Objective To carry out a research of terrain recognition on intelligent knee joint from the perspective of pure visual information.Methods The whole experimental environment was illuminated by halogen lamp, which made the brightness and color temperature of the set scene change less. The machine vision module was embedded in the intelligent knee joint control system. The road image data was collected by the camera in real time, and the captured image was processed in grayscale. The normalized cross correlation algorithm (NCC) was used to match the image pattern to identify the corresponding road conditions.Results The accuracy rates of the road vision, up/down hill, and up/down stairs recognized by the machine vision module were 88.6%, 85.3%, 78.4%, 87.5%, and 77.9%, respectively. The recognition effect was good, and the recognition time was within one second, real-time performance was strong.Conclusion The effectiveness and feasibility of intelligent knee joint prosthetic road condition recognition based on pure visual information is proved.
YU Bei-bei
,
MENG Qing-yun
,
YU Hong-liu
,
CAO Wu-jing
,
ZHAO Wei-liang
. Road Condition Identification of Intelligent Lower Limb Prosthesis Based on Visual Information[J]. Chinese Journal of Rehabilitation Theory and Practice, 2018
, 24(10)
: 1210
-1214
.
DOI: 10.3969/j.issn.1006-9771.2018.10.016
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