Background: Electromyography (EMG) technology has been shown to accurately measure individual muscle activation, force, and fatigue, and thus presents as an interesting aid to medical diagnosis. Surface EMG is a noninvasive alternative to traditional, intramuscular EMG. Our aim is to assess the feasibility of using surface EMG technology to measure activity of eight different shoulder muscles in healthy volunteers performing both daily living and range of motion exercises.

Methods: Nine subjects completed a series of three motions (abduction/adduction, internal/external rotation, and drinking). Eight surface EMG electrodes were used to measure muscle activity: anterior deltoid, middle deltoid, posterior deltoid, supraspinatus, infraspinatus, trapezius, teres major, and biceps brachii. Muscle activity was captured using wireless 3-dimensional Bluetooth sensors. ANOVA and principal component analysis (PCA) were used for statistical analysis to determine the pattern of shoulder muscle activation in response to upper arm’s activity of daily life.

Results: ANOVA analysis showed significantly different root mean square (RMS) values among muscles for all three exercises (p<0.001). Furthermore, for each individual muscle, there were statistically significant differences among the different motions (p<0.001). PCA displayed significant correlations between muscles for each motion and predominant muscle groupings. ANOVA analysis showed significantly different peak frequency values among muscles for all three exercises, in each phase of the exercise (p<0.001).

Conclusion: The results of this study indicate that kinematics of the muscles in the shoulder girdle and upper extremity can be accurately and effectively quantified using surface EMG. Specifically, force and fatigue can viably be measured and assessed in both superficial and deep muscles.