센서학회지 (Journal of Sensor Science and Technology)

  • 제25권2호
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  • Pages.79-85
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  • 2016
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  • 1225-5475(pISSN)
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  • 2093-7563(eISSN)
한국센서학회 (The Korean Sensors Society)
권호 표지
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Recognition of Falls and Activities of Daily Living using Tri-axial Accelerometer and Bi-axial Gyroscope

  • Park, Geun-chul (Dept. of Interdisciplinary program in Biomedical Engineering, Pusan National University) ;
  • Kim, Soo-Hong (Dept. of Interdisciplinary program in Biomedical Engineering, Pusan National University) ;
  • Kim, Jae-hyung (Dept. of Computer Simulation, Inje University) ;
  • Shin, Beum-joo (Dept. of applied Information Technology & Engineering, Pusan National University) ;
  • Jeon, Gye-rok (Dept. of Biomedical Engineering, School of Medicine, Pusan National University)
  • 투고 : 2016.02.22
  • 심사 : 2016.03.24
  • 발행 : 2016.03.31
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초록

This paper proposes a threshold-based fall recognition algorithm to discriminate between falls and activities of daily living (ADL) using a tri-axial accelerometer and a bi-axial gyroscope sensor mounted on the upper sternum. The experiment was executed ten times according to the proposed experimental protocol. The output signals of the tri-axial accelerometer and the bi-axial gyroscope were measured during eight falls and eleven ADL action sequences. The threshold values of the signal vector magnitude (SVM_Acc), angular velocity (${\omega}_{res}$), and angular variation (${\theta}_{res}$) parameter were calculated using MATLAB. From the preliminary study, three thresholds (TH1, TH2, and TH3) were set so that the falls could be distinguished from ADL. When the parameter SVM_Acc is greater than 2.5 g (TH1), ${\omega}_{res}$ is greater than 1.75 rad/s (TH2), and ${\theta}_{res}$ is greater than 0.385 rad (TH3), these action sequences are recognized as falls. If at least one or more of these conditions is not satisfied, the sequence is classified as ADL.

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참고문헌

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