europa y el mundo. Una de las más importantes es la Enfermedad Pulmonar Obstructiva Crónica (EPOC) asociada principalmente a la bronquitis crónica y al enfisema pulmonar. Los pacientes con EPOC durante una Insuficiencia Respiratoria Aguda (IRA) requieren ventilación mecánica para asistir o sustituir su función pulmonar, donde la selección y configuración del modo ventilatorio constituye un paso esencial durante el tratamiento y la recuperación del paciente. La evolución del conocimiento fisiopatológico y de la tecnología ha generado una gran variedad de modos de ventilación diseñados para aumentar la ventilación alveolar, reducir el trabajo respiratorio, mejorar el acoplamiento entre la ventilación y la perfusión y optimar la oxigenación de la sangre arterial. Sin embargo, en la práctica clínica suelen ser desaprovechados muchos de los beneficios que estos ofrecen debido a: 1) la complejidad y diversidad de modos ventilatorios y marcas de ventiladores, y 2) la falta de herramientas que ayuden a la selección y configuración adecuada de estos en función de las características específicas de cada paciente. Se han estudiado diversos modelos del sistema respiratorio para reforzar el conocimiento sobre el mecanismo de control ventilatorio que dicho sistema adopta en condiciones normales y patológicas. Sin embargo, la unión entre el sistema de control respiratorio y los ventiladores mecánicos sigue siendo un campo de investigación abierto, dado que antes de configurar el ventilador resulta fundamental conocer y predecir apropiadamente su patrón respiratorio y los parámetros que lo afectan. El objetivo principal de esta tesis es el desarrollo y evaluación de nuevos simuladores computacionales que permitan predecir apropiadamente la respuesta dinámica respiratoria de sujetos sanos y enfermos respiratorios ante demandas ventilatorias y ventilación mecánica asistida. En esta tesis diversos modelos del sistema respiratorio son analizados. Modificaciones en su modelado, ajustes en sus parámetros y estudios comparativos fueron realizados con el fin de predecir adecuadamente la respuesta del sistema respiratorio en sujetos sanos y patológicos durante demandas ventilatorias incrementadas. Además, una herramienta computacional, basada en un modelo que integra las características más relevantes de los modelos analizados y de un ventilador mecánico, ha sido desarrollada para simular la interacción paciente-ventilador. Las principales contribuciones de la tesis son: 1) Una nueva estimación del trabajo mecánico respiratorio con una mayor interpretación fisiológica y cuya minimización permite predecir mejor la respuesta del sistema de control. 2) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta tanto en régimen transitorio como estacionario de un sujeto sano ante demandas ventilatorias incrementales. Dicho modelo utiliza una planta respiratoria de intercambio y sensado de gases mejorada y algoritmos de optimización más apropiados. 3) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta de enfermedades pulmonares obstructivas y restrictivas. Dicho modelo incorpora la simplificación de una planta mecánica respiratoria conocida, detallada y completa que se aproxima cuadráticamente para su integración computacional en el modelo del sujeto sano anterior. Parámetros mecánicos de tres submodelos para cada enfermedad son también propuestos 5) Un simulador computacional con una interfaz amigable e interactiva, que incluye el modelo anterior de un paciente y de un ventilador mecánico. Dicha herramienta a la que ya se le han hecho pruebas de usabilidad, ha sido utilizada con éxito en cursos para médicos, investigadores y estudiantes. (...)Postprint (published version

