Jerry Cheng

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.

This Springer Brief provides a new approach to prevent user spoofing by using the physical properties associated with wireless transmissions to detect the presence of user spoofing. The most common method, applying cryptographic authentication, requires additional management and computational power that cannot be deployed consistently. The authors present the new approach by offering a summary of the recent research and exploring the benefits and potential challenges of this method. This brief discusses the feasibility of launching user spoofing attacks and their impact on the wireless and sensor networks. Readers are equipped to understand several system models. One attack detection model exploits the spatial correlation of received signal strength (RSS) inherited from wireless devices as a foundation. Through experiments in practical environments, the authors evaluate the performance of the spoofing attack detection model. The brief also introduces the DEMOTE system, which exploits the correlation within the RSS trace based on each device’s identity to detect mobile attackers. A final chapter covers future directions of this field. By presenting complex technical information in a concise format, this brief is a valuable resource for researchers, professionals, and advanced-level students focused on wireless network security.