04158nam a22005415i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050002000172072001600192072002300208072001500231100008200246245015000328250001800478264006900496300006400565336002600629337002600655338003600681347002400717490003400741505058000775520144301355650003202798650004302830650004102873650003202914650004402946650004602990650002403036700007903060700008203139700009503221710003403316773002603350776003603376776003603412776003603448830004103484856004603525912001403571912001403585999001703599978-3-031-57345-3DE-He21320251030113036.0cr nn 008mamaa240912s2024    sz |    s    |||| 0|eng d  a97830315734539978-3-031-57345-37 a10.1007/978-3-031-57345-32doi 4aTK5105.5-5105.9 7aUKN2bicssc 7aCOM0430002bisacsh 7aUKN2thema1 aGuo, Xiaonan.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut98411110aMobile Technologies for Smart Healthcare System Designh[electronic resource] /cby Xiaonan Guo, Yan Wang, Jerry Cheng, Yingying (Jennifer) Chen.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aIX, 213 p. 94 illus., 89 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aWireless Networks,x2366-14450 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.  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. . 0aComputer networks .960157 0aWireless communication systems.965781 0aMobile communication systems.965782 0aMedical informatics.96069314aComputer Communication Networks.96568924aWireless and Mobile Communication.96578624aHealth Informatics.1 aWang, Yan.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9841121 aCheng, Jerry.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9841131 aChen, Yingying (Jennifer).eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9841142 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303157344608iPrinted edition:z978303157346008iPrinted edition:z9783031573477 0aWireless Networks,x2366-144596749740uhttps://doi.org/10.1007/978-3-031-57345-3  aZDB-2-SME  aZDB-2-SXM  c63289d63289