Optimization techniques in respiratory control system models

One of the most complex physiological systems whose modeling is still an open study is the respiratory control system where different models have been proposed based on the criterion of minimizing the work of breathing (WOB). The aim of this study is twofold: to compare two known models of the respiratory control system which set the breathing pattern based on quantifying the respiratory work; and to assess the influence of using direct-search or evolutionary optimization algorithms on adjustment of model parameters. This study was carried out using experimental data from a group of healthy volunteers under CO2 incremental inhalation, which were used to adjust the model parameters and to evaluate how much the equations of WOB follow a real breathing pattern. This breathing pattern was characterized by the following variables: tidal volume, inspiratory and expiratory time duration and total minute ventilation. Different optimization algorithms were considered to determine the most appropriate model from physiological viewpoint. Algorithms were used for a double optimization: firstly, to minimize the WOB and secondly to adjust model parameters. The performance of optimization algorithms was also evaluated in terms of convergence rate, solution accuracy and precision. Results showed strong differences in the performance of optimization algorithms according to constraints and topological features of the function to be optimized. In breathing pattern optimization, the sequential quadratic programming technique (SQP) showed the best performance and convergence speed when respiratory work was low. In addition, SQP allowed to implement multiple non-linear constraints through mathematical expressions in the easiest way. Regarding parameter adjustment of the model to experimental data, the evolutionary strategy with covariance matrix and adaptation (CMA-ES) provided the best quality solutions with fast convergence and the best accuracy and precision in both models. CMAES reached the best adjustment because of its good performance on noise and multi-peaked fitness functions. Although one of the studied models has been much more commonly used to simulate respiratory response to CO2 inhalation, results showed that an alternative model has a more appropriate cost function to minimize WOB from a physiological viewpoint according to experimental data.Postprint (author's final draft

An integrated mathematical model of the cardiovascular and respiratory response to exercise: Model-building and comparison with reported models

The use of physiological models in medicine allows the evaluation of new hypotheses, development of diagnosis and clinical treatment applications, and development of training and medical education tools, as well as medical device design. Although several mathematical models of physiological systems have been presented in the literature, few of them are able to predict the human cardiorespiratory response under physical exercise stimulus adequately. This paper aims to present the building and comparison of an integrated cardiorespiratory model focused on the prediction of the healthy human response under rest and aerobic exercise. The model comprises cardiovascular circulation, respiratory mechanics, and gas exchange system, as well as cardiovascular and respiratory controllers. Every system is based on previously reported physiological models and incorporates reported mechanisms related to the aerobic exercise dynamics. Experimental data of 30 healthy male volunteers undergoing a cardiopulmonary exercise test and simulated data from two of the most current and complete cardiorespiratory models were used to evaluate the performance of the presented model. Experimental design, processing, and exploratory analysis are described in detail. The simulation results were compared against the experimental data in steady state and in transient regime. The predictions of the proposed model closely mimic the experimental data, showing in overall the lowest prediction error (10.35%), the lowest settling times for cardiovascular and respiratory variables, and in general the fastest and similar responses in transient regime. These results suggest that the proposed model is suitable to predict the cardiorespiratory response of healthy adult humans under rest and aerobic exercise conditions.Peer ReviewedPostprint (published version

A novel strategy to fit and validate physiological models: a case study of acardiorespiratory model for simulation of incremental aerobic exercise

Applying complex mathematical models of physiological systems is challenging due to the large number of parameters. Identifying these parameters through experimentation is difficult, and although procedures for fitting and validating models are reported, no integrated strategy exists. Additionally, the complexity of optimization is generally neglected when the number of experimental observations is restricted, obtaining multiple solutions or results without physiological justification. This work proposes a fitting and validation strategy for physiological models with many parameters under various populations, stimuli, and experimental conditions. A cardiorespiratory system model is used as a case study, and the strategy, model, computational implementation, and data analysis are described. Using optimized parameter values, model simulations are compared to those obtained using nominal values, with experimental data as a reference. Overall, a reduction in prediction error is achieved compared to that reported for model building. Furthermore, the behavior and accuracy of all the predictions in the steady state were improved. The results validate the fitted model and provide evidence of the proposed strategy’s usefulness.Peer ReviewedPostprint (published version

