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010   $a3-031-57345-5
024 7 $a10.1007/978-3-031-57345-3
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035   $a(Au-PeEL)EBL31661195
035   $a(CKB)35040001000041
035   $a(DE-He213)978-3-031-57345-3
035   $a(EXLCZ)9935040001000041
100   $a20240912d2024      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMobile Technologies for Smart Healthcare System Design /$fby Xiaonan Guo, Yan Wang, Jerry Cheng, Yingying (Jennifer) Chen
205   $a1st ed. 2024.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024.
215   $a1 online resource (219 pages)
225 1 $aWireless Networks,$x2366-1445
311 08$a3-031-57344-7 
327   $aChapter.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.
330   $aThis book offers a comprehensive examination of mobile technologies in healthcare. It starts by covering wireless solutions, including WiFi signals and mmWave technology for activity recognition, fitness assistance, and eating habit monitoring. The discussion extends to wearable technologies that focus on personal fitness and injury prevention, highlighting the innovative use of PPG sensors in wearables, which enable gesture recognition and user authentication. Based on thorough analyses on the challenges of designing robust mobile healthcare systems, this book addresses the difficulty of gathering accurate and reliable sensor data amidst the variability of human activities. It explores solutions using advanced sensing modalities, such as WiFi, mmWave, and PPG sensors, and robust algorithms for feature extraction to interpret activities, gestures, and biometrics. It also tackles system robustness across diverse environments and practical issues such as reducing training efforts, handling motion artifacts, and the implementation of these systems using commercially available devices. The primary audience for this book targets computer science students and researchers working in mobile computing, smart healthcare, human-computer interaction and artificial intelligence/machine learning. Professionals and consultants focused on advancing mobile-based healthcare solutions will want to purchase this book as a reference. .
410  0$aWireless Networks,$x2366-1445
606   $aComputer networks
606   $aWireless communication systems
606   $aMobile communication systems
606   $aMedical informatics
606   $aComputer Communication Networks
606   $aWireless and Mobile Communication
606   $aHealth Informatics
615  0$aComputer networks.
615  0$aWireless communication systems.
615  0$aMobile communication systems.
615  0$aMedical informatics.
615 14$aComputer Communication Networks.
615 24$aWireless and Mobile Communication.
615 24$aHealth Informatics.
676   $a004.6
700   $aGuo$b Xiaonan$01770804
701   $aWang$b Yan$0554895
701   $aCheng$b Jerry$01770805
701   $aChen$b Yingying (Jennifer)$01770806
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910887879203321
996   $aMobile Technologies for Smart Healthcare System Design$94254579
997   $aUNINA