Human Activity Recognition : Using Wearable Sensors and Smartphones.
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 physiologic...
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
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Chapman and Hall/CRC,
2013.
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| Series: | Chapman & Hall/CRC computer and information science series.
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| Subjects: | |
| Online Access: | CONNECT |
MARC
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| 100 | 1 | |a Labrador, Miguel A. | |
| 245 | 1 | 0 | |a Human Activity Recognition : |b Using Wearable Sensors and Smartphones. |
| 260 | |b Chapman and Hall/CRC, |c 2013. | ||
| 300 | |a 1 online resource. | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover -- Contents -- List of Figures -- List of Tables -- Preface -- Part I: Human Activity Recognition: Theory Fundamentals -- Chapter 1: Introduction -- Chapter 2: Human Activity Recognition -- Chapter 3: State of the Art in HAR Systems -- Chapter 4: Incorporating Physiological Signals to Improve Activity Recognition Accuracy -- Chapter 5: Enabling Real-Time Activity Recognition -- Chapter 6: New Fusion and Selection Strategies in Multiple Classifier Systems -- Chapter 7: Conclusions -- Part II: HAR in an Android Smartphone: A Practical Guide -- Chapter 8: Introduction to Android -- Chapter 9: Getting Ready to Develop Android Applications -- Chapter 10: Using the Smartphone's Sensors -- Chapter 11: Bluetooth Connectivity in Android -- Chapter 12: Saving and Retrieving Data in an Android Smartphone -- Chapter 13: Feature Extraction -- Chapter 14: Real-Time Classification in Smartphones Using WEKA -- Bibliography -- Back Cover. | |
| 520 | |a 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. | ||
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| 650 | 0 | |a Location-based services. | |
| 650 | 0 | |a Ubiquitous computing. | |
| 650 | 0 | |a Wearable computers. | |
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