Web applications for teaching the respiratory system: content validation

The subject of respiratory mechanics has complex characteristics, functions, and interactions that can be difficult to understand in training and medical education contexts. As such, education strategies based on computational simulations comprise useful tools, but their application in the medical area requires stricter validation processes. This paper shows a statistical and a Delphi validation for two modules of a web application used for respiratory system learning: (I) “Anatomy and Physiology” and (II) “Work of Breathing Indexes”. For statistical validation, population and individual analyses were made using a database of healthy men to compare experimental and model-predicted data. For both modules, the predicted values followed the trend marked by the experimental data in the population analysis, while in the individual analysis, the predicted errors were 9.54% and 25.38% for maximal tidal volume and airflow, respectively, and 6.55%, 9.33%, and 11.77% for rapid shallow breathing index, work of breathing, and maximal inspiratory pressure, respectively. For the Delphi validation, an average higher than 4 was obtained after health professionals evaluated both modules from 1 to 5. In conclusion, both modules are good tools for respiratory system learning processes. The studied parameters behaved consistently with the expressions that describe ventilatory dynamics and were correlated with experimental data; furthermore, they had great acceptance by specialists.Peer ReviewedPostprint (published version

Influence of the number of trials on evoked motor cortical activity in EEG recordings

The data that support the findings of this study are openly available at the following URL/DOI: https://doi.org/10.1371/journal.pone.0182578.Objective. Improvements in electroencephalography enable the study of the localization of active brain regions during motor tasks. Movement-related cortical potentials (MRCPs), and event-related desynchronization (ERD) and synchronization are the main motor-related cortical phenomena/neural correlates observed when a movement is elicited. When assessing neurological diseases, averaging techniques are commonly applied to characterize motor related processes better. In this case, a large number of trials is required to obtain a motor potential that is representative enough of the subject’s condition. This study aimed to assess the effect of a limited number of trials on motor-related activity corresponding to different upper limb movements (elbow flexion/extension, pronation/supination and hand open/close). Approach. An open dataset consisting on 15 healthy subjects was used for the analysis. A Monte Carlo simulation approach was applied to analyse, in a robust way, different typical time- and frequency-domain features, topography, and low-resolution electromagnetic tomography. Main results. Grand average potentials, and topographic and tomographic maps showed few differences when using fewer trials, but shifts in the localization of motor-related activity were found for several individuals. MRCP and beta ERD features were more robust to a limited number of trials, yielding differences lower than 20% for cases with 50 trials or more. Strong correlations between features were obtained for subsets above 50 trials. However, the inter-subject variability increased as the number of trials decreased. The elbow flexion/extension movement showed a more robust performance for a limited number of trials, both in population and in individual-based analysis. Significance. Our findings suggested that 50 trials can be an appropriate number to obtain stable motor-related features in terms of differences in the averaged motor features, correlation, and changes in topography and tomography.This study has been funded by the Ministry of Science and Innovation (MICINN), Spain, under contract PID2020-117751RB-I00. CIBER-BBN is an initiative of the Instituto de Salud Carlos III, Spain. Marta Borràs gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the financial support of her predoctoral Grant FPI-UPC. A B is a Serra Hunter Fellow.Peer ReviewedPostprint (published version

Modelado dinámico del sistema respiratorio ante incrementos de demanda ventilatoria, enfermedades pulmonares y ventilación mecánica asistida

