Combining topics from numerous applications in biomechanics, Applied Biomedical Engineering Mechanics demonstrates how to analyze physiological processes from an engineering perspective and apply the results to tertiary medical care. The book extends its discussion to the investigation of diagnostic and surgical procedures. It also presents guideli
Improve Your Grasp of Fluid Mechanics in the Human Circulatory System_and Develop Better Medical Devices Applied Biofluid Mechanics features a solid grasp of the role of fluid mechanics in the human circulatory system that will help in the research and design of new medical instruments, equipment, and procedures. Filled with 100 detailed illustrations, the book examines cardiovascular anatomy and physiology, pulmonary anatomy and physiology, hematology, histology and function of blood vessels, heart valve mechanics and prosthetic heart valves, stents, pulsatile flow in large arteries, flow and pressure measurement, modeling, and dimensional analysis.
Both broad and deep in coverage, Rubenstein shows that fluid mechanics principles can be applied not only to blood circulation, but also to air flow through the lungs, joint lubrication, intraocular fluid movement and renal transport. Each section initiates discussion with governing equations, derives the state equations and then shows examples of their usage. Clinical applications, extensive worked examples, and numerous end of chapter problems clearly show the applications of fluid mechanics to biomedical engineering situations. A section on experimental techniques provides a springboard for future research efforts in the subject area. - Uses language and math that is appropriate and conducive for undergraduate learning, containing many worked examples and end of chapter problems - All engineering concepts and equations are developed within a biological context - Covers topics in the traditional biofluids curriculum, as well as addressing other systems in the body that can be described by biofluid mechanics principles, such as air flow through the lungs, joint lubrication, intraocular fluid movement, and renal transport - Clinical applications are discussed throughout the book, providing practical applications for the concepts discussed.
This book presents a collection of recent and extended academic works in selected topics of biomedical technology, biomedical instrumentations, biomedical signal processing and bio-imaging. This wide range of topics provide a valuable update to researchers in the multidisciplinary area of biomedical engineering and an interesting introduction for engineers new to the area. The techniques covered include modelling, experimentation and discussion with the application areas ranging from bio-sensors development to neurophysiology, telemedicine and biomedical signal classification.
This unique resource offers over two hundred well-tested bioengineering problems for teaching and examinations. Solutions are available to instructors online.
This book provides an introduction to qualitative and quantitative aspects of human physiology. It looks at biological and physiological processes and phenomena, including a selection of mathematical models, showing how physiological problems can be mathematically formulated and studied. It also illustrates how a wide range of engineering and physics topics, including electronics, fluid dynamics, solid mechanics and control theory can be used to describe and understand physiological processes and systems. Throughout the text there are introductions to measuring and quantifying physiological processes using both signal and imaging technologies. Physiology for Engineers describes the basic structure and models of cellular systems, the structure and function of the cardiovascular system, the electrical and mechanical activity of the heart and provides an overview of the structure and function of the respiratory and nervous systems. It also includes an introduction to the basic concepts and applications of reaction kinetics, pharmacokinetic modelling and tracer kinetics. It is of interest to final year biomedical engineering undergraduates and graduate students alike, as well as to practising engineers new to the fields of bioengineering or medical physics.
Designed to meet the needs of undergraduate students, "Introduction to Biomechanics" takes the fresh approach of combining the viewpoints of both a well-respected teacher and a successful student. With an eye toward practicality without loss of depth of instruction, this book seeks to explain the fundamental concepts of biomechanics. With the accompanying web site providing models, sample problems, review questions and more, Introduction to Biomechanics provides students with the full range of instructional material for this complex and dynamic field.
Biomedical Engineering Modeling of Pancreatic, Respiratory, and Renal Regulatory Systems, and their Medical Assessments addresses the need for biomedical engineering to provide physiological analysis of organ systems and their medical applications to help enable quantitative formulation of physiological systems and defining their functions and dysfunctions, leading to precision diagnostics of diabetes, lung diseases, and kidney failure, often in the form of non-dimensional indices. The book chapters also deal with treatment systems, namely automated insulin infusion systems, hemodialysis, and peritoneal dialysis. The book is formulated to solve many physiological, bioengineering, and medical problems. - Covers foundational concepts of the emerging fields of quantitative physiology and computational medicine, developing the biomedical engineering modeling of three important organ systems: pancreas, lungs, and kidneys - Provides readers with detailed understanding of novel biomedical engineering strategies in key areas, such as pancreatic system engineering, glucose-insulin regulatory system engineering, pulmonary system engineering, and renal system engineering - Provides in-depth technical coverage of computational modeling techniques and applied mathematics for these important physiological systems, including differential equations and the associated MATLAB datasets for all applied diagnostic and treatment examples
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. - Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems - Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems - Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others - Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients
