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A Study on Random Forest-based Estimation Model for Changing the Automatic Walking Mode of Above Knee Prosthesis

대퇴의족의 자동 보행 모드 변경을 위한 랜덤 포레스트 기반 추정 모델 개발에 관한 연구

  • Na, Sun-Jong (Dept. of Electronics Engineering, Korea Polytechnic University) ;
  • Shin, Jin-Woo (Dept. of Electronics Engineering, Korea Polytechnic University) ;
  • Eom, Su-Hong (Dept. of Electronics Engineering, Korea Polytechnic University) ;
  • Lee, Eung-Hyuk (Dept. of Electronics Engineering, Korea Polytechnic University)
  • Received : 2020.03.06
  • Accepted : 2020.03.26
  • Published : 2020.03.31

Abstract

The pattern recognition or fuzzy inference, which is mainly used for the development of the automatic walking mode change of the above knee prosthesis, has a disadvantage in that it is difficult to estimate with the immediate change of the walking environment. In order to solve a disadvantage, this paper developed an algorithm that automatically converts the walking mode of the next step by estimating the walking environment at a specific gait phase. Since the proposed algorithm should be implanted and operated in the microcontroller, it is developed using the random forest base in consideration of calculation amount and estimated time. The developed random forest based gait and environmental estimation model were implanted in the microcontroller and evaluated for validity.

의족의 자동 보행 모드 변경 알고리즘 개발에는 주로 사용되는 패턴 인식 또는 퍼지 추론 기법을 이용하지만 즉각적인 보행 환경 변화에는 대응하기 어렵다는 단점을 가진다. 이러한 한계점을 해결하고자 본 논문에서는 한 보행 주기 내 특정 보행단계에서의 보행 환경 추정을 통해 다음 걸음의 보행 모드를 자동으로 변환하는 알고리즘을 개발하였다. 제안하는 알고리즘은 마이크로 컨트롤러 내에 이식되어 운용되어야 하므로 계산량과 추정 소요 시간을 고려하여 랜덤포레스트 기반을 사용하여 개발하였다. 개발된 랜덤포레스트 기반의 보행 단계 및 환경 추정 모델은 마이크로 컨트롤러 내에 이식되어 유효성 평가를 진행하였다.

Keywords

References

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