Respiratory diseases remain one of the leading causes of death and illness in Europe and worldwide. One of the most important is Chronic Obstructive Pulmonary Disease (COPD) associated mainly with chronic bronchitis and pulmonary emphysema. Patients with COPD during acute respiratory failure (ARF) require mechanical ventilation to assist or replace their lung function, where the selection of ventilatory mode and its configuration is an essential step for patient's treatment and recovery.The development of pathophysiological knowledge and technology has generated a wide variety of ventilation modes designed to increase alveolar ventilation, reduce respiratory work, improve the coupling between ventilation and perfusion and optimize oxygenation of arterial blood. In clinical practice, however, many of the benefits they provide are often unused because of: 1) the complexity and diversity of ventilatory modalities and ventilator brands, and 2) the lack of tools to assist in the proper selection and configuration of the ventilatory modes according to the specific characteristics of each patient.Several models of the respiratory system have been studied to enhance knowledge about the mechanism of ventilatory control that the system adopts in normal and pathological conditions and to predict its cardiorespiratory response. However, the connection between the respiratory control system and mechanical ventilators remains an open research field, since it is essential to know and predict properly the respiratory pattern and the parameters that affect it before to set up the ventilator.The main objective of this doctoral thesis is the developed and evaluation of new computational simulators that allow predicting appropriately the respiratory dynamic response of healthy subjects and respiratory patients under ventilatory demands and assisted mechanical ventilation.In this thesis, different models of the respiratory system are analyzed. Modifications in their modeling, adjustments in their parameters and comparative studies were performed in order to properly predict the response of the respiratory system in healthy and pathological subjects during increased ventilatory demand. In addition, a computational and interactive tool, based on a model that integrates the most relevant characteristics of the analyzed models and a model of a mechanical ventilator, has been developed to simulate the interaction between a respiratory patient and a mechanical ventilator.The main contributions of the thesis are:1) A new estimate of respiratory mechanical work with a better physiological meaning and whose minimization allows better prediction of the system control response. 2) A complete respiratory system model that properly predicts both transient and stationary response of a healthy subject under incremental ventilatory demands. This model uses an improved gas exchange and sensing respiratory plant and more appropriate optimization algorithms.3) A complete model of the respiratory system that adequately predicts the response of obstructive and restrictive lung diseases. This model incorporates the simplification of a well-known, detailed and complete respiratory mechanical plant that is approximated quadratically for its computational integration in the model of the previous healthy subject. Mechanical parameters of three submodels for each disease are also proposed. 5) A computer simulator with a friendly and interactive user's interface, which includes the previous analyzed models and a mechanical ventilator model. This tool, which has already been tested for usability, has been successfully used in courses for physicians, researchers and students. With all these tools, it is expected to provide resources that assist physicians in the configuration of mechanical ventilators and understanding the interaction patient-ventilator.Las enfermedades respiratorias son una de las causas principales de muerte y enfermedad en Europa y el mundo. Una de las más importantes es la Enfermedad Pulmonar Obstructiva Crónica (EPOC) asociada principalmente a la bronquitis crónica y al enfisema pulmonar. Los pacientes con EPOC durante una Insuficiencia Respiratoria Aguda (IRA) requieren ventilación mecánica para asistir o sustituir su función pulmonar, donde la selección y configuración del modo ventilatorio constituye un paso esencial durante el tratamiento y la recuperación del paciente. La evolución del conocimiento fisiopatológico y de la tecnología ha generado una gran variedad de modos de ventilación diseñados para aumentar la ventilación alveolar, reducir el trabajo respiratorio, mejorar el acoplamiento entre la ventilación y la perfusión y optimar la oxigenación de la sangre arterial. Sin embargo, en la práctica clínica suelen ser desaprovechados muchos de los beneficios que estos ofrecen debido a: 1) la complejidad y diversidad de modos ventilatorios y marcas de ventiladores, y 2) la falta de herramientas que ayuden a la selección y configuración adecuada de estos en función de las características específicas de cada paciente. Se han estudiado diversos modelos del sistema respiratorio para reforzar el conocimiento sobre el mecanismo de control ventilatorio que dicho sistema adopta en condiciones normales y patológicas. Sin embargo, la unión entre el sistema de control respiratorio y los ventiladores mecánicos sigue siendo un campo de investigación abierto, dado que antes de configurar el ventilador resulta fundamental conocer y predecir apropiadamente su patrón respiratorio y los parámetros que lo afectan. El objetivo principal de esta tesis es el desarrollo y evaluación de nuevos simuladores computacionales que permitan predecir apropiadamente la respuesta dinámica respiratoria de sujetos sanos y enfermos respiratorios ante demandas ventilatorias y ventilación mecánica asistida. En esta tesis diversos modelos del sistema respiratorio son analizados. Modificaciones en su modelado, ajustes en sus parámetros y estudios comparativos fueron realizados con el fin de predecir adecuadamente la respuesta del sistema respiratorio en sujetos sanos y patológicos durante demandas ventilatorias incrementadas. Además, una herramienta computacional, basada en un modelo que integra las características más relevantes de los modelos analizados y de un ventilador mecánico, ha sido desarrollada para simular la interacción paciente-ventilador. Las principales contribuciones de la tesis son: 1) Una nueva estimación del trabajo mecánico respiratorio con una mayor interpretación fisiológica y cuya minimización permite predecir mejor la respuesta del sistema de control. 2) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta tanto en régimen transitorio como estacionario de un sujeto sano ante demandas ventilatorias incrementales. Dicho modelo utiliza una planta respiratoria de intercambio y sensado de gases mejorada y algoritmos de optimización más apropiados. 3) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta de enfermedades pulmonares obstructivas y restrictivas. Dicho modelo incorpora la simplificación de una planta mecánica respiratoria conocida, detallada y completa que se aproxima cuadráticamente para su integración computacional en el modelo del sujeto sano anterior. Parámetros mecánicos de tres submodelos para cada enfermedad son también propuestos 5) Un simulador computacional con una interfaz amigable e interactiva, que incluye el modelo anterior de un paciente y de un ventilador mecánico. Dicha herramienta a la que ya se le han hecho pruebas de usabilidad, ha sido utilizada con éxito en cursos para médicos, investigadores y estudiantes. (...

