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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2016 6th International Workshop on Computer Science and Engineering, WCSE 2016
PublisherInternational Workshop on Computer Science and Engineering (WCSE)
Pages636-639
Number of pages4
ISBN (Electronic)9789811100086
Publication statusPublished - 2016
Externally publishedYes
Event2016 6th International Workshop on Computer Science and Engineering, WCSE 2016 - Tokyo, Japan
Duration: 2016 Jun 172016 Jun 19

Other

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

Fingerprint

Electromyography
Membership functions
Fuzzy logic
Patient rehabilitation
MATLAB
Robotics
Control systems
Controllers

Keywords

  • Classification
  • Fuzzy logic
  • Pattern recognition
  • Walking phases

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

Cite this

Nazmi, N., Yamamoto, S., Rahman, M. A. A., Ahmad, S. A., Adiputra, D., Zamzuri, H., & Mazlan, S. A. (2016). Fuzzy logic for walking patterns based on surface electromyography signals with different membership functions. In 2016 6th International Workshop on Computer Science and Engineering, WCSE 2016 (pp. 636-639). International Workshop on Computer Science and Engineering (WCSE).

Fuzzy logic for walking patterns based on surface electromyography signals with different membership functions. / Nazmi, Nurhazimah; Yamamoto, Shinichirou; Rahman, Mohd Azizi Abdul; Ahmad, Siti Anom; Adiputra, Dimas; Zamzuri, Hairi; Mazlan, Saiful Amri.

2016 6th International Workshop on Computer Science and Engineering, WCSE 2016. International Workshop on Computer Science and Engineering (WCSE), 2016. p. 636-639.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nazmi, N, Yamamoto, S, Rahman, MAA, Ahmad, SA, Adiputra, D, Zamzuri, H & Mazlan, SA 2016, Fuzzy logic for walking patterns based on surface electromyography signals with different membership functions. in 2016 6th International Workshop on Computer Science and Engineering, WCSE 2016. International Workshop on Computer Science and Engineering (WCSE), pp. 636-639, 2016 6th International Workshop on Computer Science and Engineering, WCSE 2016, Tokyo, Japan, 16/6/17.
Nazmi N, Yamamoto S, Rahman MAA, Ahmad SA, Adiputra D, Zamzuri H et al. Fuzzy logic for walking patterns based on surface electromyography signals with different membership functions. In 2016 6th International Workshop on Computer Science and Engineering, WCSE 2016. International Workshop on Computer Science and Engineering (WCSE). 2016. p. 636-639
Nazmi, Nurhazimah ; Yamamoto, Shinichirou ; Rahman, Mohd Azizi Abdul ; Ahmad, Siti Anom ; Adiputra, Dimas ; Zamzuri, Hairi ; Mazlan, Saiful Amri. / Fuzzy logic for walking patterns based on surface electromyography signals with different membership functions. 2016 6th International Workshop on Computer Science and Engineering, WCSE 2016. International Workshop on Computer Science and Engineering (WCSE), 2016. pp. 636-639
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