Human Activity Recognition: Using Wearable Sensors and Smartphones (Chapman & Hall/CRC Computer and Information Science Series Book 30)

__Learn How to Design and Implement HAR Systems__ The pervasiveness and range of capabilities of today’s mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. **Human Activity Recognition: Using Wearable Sensors and Smartphones** focuses on the automatic identification of human activities from pervasive wearable sensors—a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations. Developed from the authors’ nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user’s activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework. The pervasiveness and range of capabilities of today's mobile devices have enabled a wide spectrum of mobile applications, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data, that are transforming our daily lives. Human Activity Recognition: Using Wearable Sensors and Smart-phones focuses on the automatic identification of human activities from pervasive wearable sensors-a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations. Developed from the authors' nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user's activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework. Features, Describes the potential of HAR in application areas, including health monitoring, entertainment, and tactical operations, Presents the fundamentals of feature extraction and machine learning tools, Looks at the design of HAR systems from a research point of view, Shows how to perform real-time HAR, Offers a hands-on guide to developing mobile HAR applications for an Android smartphone, Explores future research considerations Book jacket