Modelado dinámico del sistema respiratorio ante incrementos de demanda ventilatoria, enfermedades pulmonares y ventilación mecánica asistida

Respiratory diseases remain one of the leading causes of death and illness in Europe and worldwide. One of the most important is Chronic Obstructive Pulmonary Disease (COPD) associated mainly with chronic bronchitis and pulmonary emphysema. Patients with COPD during acute respiratory failure (ARF) require mechanical ventilation to assist or replace their lung function, where the selection of ventilatory mode and its configuration is an essential step for patient's treatment and recovery.The development of pathophysiological knowledge and technology has generated a wide variety of ventilation modes designed to increase alveolar ventilation, reduce respiratory work, improve the coupling between ventilation and perfusion and optimize oxygenation of arterial blood. In clinical practice, however, many of the benefits they provide are often unused because of: 1) the complexity and diversity of ventilatory modalities and ventilator brands, and 2) the lack of tools to assist in the proper selection and configuration of the ventilatory modes according to the specific characteristics of each patient.Several models of the respiratory system have been studied to enhance knowledge about the mechanism of ventilatory control that the system adopts in normal and pathological conditions and to predict its cardiorespiratory response. However, the connection between the respiratory control system and mechanical ventilators remains an open research field, since it is essential to know and predict properly the respiratory pattern and the parameters that affect it before to set up the ventilator.The main objective of this doctoral thesis is the developed and evaluation of new computational simulators that allow predicting appropriately the respiratory dynamic response of healthy subjects and respiratory patients under ventilatory demands and assisted mechanical ventilation.In this thesis, different models of the respiratory system are analyzed. Modifications in their modeling, adjustments in their parameters and comparative studies were performed in order to properly predict the response of the respiratory system in healthy and pathological subjects during increased ventilatory demand. In addition, a computational and interactive tool, based on a model that integrates the most relevant characteristics of the analyzed models and a model of a mechanical ventilator, has been developed to simulate the interaction between a respiratory patient and a mechanical ventilator.The main contributions of the thesis are:1) A new estimate of respiratory mechanical work with a better physiological meaning and whose minimization allows better prediction of the system control response. 2) A complete respiratory system model that properly predicts both transient and stationary response of a healthy subject under incremental ventilatory demands. This model uses an improved gas exchange and sensing respiratory plant and more appropriate optimization algorithms.3) A complete model of the respiratory system that adequately predicts the response of obstructive and restrictive lung diseases. This model incorporates the simplification of a well-known, detailed and complete respiratory mechanical plant that is approximated quadratically for its computational integration in the model of the previous healthy subject. Mechanical parameters of three submodels for each disease are also proposed. 