Guo / Wang / Cheng

Mobile Technologies for Smart Healthcare System Design

Springer

ISBN 978-3-031-57344-6

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181,89 €

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auch verfügbar als eBook (PDF) für 181,89 €

Bibliografische Daten

Fachbuch

Buch. Hardcover

2024

5 s/w-Abbildungen, 89 Farbabbildungen.

In englischer Sprache

Umfang: ix, 213 S.

Format (B x L): 15,5 x 23,5 cm

Verlag: Springer

ISBN: 978-3-031-57344-6

Weiterführende bibliografische Daten

Das Werk ist Teil der Reihe: Wireless Networks

auch verfügbar als eBook (PDF) für 181,89 €

Produktbeschreibung

This book offers a comprehensive examination of mobile technologies in healthcare. It starts by covering wireless solutions, including WiFi signals and mmWave technology for activity recognition, fitness assistance, and eating habit monitoring. The discussion extends to wearable technologies that focus on personal fitness and injury prevention, highlighting the innovative use of PPG sensors in wearables, which enable gesture recognition and user authentication. Based on thorough analyses on the challenges of designing robust mobile healthcare systems, this book addresses the difficulty of gathering accurate and reliable sensor data amidst the variability of human activities. It explores solutions using advanced sensing modalities, such as WiFi, mmWave, and PPG sensors, and robust algorithms for feature extraction to interpret activities, gestures, and biometrics. It also tackles system robustness across diverse environments and practical issues such as reducing training efforts, handling motion artifacts, and the implementation of these systems using commercially available devices. The primary audience for this book targets computer science students and researchers working in mobile computing, smart healthcare, human-computer interaction and artificial intelligence/machine learning. Professionals and consultants focused on advancing mobile-based healthcare solutions will want to purchase this book as a reference.

Autorinnen und Autoren

Kundeninformationen

Presents edge mobile technologies to address key challenges in developing real-world healthcare applications Offers reducing training effort, handling motion artifacts and implementing systems using commercially available devices Focuses on practical AI/ML solutions

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