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.

References

M. A. Islam, K. Sundaraj, R. B. Ahmad, and N. U. Ahamed, "Mechanomyogram for muscle function assessment: a review," PloS One, vol. 8, art no. e58902, 2013.

M. A. Islam, K. Sundaraj, R. B. Ahmad, N. U. Ahamed, and M. A. Ali, "Mechanomyography sensor development, related signal processing, and applications: a systematic review," IEEE Sensors Journal, vol. 13, pp. 2499-2516, 2013.

W. Guo, X. Sheng, H. Liu, and X. Zhu, "Mechanomyography assisted myoeletric sensing for upper-extremity prostheses: A hybrid approach," IEEE Sensors Journal, vol. 17, pp. 3100-3108, 2017.

M. Petitjean, B. Maton, and J. Cnockaert, "Evaluation of human dynamic contraction by phonomyography," Journal of Applied Physiology, vol. 73, pp. 2567-2573, 1992.

C. Orizio, M. Gobbo, B. Diemont, F. Esposito, and A. Veicsteinas, "The surface mechanomyogram as a tool to describe the influence of fatigue on biceps brachii motor unit activation strategy. Historical basis and novel evidence," European journal of applied physiology, vol. 90, pp. 326-336, 2003.

A. Posatskiy and T. Chau, "The effects of motion artifact on mechanomyography: A comparative study of microphones and accelerometers," Journal of Electromyography and Kinesiology, vol. 22, pp. 320-324, 2012.

D. Tosovic, C. Than, and J. Brown, "The effects of accumulated muscle fatigue on the mechanomyographic waveform: implications for injury prediction," European journal of applied physiology, vol. 116, pp. 1485-1494, 2016.

T. W. Beck, M. A. Dillon, J. M. DeFreitas, and M. S. Stock, "Crosscorrelation analysis of mechanomyographic signals detected in two axes," Physiological Measurement, vol. 30, p. 1465, 2009.

T. W. Beck, J. M. DeFreitas, and M. S. Stock, "An examination of cross-talk among surface mechanomyographic signals from the superficial quadriceps femoris muscles during isometric muscle actions," Human Movement Science, vol. 29, pp. 165-171, 2010.

M. A. Islam, K. Sundaraj, R. B. Ahmad, S. Sundaraj, N. U. Ahamed, and M. A. Ali, "Cross-talk in mechanomyographic signals from the forearm muscles during sub-maximal to maximal isometric grip force," PLoS One, vol. 9, art no. e96628, 2014.

M. A. Islam, K. Sundaraj, R. B. Ahmad, S. Sundaraj, N. U. Ahamed, and M. A. Ali, "Longitudinal, lateral and transverse axes of forearm muscles influence the crosstalk in the mechanomyographic signals during isometric wrist postures," PloS One, vol. 9, art no. e104280, 2014.

A. Islam, K. Sundaraj, R. B. Ahmad, S. Sundaraj, N. U. Ahamed, and M. Ali, "Analysis of crosstalk in the mechanomyographic signals generated by forearm muscles during different wrist postures," Muscle & Nerve, vol. 51, pp. 899-906, 2015.

M. M. Lowery, N. S. Stoykov, and T. A. Kuiken, "A simulation study to examine the use of cross-correlation as an estimate of surface EMG cross talk," Journal of Applied Physiology, vol. 94, pp. 1324-1334, 2003.

D. Farina, R. Merletti, B. Indino, M. Nazzaro, and M. Pozzo, "Surface EMG crosstalk between knee extensor muscles: experimental and model results," Muscle & Nerve, vol. 26, pp. 681-695, 2002.

D. Winter, A. Fuglevand, and S. Archer, "Crosstalk in surface electromyography: theoretical and practical estimates," Journal of Electromyography and Kinesiology, vol. 4, pp. 15-26, 1994.

J. P. Mogk and P. J. Keir, "Crosstalk in surface electromyography of the proximal forearm during gripping tasks," Journal of Electromyography and Kinesiology, vol. 13, pp. 63-71, 2003.

I. Talib, K. Sundaraj and C. K. Lam, " Choice of Mechanomyography Sensors for Diverse Types of Muscle Activities," Journal of Telecommunication, Electronic and Computer Engineering, (accepted for publication).

Downloads

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

Most read articles by the same author(s)