This book is a detailed exploration of mobile technologies in the healthcare sector. It begins with an overview of WiFi-based systems for activity recognition, utilizing existing infrastructure for health monitoring, and then examines mmWave technology for its precision in health systems and the design of a sophisticated fitness assistant system. The narrative progresses to wearable technologies, emphasizing their role in personal fitness and injury prevention. A significant focus is on eating habit monitoring for comprehensive dietary analysis. The book concludes with an innovative use of PPG sensors in wearables for intricate applications, suck as gesture recognition and user authentication. Looking ahead, this book outlines future research directions, emphasizing the importance of securing deep learning techniques in mobile health technologies, developing adaptive systems for dynamic environments, and creating integrated systems for personalized medicine and comprehensive health monitoring. This forward-looking perspective highlights the need for proactive, preventive and tailored healthcare solutions.

This book also discusses various challenges in designing effective and robust mobile healthcare systems. One of the major challenges is collecting accurate and reliable sensor data, given the complexity and variability of human activities. It tackles this challenge through innovative sensing modalities like WiFi, millimeter wave signals, and photoplethysmography that can capture fine-grained details regarding human activities and physiology. Robust algorithms are designed to extract meaningful features from the sensor data to interpret activities, gestures, and biometrics. System robustness across diverse environments is another big challenge in mobile healthcare. The solutions presented by this book could adapt to different settings using advanced learning techniques such as environment-invariant analysis and domain adaptation training. The book also deals with practical issues like reducing training efforts, handling motion artifacts and implementing systems using commercially available devices. Overall, this book provides comprehensive methodologies leveraging cutting-edge mobile technologies to address key challenges in developing real-world healthcare applications for continuous monitoring, personalized assistance, dietary tracking, gesture recognition and user authentication. The systems are designed to work reliably despite environmental variations, individual differences, and device constraints.

The primary audience for this book targets researchers working in mobile computing, smart healthcare, human-computer interaction, cyber-physical systems, AI/ML and cybersecurity. Specifically, it targets advanced-level students majoring in electronic engineering, computer engineering, computer science, biomedical engineering, data science, biobehavioral health and information science. Professional and consultants focusing on advancing mobile computing, smart healthcare, human-computer interaction, Internet-of-Things, and cybersecurity through the application of sensing modalities, signal processing and AI/ML will also find this book highly valuable.

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