Human Activity Recognition Using Wearable Sensors and Smartphones

Developed from the authors' nearly four years of rigorous research in the field, this 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...

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Bibliographic Details
Main Authors Labrador, Miguel A., Lara Yejas, Oscar D.
Format eBook Book
LanguageEnglish
Published Boca Raton Chapman and Hall/CRC 2014
CRC Press, Taylor & Francis Group
CRC Press LLC
CRC Press
Edition1
SeriesChapman & Hall/CRC computer & information science series
Subjects
Location-based services
Ubiquitous computing
Wearable computers
Tcp
Stat Ic
ALR
Bluetooth Device
Import Java
Gps Sensor
Semi-supervised Learning
Android Software Development Kit
Android Operating System
Activity Recognition System
Young Men
Human Activity Recognition Model
Android Applications
Android Smartphone
HAR System
Public Void
Mobile Application User Interface
AVD
SQLite Database
Android Platform
Dalvik Virtual Machine
HAR
Data Link Layer Frame
Acceleration Signals
FE
Online AccessGet full text
ISBN1466588276
9781466588271
DOI10.1201/b16098

Cover

Table of Contents:
  • 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