Academia.edu no longer supports Internet Explorer.
To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser.
2019, Signals and Systems in Biomedical Engineering: Physiological Systems Modeling and Signal Processing
That virtual reality is possible is an important fact about the fabric of reality. It is the basis not only of computation, but of human imagination and external experience, science and mathematics, art and fiction.-David Deutsch The availability of cheap computing power makes computational models available easily to physiologists. Modern computers have not only good computational capabilities but also very good graphical displays, thereby making the output of models convenient for non-mathematical users. Graphical presentation itself uses visual analogy for physical behavior. Since modern computers are all discrete numerical machines, while physiological systems are fundamentally continuous, some approximations are required in order to use discrete modeling for continuoustime systems. The issue of discretization has been dealt with in some detail in Chap. 4, and a number of digital techniques for the analysis of signals and systems have been discussed in Chap. 5. In this chapter, we look at some geometric and animation techniques for representing physiological models. We also introduce haptics which can impart a tactile component to the models. These computational models with graphical display, audio, and haptics make possible virtual experiments for physiological exploration. 6.1 Numerical Methods for Solving Equations In the early days of computational models, differential equations were solved using analog computers. The analog computers were electronic circuits whose behavior mimicked that of the system being modeled. Modern computer models use digital computers to solve the system equations. Contemporary digital computers are
Computer Methods and …, 2010
The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original document and are linked to publications on ResearchGate, letting you access and read them immediately. c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e 1 0 2 ( 2 0 1 1 ) 295-304 Physiology Mathematical model Computer model Simulation a b s t r a c t Guyton's original integrative physiology model was a milestone in integrative physiology, combining significant physiological knowledge with an engineering perspective to develop a computational diagrammatic model. It is still used in research and teaching, with a small number of variants on the model also in circulation. However, though new research has added significantly to the knowledge represented by Guyton's model, and significant advances have been made in computing and simulation software, an accepted common platform to integrate this new knowledge has not emerged. This paper discusses the issues in the selection of a suitable platform, together with a number of current possibilities, and suggests a graphical computing environment for modelling and simulation. By way of example, a validated version of Guyton's 1992 model, implemented in the ubiquitous Simulink environment, is presented which provides a hierarchical representation amenable to extension and suitable for teaching and research uses. It is designed to appeal to the biomedical engineer and physiologist alike. .ie (V. Mangourova).
Signals and Systems in Biomedical Engineering: Physiological Systems Modeling and Signal Processing, 2019
Model-Based Analysis of Physiological Systems Sometimes a computing machine does do something rather weird that we hadn't expected. In principle one could have predicted it, but in practice it's usually too much trouble.-Alan Turing Physiological modeling involves the development of mathematical, electrical, chemical, or other analogs whose behavior closely approximates the behavior of a particular physiological system. Such models allow us to extend intuitive knowledge gained in one area to another less familiar area. The earliest models of physiological system were physical analogies. Even now many students in high school are introduced to the ideas of respiration and blood flow using physical models involving air flow and water in tubes, respectively. Mathematical descriptions of physiological systems use differential equations and the analysis of these systems requires solving differential equations. Such solutions of differential equations can in principle be done analytically (i.e., on paper), physically (i.e., by building a physical analog), or numerically (i.e., on a digital computer). With modern personal computers, the last of these options is very attractive. Since models rely on experimental data to provide the basic relationship between parameters, the accuracy of the model rests on the accuracy of the experimental measurement. The majority of contemporary models are computer based, using computational solutions of equations and graphical presentations to analyze and simulate the system under study. 7.1 Biophysical and Black Box Models There are two main approaches to modeling physiological systems and the choice of either approach depends on the end purpose and the ease of implementation. The first approach is to obtain a set of mathematical equations that will mimic
2005
The authors' methodology of creating e-learning content for the students of physiology, pathophysiology and biomedicine at the Faculty of Medicine is presented here. The design process from a formalized description of physiological reality to interactive educational software is described. Various tools are used during the design-starting with the numerical simulation software Matlab/Simulink, through Macromedia Flash for interactive animations, Control Web or MS Visual Studio for user interface design to web publishing tools including the Macromedia Breeze learning management system. Also, various professions are involved-teachers, physicians, simulation/modeling experts, graphic designers and programmers. The aim is to provide students with software that helps them understand the complex dynamics of physiological systems.
2004
Here, we will start with the discussion about the application of the mechanics to the living systems or materials. Such an approach to mechanical analysis of living systems is different to that one used in engineering because of its functional complexity of the living systems. Living systems are the constructin of many organic systems, that we should study them and also their interactions. Partially is important interaction of the human with its environment. The ralationship between man and environment has ever been a subject of investigation. Scientifitic studies on five senses have been carried out since the time of Aristotle. Man communicates in two different ways. One is effected in contact with the outside world and another with its own body. The first way of communication is through five sences known as hearing, sight, smell, tase and touch; the second way through the proprioceptive system. Fischer and Braun (1889). They involved an approximative method which is known as "...
