Inhomogeneities in muscle activation reveal motor unit recruitment.
This paper presents a novel method to quantify spatial changes in muscle activation pattern by multi-channel surface electromyography (MCSEMG) in order to investigate motor unit recruitment variation. The method is based on non-uniform distributions of motor units that cause spatial inhomogeneous muscle activation. To evaluate the method, 15 subjects performed three isometric elbow flexion contractions consisting of slow sinusoidal changes in force ranging from 0% to 80% of the maximal voluntary contraction. MCSEMG electrodes were placed in a 10 x 13 grid over the biceps brachii muscle. From all channels, root mean square (RMS) values of bipolar leadings were computed over 0.5 s epochs over the whole recording. Thereafter, correlation coefficients were calculated between the RMS values at one epoch, with the RMS values at another epoch. Results showed consistent spatial changes in the distribution of RMS at different contraction levels up to 80% of maximal voluntary contraction and when comparing increasing and decreasing contractions at the same force level. These findings are reproducible within and between subjects, and in agreement with physiological phenomena and therefore indicate that the spatial inhomogeneities of motor unit properties in the biceps brachii muscle can be used to study changes in motor unit recruitment.
Holtermann
Andreas
A
Human Movement Sciences Program, Faculty of Social Sciences and Technology Management, Norwegian University of Science and Technology, N-7491 Trondheim, Norway.
Roeleveld
Karin
K
Karlsson
J Stefan
JS
D000328:Adult; D001132:Arm / Q000502:physiology; D001696:Biomechanical Phenomena / Q000295:instrumentation; D004576:Electromyography; D005246:Feedback; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology*; D008297:Male; D009046:Motor Neurons / Q000502:physiology*; D018482:Muscle, Skeletal / Q000294:innervation* / Q000502:physiology; D011999:Recruitment, Neurophysiological / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013314:Stress, Mechanical