Advances in surface electromyographic (sEMG) signal decomposition algorithms have allowed for a richer understanding of motor unit behavior during voluntary contractions. However, this technology has primarily been applied to conditions in which muscle length remains constant (isometric contractions) and force is low. It is unclear if previous findings obtained during isometric contractions are applicable to dynamic, real-world movements, particularly when examined across days. We sought to determine the reliability of firing rates from the biceps brachii during the concentric (lifting) and eccentric (lowering) phases of one-repetition maximum (1RM) curls using a novel sEMG signal decomposition algorithm. Fourteen resistance trained adults (six males, eight females) participated in three laboratory visits, during which 1RM strength for the barbell curl exercise was assessed while sEMG signals were recorded from the biceps brachii. The motor unit mean firing rate (pulses per second [pps]) versus action potential amplitude (millivolts [mV]) relationship was quantified, and linear regression was used to determine the slopes and y-intercepts. The slopes during both the concentric and eccentric phases demonstrated intraclass correlation coefficients (model 3,1) ≥ 0.861, standard errors of measurement ~26.5%, and minimal differences needed to be considered real ~34.5 (pps/mV). The y-intercepts displayed intraclass correlation coefficients ≥ 0.375, standard errors of measurement ≥ 10.0%, and minimal differences needed to be considered real ≥ 7.8 (pps). For both the slopes and y-intercepts, there were no significant differences across days (p > .05) and small effect sizes were observed (ƞp2 < 0.01). In summary, motor unit data from the biceps brachii obtained during high-force, dynamic contractions across multiple days appears to demonstrate sufficient reliability to track neuromuscular adaptations.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses-2558 |
| Date | 01 January 2023 |
| Creators | George, Daniel P |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Honors Undergraduate Theses |
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