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http://dx.doi.org/10.7471/ikeee.2020.24.1.9

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

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)
Publication Information
Journal of IKEEE / v.24, no.1, 2020 , pp. 9-18 More about this Journal
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.
Keywords
automatic walking mode change; above knee prosthesis; machine learning; random forest;
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Times Cited By KSCI : 2  (Citation Analysis)
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