DOI QR코드

DOI QR Code

Implementation of Fall Direction Detector using a Single Gyroscope

자이로센서를 이용한 낙상 방향 탐지 시스템 구현

  • 문병현 (대구대학교 정보통신공학부) ;
  • 류정탁 (대구대학교 전자전기공학부)
  • Received : 2016.03.16
  • Accepted : 2016.04.25
  • Published : 2016.04.30

Abstract

Falling situations are extremely critical events for the elderly person who requires timely and adequate emergency service. For the case of emergency, the information of falling and its direction can be used as an important information for the first aid treatment of the injured person. In this paper, a falling detection system which can pinpoint the falling event with the falling direction is implemented. In order to detect the fall situation, a single gyroscope (MPU-6050) is used in the developed system. The fall detection algorithm that can classify 8 different fall directions such as front, back, left, right and in between falls is proposed. The direction of the fall is decided by examining the acceleration values of X and Y directions of the sensor. It is shown that the proposed algorithm successfully detects the falling event and the falling direction with probability of 97% for a selected value of acceleration threshold.

낙상은 응급상황이 발생한 노인에게는 적절한 시간이 응급처치가 요구되는 주요한 상태이다. 응급상황의 경우, 낙상의 발생과 낙상 방향은 초기 상태의 응급처치를 위한 중요한 정보로 사용될 수 있다. 본 논문에서는 낙상의 발생과 방향을 정확히 판단하는 시스템을 구현하였다. 낙상과 방향을 감지하기 위하여 하나의 3축 자이로도센서(MPU-6050)를 사용하였다. 제안된 낙상 방향 알고리듬은 X와 Y축 가속도값을 사용하여 낙상여부와 앞, 뒤 좌,우 및 중간방향을 포함한 8개 낙상방향을 감지하였다. 제안된 시스템은 선택적인 가속도 임계값을 사용하여 97% 이상의 낙상과 낙상방향을 성공적으로 감지함을 보였다.

Keywords

References

  1. P. Pierleoni et. al., "A High Reliability Wearable Device for Elderly Fall Detection", IEEE Sensors Journal, Vol. 15, No. 8, pp. 4544-4553, 2015. https://doi.org/10.1109/JSEN.2015.2423562
  2. F. Bianchi et. al., "Barometric Pressure and Triaxial Accelerometry-Based Falls Event Detection", IEEE Trans. on Neural Systems and Rehabilitation Engineering, Vol. 18, No.6, pp. 619-627, 2010. https://doi.org/10.1109/TNSRE.2010.2070807
  3. P. Kostopoulos et. al., "F2D: A Fall Detection System Tested with Real Data from Daily Life of Elderly People", 17th Internatioal Conference of E-health Networking, Application & services (HealthCom) , pp. 397-403, 2015.
  4. Nitha V.P and Sukesh K. A, "Design of a Telemonitoring System for Detecting Falls fo the Elderly", 2015 ICGCIoT, pp. 800-803, 2015.
  5. W.J. Lee et. al., "Design flow of Wearable Heart Monitoring and Fall Detection System using Wireless Intelligent Personal Communication Node", IEEE International Conference on Electro/ Information Technology (EIT) , pp. 314-319, 2015.
  6. H. Gjoreski, M. Lustrek and M. Gams, "Accelerometer Placement for Posture Recognition and Fall Detection," 7th international Conference of Intelligent Environment, pp. 47-54, 2011.
  7. Y. Hou, N. Li and Z. Huang, " Triaxial Accelerometer-Based Real Time Fall Event Detection", 2012 International Conference on Informaion Society(i-Society), pp. 386-390, 2012.

Cited by

  1. Implementation of a real-time fall detection system for elderly Korean farmers using an insole-integrated sensing device vol.48, pp.1, 2020, https://doi.org/10.1080/10739149.2019.1648293