Absolute electrical impedance tomography (aEIT) guided ventilation therapy in critical care patients: simulations and future trends

Thoracic electrical impedance tomography (EIT) is a noninvasive, radiation-free monitoring technique whose aim is to reconstruct a cross-sectional image of the internal spatial distribution of conductivity from electrical measurements made by injecting small alternating currents via an electrode array placed on the surface of the thorax. The purpose of this paper is to discuss the fundamentals of EIT and demonstrate the principles of mechanical ventilation, lung recruitment, and EIT imaging on a comprehensive physiological model, which combines a model of respiratory mechanics, a model of the human lung absolute resistivity as a function of air content, and a 2-D finite-element mesh of the thorax to simulate EIT image reconstruction during mechanical ventilation. The overall model gives a good understanding of respiratory physiology and EIT monitoring techniques in mechanically ventilated patients. The model proposed here was able to reproduce consistent images of ventilation distribution in simulated acutely injured and collapsed lung conditions. A new advisory system architecture integrating a previously developed data-driven physiological model for continuous and noninvasive predictions of blood gas parameters with the regional lung function data/information generated from absolute EIT (aEIT) is proposed for monitoring and ventilator therapy management of critical care patients

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

USSR Space Life Sciences Digest, volume 2, no. 3

Soviet scientists are making significant contributions to the field of space medicine and biology through their active manned space program, frequent biosatellites, and extensive ground-based research. An overview of the developments and direction of the USSR Space Life Sciences Program is provided

Prognosis of the state of health of a person under spaceflight conditions

Methods of predicting the state of health and human efficiency during space flight are discussed. Diversity of reactions to the same conditions, development of extrapolation methods of prediction, and isolation of informative physiological indexes are among the factors considered

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Vaccination is a suitable tool in the control of Aujeszky's disease outbreaks in pigs using a Population Dynamics P systems model

Aujeszky's disease is one of the main pig viral diseases and results in considerable economic losses in the pork production industry. The disease can be controlled using preventive measures such as improved stock management and vaccination throughout the pig-rearing period. We developed a stochastic model based on Population Dynamics P systems (PDP) models for a standard pig production system to differentiate between the effects of pig farm management regimes and vaccination strategies on the control of Aujeszky's disease under several different epidemiological scenarios. Our results suggest that after confirming the diagnosis, early vaccination of most of the population (>75%) is critical to decrease the spread of the virus and minimize its impact on pig productivity. The direct economic cost of an outbreak of Aujeszky's disease can be extremely high on a previously uninfected farm (from 352-792 Euros/sow/year) and highlights the positive benefits of investing in vaccination measures to control infections. We demonstrate the usefulness of computational models as tools in the evaluation of preventive medicine programs aimed at limiting the impact of disease on animal production.This work was partially supported by FEDER project COMRDI16-1-0035-03

Компромиссное разрешение конфликтных ситуаций в задачах оптимального управления при принятии решений в сложных ситуационных обстоятельствах

In present article it was proposed to apply mathematical model of the functional system of respiration for the simulation conflictcontrolled processes that appear during the self-organization of respiratory system under the conditions of complex situational stress in process of decisions’ making. The mathematical model of mass transfer and mass exchange of respiratory gases in human organism is represented as a system of ordinary differential equations, which in the dynamics of the respiratory cycle describe the changes in the stresses of oxygen and carbon dioxide at all stages of its path in human organism.Пропонується застосувати математичну модель функціональної системи дихання для імітації конфліктно-керованих процесів, які виникають при самоорганізації системи дихання в умовах складної ситуаційної напруги при прийнятті рішень. Математична модель масопереносу та масообміну респіраторних газів в організмі людини представлена системою звичайних диференційних рівнянь, які в динаміці дихального циклу описують зміну напружень кисню та вуглекислого газу на всіх етапах його шляху в організмі людини. Розв’язок цієї задачі з урахуванням як внутрішньо системних, так і між системних механізмів дозволяє прогнозувати оптимальні величини активних параметрів керування – вентиляції, об’ємних швидкостей системного та органних кровообігів.Предлагается применить математическую модель функциональной системы дыхания для имитации конфликтно-управляемых процессов, возникающих при самоорганизации системы дыхания в условиях сложного ситуационного напряжения при принятии решений. Математическая модель массопереноса и массообмена респираторных газов в организме человека представлена системой обыкновенных дифференциальных уравнений, которые в динамике дыхательного цикла описывают изменения напряжений кислорода и углекислого газа на всех этапах его пути в организме человека

Systems identification and application systems development for monitoring the physiological and health status of crewmen in space

The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 130, July 1974

This special bibliography lists 291 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1974