Biomedical Product and Materials Evaluation: Standards and Ethics provides a much-needed overview of the procedures, issues, standards and ethical issues in the early development of biomedical products. The book covers a range of key biomedical products, from 3D printed organs and blood derived products, to stem calls and decellularized tissue products. Each chapter reviews a single product type, associated materials, biomedical applications, proven development strategies, and potential challenges. The core focus of the book is on the standardization and ethical aspects of biomedical product development, with these elements addressed and discussed in chapters dedicated to product evaluation. This is a useful reference for academics, researchers and industry professionals in R&D groups with an interest in biomaterial research and production, as well as those working in the fields of biomedical engineering, biotechnology and toxicology.

Immunomodulatory Effects of Nanomaterials: Assessment and Analysis provides an overview of the modulatory impact of nanomaterials on the immune system, as well as evaluative and analytical methods for assessing effects. Sections cover a range of common nanomaterials for biomedical use and how different properties can elicit varied responses from the immune system. The immunomodulatory effects of these materials are then discussed, with coverage on adverse and/or toxic effects on the immune system, as well as desired modulatory effects to improve efficacy of applied therapeutics. Readers will also learn about the best evaluation methods for immunomodulatory effects of nanomaterials and associated risks. This book is a useful reference for academics and researchers with an interest in immunology, but it is also idea for those working in the fields of materials science, biomedical engineering, pharmaceutical science, immunology and toxicology.

Biomaterials for Angiogenesis and Vasculogenesis covers the application of materials designed to encourage new blood vessel formation. Angiogenesis and vasculogenesis play an important role in tissue engineering and regenerative medicine research by promoting vascular networks inside engineered tissues and thereby increasing tissue healing and regeneration. However, researchers are faced with the challenge of finding suitable materials for improving angiogenesis and vascular formation in assays. This book reviews a broad range of biomaterials for the promotion of blood vessel genesis, from polymers and bioactive glass, to nanomaterial scaffolds and 3D angiogenic constructs. In addition, the book covers a variety of applications for biomaterials in tissue repair and regeneration, including cardiovascular regeneration, liver tissue engineering and much more. It will serve as a detailed reference for researchers in academia and industry, working in the fields of biomedical science and engineering, materials science, regenerative medicine and translational medicine.

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence focuses on how the neurosciences can benefit from advances in AI, especially in areas such as medical image analysis for the improved diagnosis of Alzheimer's disease, early detection of acute neurologic events, prediction of stroke, medical image segmentation for quantitative evaluation of neuroanatomy and vasculature, diagnosis of Alzheimer's Disease, autism spectrum disorder, and other key neurological disorders. Chapters also focus on how AI can help in predicting stroke recovery, and the use of Machine Learning and AI in personalizing stroke rehabilitation therapy. Other sections delve into Epilepsy and the use of Machine Learning techniques to detect epileptogenic lesions on MRIs and how to understand neural networks.

Feedback Control for Personalized Medicine provides ideas on ongoing efforts and obstacles by members of the control engineering community in different biological and medical applications. In addition, the book presents key challenges, insights, tools and theoretical developments that arise from personalized medicine, along with medical concepts that are explained by engineers to help non-experts follow research topics. Several clinical trials have tried to find therapeutic approaches to achieve eradication or at least lifelong, therapy-free, host control of the infection. This has been performed integrating clinical observations, empirical knowledge and information from medical tests to treat patients. As this "trial and error" approach is becoming more challenging and unfeasible by the steep increase in the number of different pieces of information and the complexity of large datasets, a systematic and tractable approach that integrates a variety of biological and medical research data into mathematical models and computational algorithms is crucial to harness knowledge and to develop new therapies towards personalized medicine.

Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development focuses on recent advances and benefits of wearable telemedicine techniques for remote health monitoring and prevention of chronic conditions, providing real time feedback and help with rehabilitation and biomedical applications. Readers will learn about various techniques used by software engineers, computer scientists and biomedical engineers to apply intelligent systems, artificial intelligence, machine learning, virtual reality and augmented reality to gather, transmit, analyze and deliver real-time clinical and biological data to clinicians, patients and researchers. Wearable telemedicine technology is currently establishing its place with large-scale impact in many healthcare sectors because information about patient health conditions can be gathered anytime and anywhere outside of traditional clinical settings, hence saving time, money and even lives.

