Applied Biomechatronics Using Mathematical Models provides an appropriate methodology to detect and measure diseases and injuries relating to human kinematics and kinetics. It features mathematical models that, when applied to engineering principles and techniques in the medical field, can be used in assistive devices that work with bodily signals. The use of data in the kinematics and kinetics analysis of the human body, including musculoskeletal kinetics and joints and their relationship to the central nervous system (CNS) is covered, helping users understand how the complex network of symbiotic systems in the skeletal and muscular system work together to allow movement controlled by the CNS. With the use of appropriate electronic sensors at specific areas connected to bio-instruments, we can obtain enough information to create a mathematical model for assistive devices by analyzing the kinematics and kinetics of the human body. The mathematical models developed in this book can provide more effective devices for use in aiding and improving the function of the body in relation to a variety of injuries and diseases. - Focuses on the mathematical modeling of human kinematics and kinetics - Teaches users how to obtain faster results with these mathematical models - Includes a companion website with additional content that presents MATLAB 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

Cognitive Informatics, Computer Modelling, and Cognitive Science: Volume Two, Application to Neural Engineering, Robotics, and STEM presents the practical, real-world applications of Cognitive Science to help readers understand how it can help them in their research, engineering and academic pursuits. The book is presented in two volumes, covering Introduction and Theoretical Background, Philosophical and Psychological Theory, and Cognitive Informatics and Computing. Volume Two includes Statistics for Cognitive Science, Cognitive Applications and STEM Case Studies. Other sections cover Cognitive Informatics, Computer Modeling and Cognitive Science: Application to Neural Engineering, Robotics, and STEM. The book's authors discuss the current status of research in the field of Cognitive Science, including cognitive language processing that paves the ways for developing numerous tools for helping physically challenged persons, and more. - Identifies how foundational theories and concepts in cognitive science are applicable in other fields - Includes a comprehensive review of cognitive science applications in multiple domains, applying it to neural engineering, robotics, computer science and STEM - Presents basic statistics and cognitive maps, testing strategies of hypothesis, maximum likelihood estimator, Bayesian statistics, and discrete probability models of neural computation - Contains in-depth technical coverage of cognitive applications and case studies, including neuro-computing, brain modeling, cognitive ability and cognitive robots

This two-volume set LNCS 12645-12646 constitutes the refereed proceedings of the 16th International Conference on Diversity, Divergence, Dialogue, iConference 2021, held in Beijing, China, in March 2021. The 32 full papers and the 59 short papers presented in this volume were carefully reviewed and selected from 225 submissions. They cover topics such as: AI and machine learning; data science; human-computer interaction; social media; digital humanities; education and information literacy; information behavior; information governance and ethics; archives and records; research methods; and institutional management.

This book gathers the latest advances, innovations, and applications in the field of multibody and mechatronic systems. Topics addressed include the analysis and synthesis of mechanisms; dynamics of multibody systems; design algorithms for mechatronic systems; robots and micromachines; experimental validations; theory of mechatronic simulation; mechatronic systems for rehabilitation and assistive technologies; mechatronic systems for energy harvesting; virtual reality integration in multibody and mechatronic systems; multibody design in robotic systems; and control of mechatronic systems. The contents reflect the outcomes of the 7th International Symposium on Multibody Systems and Mechatronics (7th MuSMe) in 2020, within the framework of the FEIbIM Commission for Robotics and Mechanisms and IFToMM Technical Committees for Multibody Dynamics and for Robotics and Mechatronics.

This book includes 46 scientific papers presented at the conference and reflecting the latest research in the fields of data mining, machine learning and decision-making. The international scientific conference “Intellectual Systems of Decision-Making and Problems of Computational Intelligence” was held in the Kherson region, Ukraine, from May 25 to 29, 2020. The papers are divided into three sections: “Analysis and Modeling of Complex Systems and Processes,” “Theoretical and Applied Aspects of Decision-Making Systems” and “Computational Intelligence and Inductive Modeling.” The book will be of interest to scientists and developers specialized in the fields of data mining, machine learning and decision-making systems.

Fundamentals and Recent Advances in Nanocomposites Based on Polymers and Nanocellulose brings together the latest research in cellulose-based nanocomposites, covering fundamentals, processing, properties, performance, applications, and the state of the art. The book begins by explaining the fundamentals of cellulose and cellulose-based nanocomposites, including sources, extraction, types, classification, linkages, model structure, model compounds, and characterization techniques. The second part of the book covers the incorporation of cellulose fillers to improve the properties or characteristics of nanocomposites, organized by composite category, including in aerogels, thermoplastic composites, thermoset composites, bioplastic composites, carbon nanofibers, rubber composites, carbon fibers, and foaming materials. Throughout these chapters, there is an emphasis on the latest innovations and application potential. Finally, applications are explored in more detail, notably focusing on the utilization of nanocellulose in biodegradable composites for biomedical applications, along with other important industrial application areas. This book is of great interest to researchers, scientists, and advanced students working with bio-based materials, and across polymer science, nanomaterials, composite materials, plastics engineering, chemical engineering, materials science and engineering, as well as R&D professionals, engineers, and industrialists interested in the development of bio-based materials for advanced applications or material commercialization. - Presents the fundamentals of cellulose-based nanocomposites, including sources, extraction, types, classification, linkages, structure, compounds, and characterization. - Discusses and analyzes the most suitable fabrication methods and processing techniques for cellulose as a reinforcement in a range of composites. - Opens the door to a range of cutting-edge applications and considers key aspects such as cost, lifecycle, and biodegradability.