5) A computer simulator with a friendly and interactive user's interface, which includes the previous analyzed models and a mechanical ventilator model. This tool, which has already been tested for usability, has been successfully used in courses for physicians, researchers and students. With all these tools, it is expected to provide resources that assist physicians in the configuration of mechanical ventilators and understanding the interaction patient-ventilator.Las enfermedades respiratorias son una de las causas principales de muerte y enfermedad en Europa y el mundo. Una de las más importantes es la Enfermedad Pulmonar Obstructiva Crónica (EPOC) asociada principalmente a la bronquitis crónica y al enfisema pulmonar. Los pacientes con EPOC durante una Insuficiencia Respiratoria Aguda (IRA) requieren ventilación mecánica para asistir o sustituir su función pulmonar, donde la selección y configuración del modo ventilatorio constituye un paso esencial durante el tratamiento y la recuperación del paciente. La evolución del conocimiento fisiopatológico y de la tecnología ha generado una gran variedad de modos de ventilación diseñados para aumentar la ventilación alveolar, reducir el trabajo respiratorio, mejorar el acoplamiento entre la ventilación y la perfusión y optimar la oxigenación de la sangre arterial. Sin embargo, en la práctica clínica suelen ser desaprovechados muchos de los beneficios que estos ofrecen debido a: 1) la complejidad y diversidad de modos ventilatorios y marcas de ventiladores, y 2) la falta de herramientas que ayuden a la selección y configuración adecuada de estos en función de las características específicas de cada paciente. Se han estudiado diversos modelos del sistema respiratorio para reforzar el conocimiento sobre el mecanismo de control ventilatorio que dicho sistema adopta en condiciones normales y patológicas. Sin embargo, la unión entre el sistema de control respiratorio y los ventiladores mecánicos sigue siendo un campo de investigación abierto, dado que antes de configurar el ventilador resulta fundamental conocer y predecir apropiadamente su patrón respiratorio y los parámetros que lo afectan. El objetivo principal de esta tesis es el desarrollo y evaluación de nuevos simuladores computacionales que permitan predecir apropiadamente la respuesta dinámica respiratoria de sujetos sanos y enfermos respiratorios ante demandas ventilatorias y ventilación mecánica asistida. En esta tesis diversos modelos del sistema respiratorio son analizados. Modificaciones en su modelado, ajustes en sus parámetros y estudios comparativos fueron realizados con el fin de predecir adecuadamente la respuesta del sistema respiratorio en sujetos sanos y patológicos durante demandas ventilatorias incrementadas. Además, una herramienta computacional, basada en un modelo que integra las características más relevantes de los modelos analizados y de un ventilador mecánico, ha sido desarrollada para simular la interacción paciente-ventilador. Las principales contribuciones de la tesis son: 1) Una nueva estimación del trabajo mecánico respiratorio con una mayor interpretación fisiológica y cuya minimización permite predecir mejor la respuesta del sistema de control. 2) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta tanto en régimen transitorio como estacionario de un sujeto sano ante demandas ventilatorias incrementales. Dicho modelo utiliza una planta respiratoria de intercambio y sensado de gases mejorada y algoritmos de optimización más apropiados. 3) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta de enfermedades pulmonares obstructivas y restrictivas. Dicho modelo incorpora la simplificación de una planta mecánica respiratoria conocida, detallada y completa que se aproxima cuadráticamente para su integración computacional en el modelo del sujeto sano anterior. Parámetros mecánicos de tres submodelos para cada enfermedad son también propuestos 5) Un simulador computacional con una interfaz amigable e interactiva, que incluye el modelo anterior de un paciente y de un ventilador mecánico. Dicha herramienta a la que ya se le han hecho pruebas de usabilidad, ha sido utilizada con éxito en cursos para médicos, investigadores y estudiantes. (...