2015
ABSTRACT: Creation of modern educational software represents a challenging and complicated project, requiring team cooperation of various professionals. To keep the whole interdisciplinary design cycle fast and efficient, it is necessary to use specialized development tools with sufficient technical support at every stage of the design. The authors present their way of designing multimedia biomedical educational software with simulation games. Simulation models, created using simulation development tools- Matlab/Simulink from MathWorks, are decomposed to interconnected simulation chips suitable for interdisciplinary cooperation between physiologists and programmers during design-time. Interactive graphical components utilize animation software tools- Flash and Director from Macromedia. The user interfaces of the simulators are implemented in Control Web from Moravian Instruments (the Control Web environment was primarily intended to develop industrial control and visualization appli...
In this study, a mathematical model is developed based on algebraic equations which is capable of generating artificially normal events of electrocardiogram (ECG) signals such as P-wave, QRS complex, and T-wave. This model can also be implemented for the simulation of abnormal phenomena of electrocardiographic signals such as STsegment episodes (i.e. depression, elevation, and sloped ascending or descending) and repolarization abnormalities such as T-Wave Alternans (TWA). Event parameters such as amplitude, duration, and incidence time in the conventional ECG leads can be a good reflective of heart electrical activity in specific directions. The presented model can also be used for the simulation of ECG signals on torso plane or limb leads. To meet this end, the amplitude of events in each of the 15-lead ECG waveforms of 80 normal subjects at MIT-BIH Database (www.physionet.org) are derived and recorded. Various statistical analyses such as amplitude mean value, variance and confidence intervals calculations, Anderson-Darling normality test, and Bayesian estimation of events amplitude are then conducted. Heart Rate Variability (HRV) model has also been incorporated to this model with HF/LF and VLF/LF waves power ratios. Eventually, in order to demonstrate the suitable flexibility of the presented model in simulation of ECG signals, fascicular ventricular tachycardia (left septal ventricular tachycardia), rate dependent conduction block (Aberration), and acute Qwave infarctions of inferior and anterior-lateral walls are finally simulated. The opensource simulation code of above abnormalities will be freely available.
Journal of healthcare engineering, 2018
The modelling of virtual environments and scenarios is an important area of research for the development of new computer-assisted systems in the areas of engineering and medicine, particularly in the area of biomechanics and biomedical engineering. One of the main issues while designing a virtual environment is the level of realism, which depends on the computing capacity and the level of accuracy and usefulness of the generated data. Thus, the dilemma is between the aesthetic realism and the information utility. This paper proposes a methodology to develop low-cost and high-quality virtual environments and scenarios for computer-aided biomedical applications. The proposed methodology is based on the open-source software Blender and the Visualization Toolkit libraries (VTK). In order to demonstrate the usability of the proposed methodology, the design and development of a computer-assisted biomedical application is presented and analysed.
2008 Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2008
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010
The modeling of the electrical activity of the heart is of great medical and scientific interest, because it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. The cardiac electrophysiology may be simulated by solving a partial differential equation (PDE) coupled to a system of ordinary differential equations (ODEs) describing the electrical behavior of the cell membrane. The numerical solution is, however, computationally demanding because of the fine temporal and spatial sampling required. The demand for real time high definition 3D graphics made the new graphic processing units (GPUs) a highly parallel, multithreaded, many-core processor with tremendous computational horsepower. It makes the use of GPUs a promising alternative to simulate the electrical activity in the heart. The aim of this work is to study the performance of the use of GPUs to solve the equations underlying the electrical activity in a simple cardiac tissue.
2013
In teaching medical decision-making, comprehensive training simulators are of great importance. These must include models of various physiological subsystems, and also integrate them into a comprehensive whole. Medical simulators have recently become a highly sought-after commercial commodity. Like an airline pilot simulator, a medical simulator is controlled by a remote operator, who manipulates the simulated patient and chooses between various scenarios to simulate different maladies. The core of a medical training simulator is a complex model of the human body‘s internal physiological regulators, connected with a hardware simulator. Its detailed structure (the system of equations and the parameter values that feed into them) is usually not published, becoming a carefully-protected piece of trade secrets There are also open source models of integrated physiological systems. One is a large model by Coleman et al. called HumMod (http://hummod.org) implemented by thousands of XML fil...
2006
♯ MOX–Modellistica e Calcolo Scientifico Dipartimento di Matematica “F. Brioschi” Politecnico di Milano via Bonardi 9, 20133 Milano, Italy. alfio. quarteroni@ mate. polimi. it Modelling and Scientific Computing (CMCS), Institute of Analysis and Scientific Computing (IACS), EPFL, École Polytechnique Fédérale de Lausanne, CH-1015, Lausanne, Switzerland. alfio. quarteroni@ epfl.
