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http://dx.doi.org/10.5573/ieie.2015.52.3.181

Gait Phase Recognition based on EMG Signal for Stairs Ascending and Stairs Descending  

Lee, Mi-Ran (Department of Electronic Engineering, Inha University)
Ryu, Jae-Hwan (Department of Electronic Engineering, Inha University)
Kim, Sang-Ho (Department of Electronic Engineering, Inha University)
Kim, Deok-Hwan (Department of Electronic Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.52, no.3, 2015 , pp. 181-189 More about this Journal
Abstract
Powered prosthesis is used to assist walking of people with an amputated lower limb and/or weak leg strength. The accurate gait phase classification is indispensable in smooth movement control of the powered prosthesis. In previous gait phase classification using physical sensors, there is limitation that powered prosthesis should be simulated as same as the speed of training process. Therefore, we propose EMG signal based gait phase recognition method to classify stairs ascending and stairs descending into four steps without using physical sensors, respectively. RMS, VAR, MAV, SSC, ZC, WAMP features are extracted from EMG signal data and LDA(Linear Discriminant Analysis) classifier is used. In the training process, the AHRS sensor produces various ranges of walking steps according to the change of knee angles. The experimental results show that the average accuracies of the proposed method are about 85.6% in stairs ascending and 69.5% in stairs descending whereas those of preliminary studies are about 58.5% in stairs ascending and 35.3% in stairs descending. In addition, we can analyze the average recognition ratio of each gait step with respect to the individual muscle.
Keywords
Gait phase; Stair ascending; Stair descending; EMG signal; Classifier;
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Times Cited By KSCI : 1  (Citation Analysis)
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