Modelado dinámico del sistema respiratorio ante incrementos de demanda ventilatoria, enfermedades pulmonares y ventilación mecánica asistida

Respiratory diseases remain one of the leading causes of death and illness in Europe and worldwide. One of the most important is Chronic Obstructive Pulmonary Disease (COPD) associated mainly with chronic bronchitis and pulmonary emphysema. Patients with COPD during acute respiratory failure (ARF) require mechanical ventilation to assist or replace their lung function, where the selection of ventilatory mode and its configuration is an essential step for patient's treatment and recovery.The development of pathophysiological knowledge and technology has generated a wide variety of ventilation modes designed to increase alveolar ventilation, reduce respiratory work, improve the coupling between ventilation and perfusion and optimize oxygenation of arterial blood. In clinical practice, however, many of the benefits they provide are often unused because of: 1) the complexity and diversity of ventilatory modalities and ventilator brands, and 2) the lack of tools to assist in the proper selection and configuration of the ventilatory modes according to the specific characteristics of each patient.Several models of the respiratory system have been studied to enhance knowledge about the mechanism of ventilatory control that the system adopts in normal and pathological conditions and to predict its cardiorespiratory response. However, the connection between the respiratory control system and mechanical ventilators remains an open research field, since it is essential to know and predict properly the respiratory pattern and the parameters that affect it before to set up the ventilator.The main objective of this doctoral thesis is the developed and evaluation of new computational simulators that allow predicting appropriately the respiratory dynamic response of healthy subjects and respiratory patients under ventilatory demands and assisted mechanical ventilation.In this thesis, different models of the respiratory system are analyzed. Modifications in their modeling, adjustments in their parameters and comparative studies were performed in order to properly predict the response of the respiratory system in healthy and pathological subjects during increased ventilatory demand. In addition, a computational and interactive tool, based on a model that integrates the most relevant characteristics of the analyzed models and a model of a mechanical ventilator, has been developed to simulate the interaction between a respiratory patient and a mechanical ventilator.The main contributions of the thesis are:1) A new estimate of respiratory mechanical work with a better physiological meaning and whose minimization allows better prediction of the system control response. 2) A complete respiratory system model that properly predicts both transient and stationary response of a healthy subject under incremental ventilatory demands. This model uses an improved gas exchange and sensing respiratory plant and more appropriate optimization algorithms.3) A complete model of the respiratory system that adequately predicts the response of obstructive and restrictive lung diseases. This model incorporates the simplification of a well-known, detailed and complete respiratory mechanical plant that is approximated quadratically for its computational integration in the model of the previous healthy subject. Mechanical parameters of three submodels for each disease are also proposed. 5) A computer simulator with a friendly and interactive user's interface, which includes the previous analyzed models and a mechanical ventilator model. This tool, which has already been tested for usability, has been successfully used in courses for physicians, researchers and students. With all these tools, it is expected to provide resources that assist physicians in the configuration of mechanical ventilators and understanding the interaction patient-ventilator.Las enfermedades respiratorias son una de las causas principales de muerte y enfermedad en Europa y el mundo. Una de las más importantes es la Enfermedad Pulmonar Obstructiva Crónica (EPOC) asociada principalmente a la bronquitis crónica y al enfisema pulmonar. Los pacientes con EPOC durante una Insuficiencia Respiratoria Aguda (IRA) requieren ventilación mecánica para asistir o sustituir su función pulmonar, donde la selección y configuración del modo ventilatorio constituye un paso esencial durante el tratamiento y la recuperación del paciente. La evolución del conocimiento fisiopatológico y de la tecnología ha