Reproducibility of MUAP properties in high-density surface EMG recordings of the upper trapezius and sternocleidomastoid muscle

Kallenberg, Laura A.C. and Preece, Stephen and Nester, Chris and Hermens, Hermie J. (2009) Reproducibility of MUAP properties in high-density surface EMG recordings of the upper trapezius and sternocleidomastoid muscle. Journal of Electromyography and Kinesiology, 19 (6). e536-e542. ISSN 1050-6411

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Abstract:	The use of array surface EMG recordings for detailed assessment of motor control and muscle properties is increasing. Motor unit action potentials (MUAPs) and their properties can be extracted from these recordings. The objective of this study was to determine the reproducibility of variables obtained from array surface EMG recordings of the shoulder and neck muscles during different functional tasks. Eight-channel linear arrays were placed on the upper trapezius (UT) and sternocleidomastoid (SCM) muscles of 12 healthy subjects. Subjects performed 3 tasks: shoulder abduction (90 degrees), ironing (repetitively touching two ends of a horizontal bar in front of the subject), and 90 degrees head turning. The protocol was performed twice while electrodes remained on and repeated a third time a week later. Three global and six MUAP-related variables were calculated. Intra-class correlation coefficients (ICC) were calculated to assess reliability and smallest detectable changes (SDC) were calculated to assess agreement. In general, the EMG variables showed high levels of reliability which suggests they may be effective for differentiating between-subjects. SDC was found to be considerably lower for the frequency-related (5-23%) than for the amplitude-related variables (15-78%), indicating that the frequency-related variables may be more suitable for investigating interventions which aim to modify motor control. There was no difference in reproducibility between global and MUAP-related variables, which justifies their complementary use.
Item Type:	Article
Copyright:	© 2009 Elsevier
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Biomedical Signals and Systems (BSS)
Link to this item:	http://purl.utwente.nl/publications/68619
Official URL:	http://dx.doi.org/10.1016/j.jelekin.2008.11.012
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