Fuzzy logic for walking patterns based on surface electromyography signals with different membership functions

Nurhazimah Nazmi, Yamamoto Shin-Ichiroh, Mohd Azizi Abdul Rahman, Siti Anom Ahmad, Dimas Adiputra, Hairi Zamzuri, Saiful Amri Mazlan

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

Classifying walking patterns is important in developing assistive robotic devices, especially for lower limb rehabilitation. Recently, Fuzzy Logic (FL) controllers have successfully been applied in grasping and control system for upper limb based on surface Electromyography (EMG) signals. Therefore, this paper evaluates the performance of FL with different membership functions in discriminating walking phases (e.g, stance and swing phases). The accuracy of two widely used membership functions (MF) like triangular and Gaussian is compared to identify their behavior for detecting the phases of walking. In this study, the MATLAB and Simulink toolboxes are used to examine the performance of each MF. Our findings show Gaussian MF gained better performance than the triangular MF with 90% of classification accuracy. Therefore, the Gaussian MF could be the best solution to classify the walking phases in this work.

本文言語English
ホスト出版物のタイトル2016 6th International Workshop on Computer Science and Engineering, WCSE 2016
出版社International Workshop on Computer Science and Engineering (WCSE)
ページ636-639
ページ数4
ISBN(電子版)9789811100086
出版ステータスPublished - 2016
外部発表はい
イベント2016 6th International Workshop on Computer Science and Engineering, WCSE 2016 - Tokyo, Japan
継続期間: 2016 6 172016 6 19

出版物シリーズ

名前2016 6th International Workshop on Computer Science and Engineering, WCSE 2016

Other

Other2016 6th International Workshop on Computer Science and Engineering, WCSE 2016
国/地域Japan
CityTokyo
Period16/6/1716/6/19

ASJC Scopus subject areas

  • 工学(全般)
  • コンピュータ サイエンス(全般)

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