Cross-Talk Level of Mechanomyography Signal on Compartmental Forearm Muscle
Mechanomyography (MMG) signal is a technique for recording and interpreting mechanical activity (vibration) in contracting muscle. In MMG, cross-talk refers to the contamination of the signal from the muscle of interest by a signal from another muscle or muscle group in close proximity. This study analyzed the cross-talk in MMG signals generated by the Palmaris Longus (PL), Flexor Carpi Ulnaris (FCU), Extensor Digitorum (ED) and Extensor Carpi Ulnaris (ECU) of forearm muscles during maximal voluntary contraction (MVC) force of hand exercise motions (grip strength supinated, grip strength pronated, finger flexion and pinch grip) by using different level of hand exercise balls (soft, medium and firm). Eight healthy subjects using dominant hand (mean ± SD: age = 23.25 ± 1.91 year) participated in this study to record MMG signals. During each muscle contraction, four VMG sensor (TSD250A) sensitive accelerometer (32.64 mm diameter) type were used with BIOPAC Vibromyography Systems to obtain MMG signals from flexor and extensor side of forearm muscles. Peak cross-correlation coefficients at zero time lags were used for quantification of the cross-talk. The results of cross-talk level between flexor and extensor side indicates that the magnitude range level of cross-talk for flexor side muscle groups were higher than the extensor side muscle groups for all hand exercise motions exerted.
KeywordsCross-talk Mechanomyography Forearm muscle
The authors would like to acknowledge the support from the Fundamental Research Grant Scheme (FRGS) under a grant number of FRGS/1/2015/TK04/UNIMAP/02/5 from the Ministry of Higher Education Malaysia.
- 1.Silva, J., Heim, W., Chau, T.:. MMG-based classification of muscle activity for prosthesis control. In: Proceedings of the IEEE Engineering Medicine Biology Society, vol. 2, pp. 968–971 (2004)Google Scholar
- 2.Murphy, C., Campbell, N., Caulfield, B., Ward, T., Deegan, C.: Micro electro mechanical systems based sensor for mechanomyography. In: Biosignal (2008)Google Scholar
- 4.lusola Ibitoye, M.O., Zah Hamzaid, N.A., Zuniga, J.M., Hasnan, N., Hairi, A.K., Wahab, A.: Mechanomyographic parameter extraction methods: an appraisal for clinical applications. Sensors (Basel) 14(12), 22940–22970 (2014)Google Scholar
- 6.Islam, A., Sundaraj, K., Ahmad, R.B., Sundaraj, S. Ahamed, N.U., Ali, A.: Cross-talk in mechanomyographic signals from the forearm muscles during sub-maximal to maximal isometric grip force, 9(5), 1–9 (2014)Google Scholar
- 7.Zeng, Y., Yang, Z., Cao, W. Xia, C.: Hand-motion patterns recognition based on mechanomyographic signal analysis. In: FBIE 2009 International Conference on Future Biomedical Information Engineering, pp. 21–24 (2009)Google Scholar