The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Trajectory Estimation of Center of Plantar Foot Pressure Using Gaussian Process Regression

가우시안 프로세스 회귀를 이용한 족저압 중심 궤적 추정

  • Choi, Yuna (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Lee, Daehun (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Choi, Youngjin (Department of Electrical and Electronic Engineering, Hanyang University)
  • Received : 2022.03.04
  • Accepted : 2022.04.07
  • Published : 2022.08.31
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Abstract

This paper proposes a center of plantar foot pressure (CoP) trajectory estimation method based on Gaussian process regression, with the aim to show robust results regardless of the regions and numbers of FSRs of the insole sensor. This method can bring an interpolation between the measurement points inside the wearable insole sensor, and two experiments are conducted for performance evaluation. For this purpose, the input data used in the experiment are generated in three types (13 FSRs, 8 FSRs, 5 FSRs) according to the regions and numbers of FSRs. First, the estimation results of the CoP trajectory are compared using Gaussian process regression and weighted mean. As a result of each method, the estimation results of the two methods were similar in the case of 13 FSRs data. On the other hand, in the case of the 8 and 5 FSRs data, the weighted mean varies depending on the regions and numbers of FSRs, but the estimation results of Gaussian process regression showed similar results in spite of reducing the regions and numbers. Second, the estimation results of the CoP trajectory based on Gaussian process regression during several gait cycles are analyzed. In five gait cycles, the previous cycle and the current estimation results are compared, and it was confirmed that similar trajectories appeared in all. In this way, the method of estimating the CoP trajectory based on Gaussian process regression showed robust results, and stability was confirmed by yielding similar results in several gait cycles.

Keywords

Acknowledgement

This work was supported in part by the Technology Innovation Program funded by the Korean Ministry of Trade, industry and Energy, (20017345 and 20008908), Republic of Korea

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