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PPG Signal Analysis
An Introduction Using MATLAB®
Taschenbuch von Mohamed Elgendi
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor

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.

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

Details
Erscheinungsjahr: 2023
Fachbereich: Therapie
Genre: Importe, Medizin
Rubrik: Wissenschaften
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367608279
ISBN-10: 0367608278
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Elgendi, Mohamed
Hersteller: CRC Press
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 234 x 156 x 16 mm
Von/Mit: Mohamed Elgendi
Erscheinungsdatum: 25.09.2023
Gewicht: 0,456 kg
Artikel-ID: 127491052
Über den Autor

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.

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

Details
Erscheinungsjahr: 2023
Fachbereich: Therapie
Genre: Importe, Medizin
Rubrik: Wissenschaften
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367608279
ISBN-10: 0367608278
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Elgendi, Mohamed
Hersteller: CRC Press
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 234 x 156 x 16 mm
Von/Mit: Mohamed Elgendi
Erscheinungsdatum: 25.09.2023
Gewicht: 0,456 kg
Artikel-ID: 127491052
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