Overview

This book serves as a current resource for Photoplethysmogram (PPG) signal analysis using MATLAB®. This technology is critical in the evaluation of medical and diagnostic data utilized in mobile devices. Information and methodologies outlined in the text can be used to learn the empirical and experimental process (including data collection, data analysis, feature extractions, and more) from inception to conclusion. This book also discusses how introduced methodologies can be used and applied as tools that will teach the user how to validate, test, and simulate developed algorithms before implementing and deploying the algorithms on wearable, battery-driven, or point-of-care devices.

Full Product Details

9781138049710

Table of Contents

Reviews

This is excellent!! Really. PPG Analysis - Introduction Using Matlab provides a unique and relatively comprehensive introduction to photoplethysmogram in the context of digital health. This is a fun, hands-on introduction to the important emerging field of PPG. This book will help inspire a new generation to join us in finding out how to use PPG for multiple digital health applications. - Maxime Cannesson, Professor of Clinical Anesthesiology, UCLA, USA A wonderful comprehensive hands-on reference for students and researchers doing practical PPG signal analysis. Although the code examples are in MATLAB, the book content is useful for researchers working with any math package. Richard Ribon Fletcher, Mobile Technology Group, Massachusetts Institute of Technology, USA It is a very informative book that is truly needed in the field. It was clearly taught from an engineering perspective. By reading this book the student is given a very real opportunity to make significant discoveries. This book would work well as a supplementary source for an introductory course in computational analysis of PPG signals for undergraduate and postgraduate students. - Kirk Shelley, Professor Emeritus of Anesthesiology, Yale University, USA I enjoyed reading this book - it encompasses the fascinating field of photoplethysmography and modern analysis techniques using clear Matlab focussed examples. It is a great contribution to the field. I think this book should be given a privileged spot on the bookshelf of every student and researcher in the cardiovascular, vascular optics and digital health sciences. -- Dr John Allen, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK

This is excellent!! Really. PPG Analysis - Introduction Using Matlab provides a unique and relatively comprehensive introduction to photoplethysmogram in the context of digital health. This is a fun, hands-on introduction to the important emerging field of PPG. This book will help inspire a new generation to join us in finding out how to use PPG for multiple digital health applications. - Maxime Cannesson, Professor of Clinical Anesthesiology, UCLA, USA A wonderful comprehensive hands-on reference for students and researchers doing practical PPG signal analysis. Although the code examples are in MATLAB, the book content is useful for researchers working with any math package. Richard Ribon Fletcher, Mobile Technology Group, Massachusetts Institute of Technology, USA It is a very informative book that is truly needed in the field. It was clearly taught from an engineering perspective. By reading this book the student is given a very real opportunity to make significant discoveries. This book would work well as a supplementary source for an introductory course in computational analysis of PPG signals for undergraduate and postgraduate students. - Kirk Shelley, Professor Emeritus of Anesthesiology, Yale University, USA I enjoyed reading this book - it encompasses the fascinating field of photoplethysmography and modern analysis techniques using clear Matlab focussed examples. It is a great contribution to the field. I think this book should be given a privileged spot on the bookshelf of every student and researcher in the cardiovascular, vascular optics and digital health sciences. -- Dr John Allen, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK

Author Information

Dr. Mohamed (Moe) Elgendi is currently a Senior Postdoctoral Fellow at UBC's Department of Obstetrics and Gynecology, and Adjunct Professor at UBC's Department of Electrical and Computer Engineering, a Senior Member at IEEE, and a Senior fellow at Howard Brain Sciences Foundation. In addition to his 10+ years of experience in the field of data analysis, he received training on Leadership in Education from MIT. Dr. Elgendi's expertise in the areas of digital health, data science, artificial intelligence, and visualization includes his work in Global Health with the PRE-EMPT Initiative (funded by the Bill and Melinda Gates Foundation), the Institute for Media Innovation at Nanyang Technological University (Singapore), and Alberta's Stollery Children's Hospital (Canada). Dr. Elgendi specializes in bridging the areas of engineering, computer science, psychology, and medicine for knowledge translation.

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