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Mobile technologies for smart healthcare system design

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mobile technologies for smart healthcare system designby Xiaonan Guo ... [et al.].
其他作者:	Guo, Xiaonan.
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	ix, 213 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Wireless communication systems in medical care.
電子資源:	https://doi.org/10.1007/978-3-031-57345-3
ISBN:	9783031573453$q(electronic bk.)

Mobile technologies for smart healthcare system design
Mobile technologies for smart healthcare system design[electronic resource] /by Xiaonan Guo ... [et al.]. - Cham :Springer Nature Switzerland :2024. - ix, 213 p. :ill., digital ;24 cm. - Wireless networks,2366-1445. - Wireless networks..

Chapter.1.Introduction -- Chapter.2.Contactless Activity Identification Using Commodity WiFi -- Chapter.3.Personalized Fitness Assistance using Commodity WiFi -- Chapter.4. Multi-person Fitness Assistance via Millimeter Wave -- Chapter.5.Non-intrusive Eating Habits Monitoring Using Millimeter Wave -- Chapter.6.Fitness Assistance Using Motion Sensor -- Chapter.7.Fine-grained Gesture Recognition and Sign Language Interpretation via Photoplethysmography (PPG) on Smartwatches -- Chapter.8.Continuous User Authentication via PPG -- Chapter.9.Conclusion and Future Directions.

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.

ISBN: 9783031573453$q(electronic bk.)

Standard No.: 10.1007/978-3-031-57345-3doiSubjects--Topical Terms:

676419
Wireless communication systems in medical care.

LC Class. No.: R119.9

Dewey Class. No.: 610.285

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520 $a 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.
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