Application of random forest algorithm in terrain recognition to control active above-knee prosthesis

doi:10.3969/j.issn.2095-4344.2015.53.014

Abstract

Abstract:

BACKGROUND: In the research of the active above-knee prosthesis, the existing motion pattern recognition methods have shown promising results, but the further improvement of the recognition accuracy and the reduction of the response time are still necessary.

OBJECTIVE: To establish a terrain recognition system based on the random forest algorithm, achieve the identification of the front terrain, and obtain the motion mode of the subject on the terrain for the control of artificial limb.

METHODS: A laser distance sensor and an inertial measurement unit sensor were fixed on the waist to collect the terrain information and human motion signals. The collected data were filtered and the characteristic values were extracted from the data. The random forest algorithm was applied in the establishment of the classifier, which was used to recognize the terrain.

RESULTS AND CONCLUSION: The results showed that the terrain recognition system could recognize level ground, stair ascent/descent and ramp ascent/descent at a high accuracy, which could contribute to the control of the active above-knee prosthesis.

中国组织工程研究杂志出版内容重点：人工关节；骨植入物；脊柱；骨折；内固定；数字化骨科；组织工程

CLC Number:

R318

Zhang Yan, Gao Xin, Chen Ling-ling, Zhang Hao-miao. Application of random forest algorithm in terrain recognition to control active above-knee prosthesis[J]. Chinese Journal of Tissue Engineering Research, 2015, 19(53): 8609-8614.

Figures/Tables 1

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