04337nam a22005895i 4500 978-3-031-57345-3 DE-He213 20251030113036.0 cr nn 008mamaa 240912s2024 sz | s |||| 0|eng d 9783031573453 978-3-031-57345-3 10.1007/978-3-031-57345-3 doi TK5105.5-5105.9 UKN bicssc COM043000 bisacsh UKN thema Guo, Xiaonan. author. aut http://id.loc.gov/vocabulary/relators/aut 84111 Mobile Technologies for Smart Healthcare System Design [electronic resource] / by Xiaonan Guo, Yan Wang, Jerry Cheng, Yingying (Jennifer) Chen. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. IX, 213 p. 94 illus., 89 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Wireless Networks, 2366-1445 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. . Computer networks . 60157 Wireless communication systems. 65781 Mobile communication systems. 65782 Medical informatics. 60693 Computer Communication Networks. 65689 Wireless and Mobile Communication. 65786 Health Informatics. Wang, Yan. author. aut http://id.loc.gov/vocabulary/relators/aut 84112 Cheng, Jerry. author. aut http://id.loc.gov/vocabulary/relators/aut 84113 Chen, Yingying (Jennifer). author. aut http://id.loc.gov/vocabulary/relators/aut 84114 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031573446 Printed edition: 9783031573460 Printed edition: 9783031573477 Wireless Networks, 2366-1445 67497 https://doi.org/10.1007/978-3-031-57345-3 ZDB-2-SME ZDB-2-SXM 63289 63289