Development of a Standalone Application to Measure Crosstalk in MMG Signals from Forearm Muscles during Wrist Postures

Authors

  • I. Talib School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Pauh, Perlis, Malaysia
  • K. Sundaraj Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • C. K. Lam School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Pauh, Perlis, Malaysia
  • F. G. Nabi School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Pauh, Perlis, Malaysia

Keywords:

Application development, Crosstalk, Forearm muscles, Mechanomyography,

Abstract

Mechanomyography (MMG) signals can be used to study and analyze skeletal muscles. It retains its potential application in various fields including athletics, sports, medicine and prosthetic control. MMG signals do exhibit crosstalk from adjacent muscles. The measurement of crosstalk in MMG signals could be beneficial for the study of muscle mechanics. Hence, this research contributes to the development of a standalone application (APP) to measure crosstalk in MMG signals coming from human forearm muscles during various wrist postures. The application has been developed on National Instruments LabVIEW software version 14.0. Peak cross correlations have been used as a measure of crosstalk between neighboring muscles. The results produced by APP while measuring crosstalk in MMG signals are very close to literature. Hence the results for APP have been validated by previous studies. The APP can be used for both forms of MMG data either stored in the form of tdms files or real-time signals. MMG signals are acquired, displayed, processed and finally used for measurement of crosstalk. All the steps are done automatically in the APP. Hence APP cannot only save time to measure crosstalk through other tedious methods but it also provides a source of MMG data validation in a real-time environment.

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Published

2018-07-05

How to Cite

Talib, I., Sundaraj, K., Lam, C. K., & Nabi, F. G. (2018). Development of a Standalone Application to Measure Crosstalk in MMG Signals from Forearm Muscles during Wrist Postures. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(2-7), 103–106. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4434

Issue

Vol. 10 No. 2-7: Embracing The 4th Industrial Revolution: Innovation in Telecommunication, Electronic & Computer Engineering III

Section

Articles

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