generado una gran variedad de modos de ventilación diseñados para aumentar la ventilación alveolar, reducir el trabajo respiratorio, mejorar el acoplamiento entre la ventilación y la perfusión y optimar la oxigenación de la sangre arterial. Sin embargo, en la práctica clínica suelen ser desaprovechados muchos de los beneficios que estos ofrecen debido a: 1) la complejidad y diversidad de modos ventilatorios y marcas de ventiladores, y 2) la falta de herramientas que ayuden a la selección y configuración adecuada de estos en función de las características específicas de cada paciente. Se han estudiado diversos modelos del sistema respiratorio para reforzar el conocimiento sobre el mecanismo de control ventilatorio que dicho sistema adopta en condiciones normales y patológicas. Sin embargo, la unión entre el sistema de control respiratorio y los ventiladores mecánicos sigue siendo un campo de investigación abierto, dado que antes de configurar el ventilador resulta fundamental conocer y predecir apropiadamente su patrón respiratorio y los parámetros que lo afectan. El objetivo principal de esta tesis es el desarrollo y evaluación de nuevos simuladores computacionales que permitan predecir apropiadamente la respuesta dinámica respiratoria de sujetos sanos y enfermos respiratorios ante demandas ventilatorias y ventilación mecánica asistida. En esta tesis diversos modelos del sistema respiratorio son analizados. Modificaciones en su modelado, ajustes en sus parámetros y estudios comparativos fueron realizados con el fin de predecir adecuadamente la respuesta del sistema respiratorio en sujetos sanos y patológicos durante demandas ventilatorias incrementadas. Además, una herramienta computacional, basada en un modelo que integra las características más relevantes de los modelos analizados y de un ventilador mecánico, ha sido desarrollada para simular la interacción paciente-ventilador. Las principales contribuciones de la tesis son: 1) Una nueva estimación del trabajo mecánico respiratorio con una mayor interpretación fisiológica y cuya minimización permite predecir mejor la respuesta del sistema de control. 2) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta tanto en régimen transitorio como estacionario de un sujeto sano ante demandas ventilatorias incrementales. Dicho modelo utiliza una planta respiratoria de intercambio y sensado de gases mejorada y algoritmos de optimización más apropiados. 3) Un modelo completo del sistema respiratorio que predice adecuadamente la respuesta de enfermedades pulmonares obstructivas y restrictivas. Dicho modelo incorpora la simplificación de una planta mecánica respiratoria conocida, detallada y completa que se aproxima cuadráticamente para su integración computacional en el modelo del sujeto sano anterior. Parámetros mecánicos de tres submodelos para cada enfermedad son también propuestos 5) Un simulador computacional con una interfaz amigable e interactiva, que incluye el modelo anterior de un paciente y de un ventilador mecánico. Dicha herramienta a la que ya se le han hecho pruebas de usabilidad, ha sido utilizada con éxito en cursos para médicos, investigadores y estudiantes. (...

Comparison of computational cost and prediction error of cardiorespiratory models for exercise simulation

The modeling and simulation of the cardiorespiratory system has allowed a better understanding of the physiological system behavior to different stimuli and pathologies. Among its main applications stands out the computational tools for diagnosis and clinical treatment support, context in which the knowledge of the computational cost is fundamental for its implementation. The purpose of this work is to develop a comparative evaluation of computational cost of the cardiorespiratory models proposed by Cheng et al. and Albanese et al. under physical activity simulation. The evaluation consisted in the comparison of the computational cost and the prediction error of the physiological variables for each model. Variations in carbon dioxide production between 0.2 and 2.0 l/min were implemented, under the conditions and nominal parameters proposed for each model. The variables compared were mean arterial blood pressure, heart rate, frequency of breathing, tidal volume, arterial partial pressure of oxygen and arterial partial pressure of carbon dioxide. The results evidence that the model proposed by Cheng et al. is the most appropriate for the exercise simulation, due to both the best prediction of variables and the best relationship between complexity and simulation time required. © 2018 IEEE.Peer ReviewedPostprint (published version