Case Studies and Applications
In the following chapter, the authors will discuss the development of medical imaging and, through specific case studies, its application in elucidating the role of fluid mechanical forces in cardiovascular disease development and therapy (namely the connection between flow patterns and circulatory system disease - atherosclerosis and aneurysms) by means of computational fluid dynamics (CFD). The research carried in the Biomedical Simulation Laboratory can be described as a multi-step process through which, from the reality of the human body through the generation of a mathematical model that is then translated into a visual representation, a refined visual representation easily understandable and used in the clinic is generated. Thus, the authors’ daily research generates virtual representations of blood flow that can serve two purposes: a) that of a model for a phenomenon or disease or b) that of a model for an experiment (non-invasive way of determining the best treatment option).
Rossiĭskii fiziologicheskiĭ zhurnal imeni I.M. Sechenova / Rossiĭskaia akademiia nauk
The article illustrates the method of mathematical modelling in physiology as a unique tool to study physiological processes. A number of demonstrated examples appear as a result of long-term experience in mathematical modelling of electrical and mechanical phenomena in the heart muscle. These examples are presented here to show that the modelling provides insight into mechanisms underlying these phenomena and is capable to predict new ones that were previously unknown. While potentialities of the mathematical modelling are analyzed with regard to the myocardium, they are quite universal to deal with any physiological processes.
Texts in Applied Mathematics, 2002
2011
The KTH School of Computer Science and Communication (CSC) established a strategic platform in Simulation-Visualization-Interaction (SimVisInt) in 2009, focused on the high potential in bringing together CSC core competences in simulation technology, visualization and interaction. The main part of the platform takes the form a set of new trans-disciplinary projects across established CSC research groups, within the theme of Computational Human Modeling and Visualization: (i) interactive virtual biomedicine (HEART), (ii) simulation of human motion (MOTION), and (iii) virtual prototyping of human hand prostheses (HAND). In this paper, we present recent results from the HEART project that focused on gestural and haptic interaction with a heart simulation.
2004
The purpose of this book is to study mathematical models of human physiology. The book is a result of work by Math-Tech (in Copenhagen, Denmark) and the BioMath group at the Department of Mathematics and Physics at Roskilde University (in Roskilde, Denmark) on mathematical models related to anesthesia simulation. The work presented in this book has been carried out as part of a larger project SIMA (SIMulation in Anesthesia) 1 , which has resulted in the production of a commercially available anesthesia simulator and several scientific research publications contributing to the understanding of human physiology. This book contains the scientific contributions and does not discuss the details of the models implemented in the SIMA project.
Models for Physiological Systems 2 J. M. Lemos-INESC-ID/IST T. Mendonça-FC UP Summary ! A basic principle for writing state equations: The law of mass action. ! HIV 1 infection: State space, equilibrium points and linearised dynamics. ! Modelling anaesthesia: Compartmental models and Wiener models. ! Models at a glance. Models for Physiological Systems 3 J. M. Lemos-INESC-ID/IST T. Mendonça-FC UP Can we build mathematical models for physiological systems? Physiological systems are very complex. They are made of cells and tissues that interact in complex ways to perform the functions required by living beings. Yet, the basic mechanisms are relatively simple, relying in many cases in basic principles from Chemistry and Physics (e. g. Electricity). Thus, it is possible to build tractable mathematical models in the form of differential or difference equations. A key issue is variability: The parameters entering the mathematical model vary from individual to individual and, very often, in the same individual as time passes. Models for Physiological Systems 4 J. M. Lemos-INESC-ID/IST T. Mendonça-FC UP Objective The objective of this lecture is to illustrate how the use basic principles may be used in a few examples to yield models of physiological systems (sometimes called mechanistic models) that are useful for modelling or control design. The treatment of the subject is by no means exhaustive. People interested are invited to pursue the subjects of their interest in the literature, e. g. the references quoted in the end of this lecture.
Cardiovascular Disease (CVD) is considered to be the common cause of death in several counties while the necessity of experienced cardiologists is at its peak. The fate of the patients depends sorely on how well-equipped the personnel and the hospitals are to overcome the clinical issues. Still, it can take a substantial amount of time for the practitioners to perfect their skills, even more so for rookies who just entered this daunting field. Hence, an educational oriented tool will undoubtedly assist the newcomers in this critical profession. This paper aims to utilize a recent simulation technology namely “Position Based Dynamic” or PBD method to visualize the mechanism and phenomenon of the muscle and blood inside the human heart, including the heart muscle movement, the blood current and the interaction between them. Then an evaluation interview was conducted with a medical professor to review the simulated animation. As a result, the system had proven the concept of using PBD ...
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.