3D Bioprinting and Nanotechnology in Tissue Engineering and Regenerative Medicine, Second Edition provides an in-depth introduction to bioprinting and nanotechnology and their industrial applications. Sections cover 4D Printing Smart Multi-responsive Structure, Cells for Bioprinting, 4D Printing Biomaterials, 3D/4D printing functional biomedical devices, 3D Printing for Cardiac and Heart Regeneration, Integrating 3D printing with Ultrasound for Musculoskeletal Regeneration, 3D Printing for Liver Regeneration, 3D Printing for Cancer Studies, 4D Printing Soft Bio-robots, Clinical Translation and Future Directions. The book's team of expert contributors have pooled their expertise in order to provide a summary of the suitability, sustainability and limitations of each technique for each specific application. The increasing availability and decreasing costs of nanotechnologies and 3D printing technologies are driving their use to meet medical needs. This book provides an overview of these technologies and their integration.

Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice.

Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in wearable sensors and PPG for cardiovascular assessment.

Emerging Nanomedicines for Diabetes Mellitus Theranostics provides readers with information on the development of efficacious nanomedicines as potential theranostic agents for diabetes. The book discusses the application of various novel nanomaterials and nanocomposites for targeted delivery of insulin, glucose sensing, including nano-tattoos as glucose monitors, biosynthesized nanoparticles for diabetes treatment, and pre-clinical and clinical assays to evaluate the efficacy of nanomedicines for diabetes treatment. This is an important references source for materials scientists, pharmaceutical scientists and biomedical engineers who want to increase their understanding of how nanotechnology is being used to improve diabetes treatment. Diabetes has emerged as one of the most common diseases associated with lifestyle choices in the modern world, with significant mortality rates. Conventional treatment methods mainly involve insulin-based therapies. However, insulin therapy possesses several limitations such as weight gain and hypoglycemia. Thus, advanced research in nanomedicine is targeting the development of new and improved diagnostics and treatment methods for diabetes.

As technology continues to develop, the healthcare industry must adapt and implement new technologies and services. Recent advancements, opportunities, and challenges for bio-medical image processing and authentication in telemedicine must be considered to ensure patients receive the best possible care. Advancements in Bio-Medical Image Processing and Authentication in Telemedicine introduces recent advancements, opportunities, and challenges for bio-medical image processing and authentication in telemedicine and discusses the design of high-accuracy decision support systems. Covering key topics such as artificial intelligence, medical imaging, telemedicine, and technology, this premier reference source is ideal for medical professionals, nurses, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Musculoskeletal Tissue Engineering introduces the fundamental concepts and translational applications of musculoskeletal tissue engineering, in combination with emerging technologies and materials. Sections discuss Tissues and Technologies, covering a range of musculoskeletal tissues, including bone, cartilage, ligament and more. Each chapter in this section details core tissue engineering principles specific to each tissue type. Next, a Technologies section looks at the range of biomaterials used in musculoskeletal tissue engineering, focusing on biocompatibility of materials and interactions at the material-tissue interface. Other chapters cover nanotechnology, 3D printing, gene therapy, tissue chips, and more. This book offers an advanced reference text for researchers in biomedical engineering, materials science and regenerative medicine.

Cardiovascular and Respiratory Bioengineering focuses on computational tools and modeling techniques in cardiovascular and respiratory systems that help develop bioengineered solutions. The book demonstrates how these technologies can be utilized in order to tackle diseases and medical issues. It provides practical guidance on how a bioengineering or medical problem can be modeled, along with which computational models can be used. Topics include computer modeling of Purkinje fibers with different electrical potential applied, modeling of cardiomyopathies caused by sarcomeric gene mutations, altered sarcomere function, perturbations in intracellular ion homeostasis, impaired myocardial energetics at reduced costs, and more. The book also discusses blood flow through deformable blood vessels in human aorta, abdominal aortic aneurysm, carotid artery, coronary artery and plaque formation, along with content on stent deployment modeling and stent design and optimization techniques.

Hybrid Nanomaterials for Drug Delivery covers a broad range of hybrid nanomaterials and nanocomposites used in drug delivery systems. The book reviews a variety of hybrid nanomaterials and structures, including polymer-lipid, chitosan-based, protein-inorganic, quantum dot hybrids, and more. The strengths, limitations and regulatory aspects of hybrid drug delivery systems are also discussed, allowing readers to make informed decisions when choosing to utilize hybrid nanomaterials. Users will find this to be an exciting and comprehensive look into this emerging area. It will be of particular interest to academics and researchers working in materials science, engineering, biomedical engineering, nanotechnology and pharmaceutical science. Multi nanocarrier-based hybrid systems are an emerging concept in the field of drug delivery that allow researchers to avoid some of the challenges faced when administering drugs, such as low bioavailability, development of drug resistance, toxicities, premature drug release, and therapeutic efficacy.

