PPG Signal Analysis

An Introduction Using MATLAB®
1. Auflage 2023
ISBN: 978-0-367-60827-9
Verlag: CRC Press

Buch, Englisch, 298 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 456 g

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.

Zielgruppe

Academic and Professional Practice & Development

Autoren/Hrsg.

Elgendi, Mohamed

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Drahtlostechnologie
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik

Inhaltsverzeichnis

1. Math Foundations. 2. Photoplethysmogram Signals. 3. Visualization of PPG Signals. 4. Pre-processing of PPG Signals. 5. Signal Quality Assessment. 6. PPG Feature Extraction. 7. A Generic Method for Event Detection. 8. Feature Selection. 9. Identifying Adverse Events. 10. Application of PPG to Global Health. 11. Available PPG Databases

Über Autor(innen)

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.