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.
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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.
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.
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