Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineering, computer science, medical physics, and anyone preparing for a career in biomedical sciences and engineering.

Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineering, computer science, medical physics, and anyone preparing for a career in biomedical sciences and engineering.

"Biomedical Sensors and Measurement" is an interdisciplinary book combining electronics with biology and medicine. It gives an overview of the concept and principle of biomedical sensors and measurement. First, the basic theory and technology are explained, followed by details of the physical sensors, chemical sensors, biosensors and their typical applications in biomedicine. Furthermore, the interface technology of the sensors and the typical measurement systems is presented. The large amount of vivid and specific figures and formulas will help to deepen the understanding of the fundamental and new applications involving biomedical sensors and measurement technology. The book is intended for biomedical engineers, medical physicists and other researchers and professionals in biomedicine-related specialties, especially interdisciplinary studies. Prof. Ping Wang and Dr. Qingjun Liu both work at the Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, China.

Overview of biomedical data science -- Spreadsheet tools and tips -- Biostatistics primer -- Data visualization -- Introduction to databases -- Big data -- Bioinformatics and precision medicine -- Programming languages for data analysis -- Machine learning -- Artificial intelligence -- Biomedical data science resources -- Appendix A: Glossary -- Appendix B: Using data.world -- Appendix C: Chapter exercises.

Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Life expectancy is increasing, and we are all expected to work for longer as a result. A balance must be found between the demands of work and human capabilities, and this makes the prevention of workplace-related health problems more important than ever. Emerging technologies, such as smart textiles, wearable devices, and the Internet of Things have enabled the development of intelligent biomedical clothing and the integration of pervasive sensitive services into the environment, and together with ambient intelligence technology techniques and big data analytics, have fostered a proliferation of p-Health monitoring solutions. This book presents a collection of the most significant challenges and advances in the field of intelligent workspaces and personalized ergonomics, bringing together the most relevant results of various international research projects. The book is organized into three main sections: Personalized Ergonomics, which explores the need for practical and reliable risk assessment methods for the prevention of musculoskeletal disorders and the enhancement of the workplace; Pervasive Technology for Intelligent Workplaces, which identifies the opportunities and challenges of technology-based interventions and the security and privacy issues of the smart workplace; and Data Warehouse Governance and Analytics. The book concludes with a chapter on lessons learnt. The transformation of the working environment into a healthy and intelligent space will not only support ergonomists, employees and employers, but may also be the solution to the sustainability of our current social welfare systems, and the book will be of interest to all those concerned with workplace health.

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. Examines the development and application of data analytics applications in biomedical data Presents innovative classification and regression models for predicting various diseases Discusses genome structure prediction using predictive modeling Shows readers how to develop clinical decision support systems Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks