Wearable sensors for gesture analysis in smart healthcare applications

Wearable sensors for gesture analysis in smart healthcare applications

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Technological solutions represent new opportunities to help elderly people and their caregivers in daily life. Understanding human behavior becomes thus essential in Ambient Assisted Living field especially for prevention and monitoring applications. In particular, recognition of human gestures is important to deliver personalized service to keep elderly people independent, while being monitored by caregivers. This chapter aims to underline the importance of recognizing behavior and in particular gesture in order to monitor older persons. An overview of the gesture recognition applications in AAL is therefore presented with a focus on the existing technologies used to capture hand gestures. Algorithms for data processing and classification are also described. Finally, an example of daily gesture recognition in AAL is presented where different gestures are recognized by mean of SensHand.

Chapter Contents:

  • Abstract
  • 4.1 Introduction: healthcare and technology
  • 4.2 Growth of smart sensors, wearables, and IoT
  • 4.3 Application scenarios
  • 4.4 Gesture recognition technology
  • 4.4.1 SensHand
  • 4.4.2 Other gloves
  • 4.4.3 Leap motion
  • 4.4.4 Smartwatch
  • 4.5 Description of the main approaches for gesture classification
  • 4.5.1 Features used in gesture recognition for AAL
  • 4.5.2 Features selections
  • 4.5.3 Classification algorithms
  • 4.6 SensHand for recognizing daily gesture
  • 4.7 Conclusion
  • References

Inspec keywords: gesture recognition; medical computing; assisted living; geriatrics; health care; biomedical equipment; pattern classification

Other keywords: human gestures; SensHand; gesture analysis; ambient assisted living; elderly people; smart healthcare applications; wearable sensors

Subjects: Data handling techniques; Automated buildings; User interfaces; Biology and medical computing

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