Tissue Engineering Using Ceramics and Polymers, Third Edition is a valuable reference tool for both academic researchers and scientists involved in biomaterials or tissue engineering, including the areas of bone and soft-tissue reconstruction, repair and organ regeneration. With its distinguished editors and international team of contributors, this book reviews the latest research and advances in this thriving area and how they can be used to develop treatments for disease states. New sections cover nanobiomaterials, drug delivery, advanced imaging and MRI for tissue engineering, and characterization of vascularized scaffolds. Technology and research in the field of tissue engineering has drastically increased within the last few years to the extent that almost every tissue and organ of the human body could potentially be regenerated with the aid of biomaterials.

Porous Silicon for Biomedical Applications, Second Edition, provides an updated guide to the diverse range of biomedical applications of porous silicon, from biosensing and imaging to tissue engineering and cancer therapy. Across biomedical disciplines, there is an ongoing search for biomaterials that are biocompatible, modifiable, structurally sound, and versatile. Porous silicon possesses a range of properties that make it ideal for a variety of biomedical applications, such as controllable geometry, tunable nanoporous structure, large pore volume/high specific surface area, and versatile surface chemistry. This book provides a fully updated and detailed overview of the range of biomedical applications for porous silicon. Part One offers the reader a helpful insight into the fundamentals and beneficial properties of porous silicon, including thermal properties and stabilization, photochemical and nonthermal chemical modification, protein modification, and biocompatibility. The book then builds on the systematic detailing of each biomedical application using porous silicon, from bioimaging and sensing to drug delivery and tissue engineering. This new edition also includes new chapters on in-vivo assessment of porous silicon, photodynamic and photothermal therapy, micro- and nanoneedles, Raman imaging, cancer immunotherapy, and more. With its acclaimed editor and international team of expert contributors, Porous Silicon for Biomedical Applications, Second Edition, is a technical resource and indispensable guide for all those involved in the research, development, and application of porous silicon and other biomaterials, while providing a comprehensive introduction for students and academics interested in this field.

Biomaterials in Endodontics offers an up-to-date overview of endodontic biomaterials and their applications in regenerative medicine and tissue engineering. This book details the key biomaterials used in clinical endodontics and the benefits and challenges of using these materials, from root canal obturation materials to alloys for endodontic files and hand instruments. Chapters also offer a unique insight into the regenerative applications of endodontic biomaterials, such as the use of stem cells and growth factors for bone regeneration. Biomaterials in Endodontics is a useful resource for researchers working in biomedical engineering, regenerative medicine, and materials science with an interest in dentistry and bone regeneration. This book is also a helpful guide for endodontists, dentists, dental scientists, and clinicians with an interest in biomaterials for endodontics.

Mechanical Design of Piezoelectric Energy Harvesters: Generating Electricity from Human Walking provides the state-of-the-art, recent mechanical designs of piezoelectric energy harvesters based on piezoelectric stacks. The book discusses innovative mechanism designs for energy harvesting from multidimensional force excitation, such as human walking, which offers higher energy density. Coverage includes analytical modeling, optimal design, simulation study, prototype fabrication, and experimental investigation. Detailed examples of their analyses and implementations are provided. The book's authors provide a unique perspective on this field, primarily focusing on novel designs for PZT Energy harvesting in biomedical engineering as well as in integrated multi-stage force amplification frame. This book presents force-amplification compliant mechanism design and force direction-transmission mechanism design. It explores new mechanism design approaches using piezoelectric materials and permanent magnets. Readers can expect to learn how to design new mechanisms to realize multidimensional energy harvesting systems.

Biosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an approach for biosignal processing and classification using computational learning and intelligence, highlighting that the term biosignal refers to all kinds of signals that can be continuously measured and monitored in living beings. The book is composed of five relevant parts. Part One is an introduction to biosignals and Part Two describes the relevant techniques for biosignal processing, feature extraction and feature selection/dimensionality reduction. Part Three presents the fundamentals of computational learning (machine learning). Then, the main techniques of computational intelligence are described in Part Four. The authors focus primarily on the explanation of the most used methods in the last part of this book, which is the most extensive portion of the book. This part consists of a recapitulation of the newest applications and reviews in which these techniques have been successfully applied to the biosignals' domain, including EEG-based Brain-Computer Interfaces (BCI) focused on P300 and Imagined Speech, emotion recognition from voice and video, leukemia recognition, infant cry recognition, EEGbased ADHD identification among others.

Applications of Computational Intelligence in Multi-Disciplinary Research provides the readers with a comprehensive handbook for applying the powerful principles, concepts, and algorithms of computational intelligence to a wide spectrum of research cases. The book covers the main approaches used in computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods, all of which can be collectively viewed as soft computing. Other key approaches included are swarm intelligence and artificial immune systems. These approaches provide researchers with powerful tools for analysis and problem-solving when data is incomplete and when the problem under consideration is too complex for standard mathematics and the crisp logic approach of Boolean computing.

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation.

Early diagnosis of cancer and other non-oncological disorders gives a significant advantage for curing the disease and improving patient's life expectancy. Recent advances in biosensor-based techniques which are designed for specific biomarkers can be exploited for early diagnosis of diseases. Biosensor Based Advanced Cancer Diagnostics covers all available biosensor-based approaches and comprehensive technologies; along with their application in diagnosis, prognosis and therapeutic management of various oncological disorders. Besides this, current challenges and future aspects of these diagnostic approaches have also been discussed. This book offers a view of recent advances and is also helpful for designing new biosensor-based technologies in the field of medical science, engineering and biomedical technology. Biosensor Based Advanced Cancer Diagnostics helps biomedical engineers, researchers, molecular biologists, oncologists and clinicians with the development of point of care devices for disease diagnostics and prognostics. It also provides information on developing user friendly, sensitive, stable, accurate, low cost and minimally invasive modalities which can be adopted from lab to clinics. This book covers in-depth knowledge of disease biomarkers that can be exploited for designing and development of a range of biosensors. The editors have summarized the potential cancer biomarkers and methodology for their detection, plus transferring the developed system to clinical application by miniaturization and required integration with microfluidic systems.

Nanotechnology in Medicine and Biology brings together a multidisciplinary team of experts from the fields of materials science, nanotechnology, medicine and biomedical engineering to introduce new nanoscale biomaterials and their applications, diagnosis and treatment of disorders of the human body. The book presents the fundamentals for understanding the design, properties and selection of nanobiomaterials as well as their real-world applications in medicine. Each chapter addresses current regulations, manufacturing processes, and translation issues of nanobiomaterials for key applications. A discussion of current protocols and their benefits and disadvantages is also included. This book provides comprehensive background and knowledge in the field of nanobiomaterials that is suitable for academics, scientists and clinicians.

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems.

Big Data permeates all aspects of modern life, and while there is no shortage of potential benefits resulting from this, author Henrik Skaug Saetra argues that we must also understand the threats Big Data poses to liberty. The issues discussed in Big Data's Threat to Liberty: Surveillance, Nudging, and the Curation of Information are related to how we are constantly under surveillance. Data is gathered from our homes, our cars, our smartphones, various devices around the house, and public sources such as facial recognition enabled camera surveillance and various websites and social networks. Furthermore, the information gathered is used to influence our actions. Detailed personality profiles are utilized in order to make us purchase products and services, or pay our taxes, through tailor-made nudges aimed at irrational and subconscious mechanisms, and delivered with a level of precision only possible with Big Data-driven algorithmic curation of data. Finally, the information we receive through various media is curated by algorithms, and even people are curated in order to satisfy our desires. By providing us with what the algorithm believes we want, we are spared from the exposure of unpleasant information, and even unpleasant people. The ideological landscapes we traverse are thus characterized by conformity, and a concomitant tyranny of popular opinion becomes ever more coercive as this occurs. The question is: How does being constantly watched, manipulated, and having our world-views shaped as just described affect our freedom? In this book it is argued that Big Data's threat to individual liberty is routinely misunderstood and underappreciated due to (a) vagueness resulting from the concept of liberty being used without it being defined, or (b) the use of definitions based on flawed understandings of what liberty is. In this new and unique contribution to the ethics of Big Data and artificial intelligence, both these challenges are thoroughly addressed.