Fall？Detection Algorithm Using Plantar Pressure and Acceleration Data
- Fall？Detection Algorithm Using Plantar Pressure and Acceleration Data
- 김충현; 박지수; 이창민; 박신석
- Activities of daily living; Center of pressure; Decision tree; Fall detection; Force sensing resistor; Inertial
- Issue Date
- International Journal of Precision Engineering and Manufacturing
- In this study, experiments are conducted for four types of falls and eight types of activities of daily living with an integrated
sensor system that uses both an inertial measurement unit and a plantar-pressure measurement unit and the fall-detection
performance is evaluated by analyzing the acquired data with the threshold method and the decision-tree method. In general,
the decision-tree method shows better performance than the threshold method, and the fall-detection accuracy increases when
the acceleration and center-of-pressure (COP) data are used together, rather than when each data point is used separately.
The results show that the fall-detection algorithm that applies both acceleration and COP data to the decision-tree method
has a fall-detection accuracy of 95% or higher and a sufficient lead time of 317 ms on average.
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- KIST Publication > Article
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