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Spectral properties of electromyographic and mechanomyographic signals during dynamic concentric and eccentric contractions of the human biceps brachii muscle
Authors:Liping Qi  James M Wakeling  Martin Ferguson-Pell[Author vitae]
Institution:aASPIRE Centre for Disability Sciences, Institute of Orthopedics and Musculoskeletal Science, University College London, Brockley Hill, Stanmore, London HA7 4LP, UK;bDepartment of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6;cFaculty of Rehabilitation Medicine, University of Alberta, Edmonton, Alberta, Canada T6G 2G4
Abstract:The purpose of this study was to describe and examine the variations in recruitment patterns of motor units (MUs) in biceps brachii (BB) through a range of joint motion during dynamic eccentric and concentric contractions. Twelve healthy participants (6 females, 6 males, age = 30 ± 8.5 years) performed concentric and eccentric contractions with constant external loading at different levels. Surface electromyography (EMG) and mechanomyography (MMG) were recorded from BB. The EMGs and MMGs were decomposed into their intensities in time–frequency space using a wavelet technique. The EMG and MMG spectra were then compared using principal component analysis. Variations in total intensity, first principal component (PCI), and the angle θ formed by first component (PCI) and second component (PCII) loading scores were explained in terms of MU recruitment patterns and elbow angles. Elbow angle had a significant effect on dynamic concentric and eccentric contractions. The EMG total intensity was greater for concentric than for eccentric contractions in the present study. MMG total intensity, however, was lower during concentric than during eccentric contractions. In addition, there was no significant difference in θ between concentric and eccentric contractions for both EMG and MMG. Selective recruitment of fast MUs from BB muscle during eccentric muscle contractions was not found in the present study.
Keywords:Wavelet  Principal component analysis  Motor unit  Elbow angle  Mechanical demand  Moment arm  Recruitment  Firing rate
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