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Fall Detection for Mobile Phone based on Movement Pattern

스마트 폰을 사용한 움직임 패턴 기반 넘어짐 감지

  • 보비에트 (전남대학교 전자컴퓨터공학과) ;
  • 황민탕 (전남대학교 전자컴퓨터공학과) ;
  • 이창무 (전남대학교 전자컴퓨터공학과) ;
  • 최덕재 (전남대학교 전자컴퓨터공학과)
  • Received : 2012.04.27
  • Accepted : 2012.07.23
  • Published : 2012.08.31

Abstract

Nowadays, recognizing human activities is an important subject; it is exploited widely and applied to many fields in real-life, especially in health care and context aware application. Research achievements are mainly focused on activities of daily living which are useful for suggesting advises to health care applications. Falling event is one of the biggest risks to the health and well-being of the elderly especially in independent living because falling accidents may be caused from heart attack. Recognizing this activity still remains in difficult research area. Many systems equipped wearable sensors have been proposed but they are not useful if users forget to wear the clothes or lack ability to adapt themselves to mobile systems without specific wearable sensors. In this paper, we develop a novel method based on analyzing the change of acceleration, orientation when the fall occurs and measure their similarity to featured fall patterns. In this study, we recruit five volunteers in our experiment including various fall categories. The results are effective for recognizing fall activity. Our system is implemented on G1 smart phone which are already plugged accelerometer and orientation sensors. The popular phone is used to get data from accelerometer and results showthe feasibility of our method and significant contribution to fall detection.

인간의 동작 인식은 건강관리, 상황기반 응용 등 실제적인 삶의 여러 부분에서 이용할 수 있기 때문에 중요한 주제이다. 건강관리를 위한 조언을 제공하는데 사용될 수 있기 때문에 동작인식 중 일상생활 동작인식이 주로 연구되고 있다. 특별히 넘어짐은 심장문제로 발생할 수 있기 때문에 넘어짐 인식은 독거 노인의 건강한 삶에 중요한 역할을 할 수 있다. 넘어짐 인식은 여전히 어려운 연구과제이다. 넘어짐 인식을 위해 몸에 여러 종류의 센서를 부착하는 시스템이 제안되었지만 이는 사용자가 센서를 부착하는 것을 잊어버리거나 이런 시스템에 익숙하지 않기 때문에 유용성에 문제가 있다. 본 연구에서는 사용자가 휴대하고 있는 스마트 폰 내의 가속도 및 자이로센서 값의 변화를 분석하여 알려진 넘어짐 패턴과 유사성을 분석하여 넘어짐을 판단하는 방법을 제안한다. 이 연구를 위해 5명의 자원자를 모집하여 다양한 종류의 넘어짐을 실험하였다. 실험결과는 본 연구를 통해서 넘어짐 인식을 위한 제안한 방식이 유효하다는 것을 보여준다. 실험 알고리즘은 많이 사용되고 있는 G1 스마트 폰 위에 구현하였다.

Keywords

References

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