Measuring the accuracies of motor unit firing times and action potential waveforms derived from surface electromyographic decomposition

Herda, Trent J.; Parra, Mandy E.; Miller, Jonathan D.; Sterczala, Adam J.; Kelly, Melani R.

doi:10.1016/j.jelekin.2020.102421

Cited by 21 publications

(10 citation statements)

References 33 publications

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“…However, numerous studies have calculated a high rate of agreement between the surface EMG signal decomposition method utilized in this study 66,67 and intramuscular MU firing times as done with other decomposition methods 68,69 . In addition, we utilized a three‐step, user‐driven validation process that allowed us to quantitatively ensure 31,33 our AP trains were reflecting MU activity 32 …”

Section: Discussionmentioning

confidence: 98%

“…Additionally, a secondary STA procedure was performed to validate the firing times and action potential waveforms created via the PD III algorithm. The derived firing times from the PD III algorithm were used to STA the four raw EMG signals 17,31,32 . MUs were selected for analysis if they demonstrated high correlations ( r ≥ 0.7) across the four channels between the PD III algorithm and the STA derived action potential waveforms and a coefficient of variation for the STA derived peak‐to‐peak amplitudes <0.3 across time 17,31 .…”

Section: Methodsmentioning

confidence: 99%

“…The derived firing times from the PD III algorithm were used to STA the four raw EMG signals. 17,31,32 MUs were selected for analysis if they demonstrated high correlations (r ≥ 0.7) across the four channels between the PD III algorithm and the STA derived action potential waveforms and a coefficient of variation for the STA derived peak-to-peak amplitudes <0.3 across time. 17,31 Supposedly valid MU action potential waveforms may be created from trigger events that do not correspond with MU discharge times.…”

Section: Emg Decompositionmentioning

confidence: 99%

“…Surface EMG signal decomposition was utilized to allow for larger MU yields 6,30,31 and the comparison of MU firing rate patterns, and secondary spike trigger averaging procedures were performed to confirm the reliability of our MU data. [32][33][34] Examining MU properties in relation to their RTs may account for the variability when comparing recruitment and firing rate patterns on a subject-to-subject basis. 14 In addition, correlations were calculated to examine the relationship of type I %MHC isoform content of the VL and MU properties for the moderate-and highintensity contraction.…”

Section: Introductionmentioning

confidence: 99%

“…Although we have previously reported the influence of %MHC isoform content on MU firing rate patterns following short‐term training 17 and young adults with various training backgrounds, 23 comparisons between males and females at differing contraction intensities have not been investigated. Surface EMG signal decomposition was utilized to allow for larger MU yields 6,30,31 and the comparison of MU firing rate patterns, and secondary spike trigger averaging procedures were performed to confirm the reliability of our MU data 32–34 . Examining MU properties in relation to their RTs may account for the variability when comparing recruitment and firing rate patterns on a subject‐to‐subject basis 14 .…”

Section: Introductionmentioning

confidence: 99%

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Sex‐related differences in motor unit behavior are influenced by myosin heavy chain during high‐ but not moderate‐intensity contractions

et al. 2023

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AimsMotor unit recruitment and firing rate patterns of the vastus lateralis (VL) have not been compared between sexes during moderate‐ and high‐intensity contraction intensities. Additionally, the influence of fiber composition on potential sex‐related differences remains unquantified.MethodsEleven males and 11 females performed 40% and 70% maximal voluntary contractions (MVCs). Surface electromyographic (EMG) signals recorded from the VL were decomposed. Recruitment thresholds (RTs), MU action potential amplitudes (MUAPAMP), initial firing rates (IFRs), mean firing rates (MFRs), and normalized EMG amplitude (N‐EMGRMS) at steady torque were analyzed. Y‐intercepts and slopes were calculated for MUAPAMP, IFR, and MFR versus RT relationships. Type I myosin heavy chain isoform (MHC) was determined with muscle biopsies.ResultsThere were no sex‐related differences in MU characteristics at 40% MVC. At 70% MVC, males exhibited greater slopes (p = 0.002) for the MUAPAMP, whereas females displayed greater slopes (p = 0.001–0.007) for the IFR and MFR versus RT relationships. N‐EMGRMS at 70% MVC was greater for females (p < 0.001). Type I %MHC was greater for females (p = 0.006), and was correlated (p = 0.018–0.031) with the slopes for the MUAPAMP, IFR, and MFR versus RT relationships at 70% MVC (r = −0.599–0.585).ConclusionBoth sexes exhibited an inverse relationship between MU firing rates and recruitment thresholds. However, the sex‐related differences in MU recruitment and firing rate patterns and N‐EMGRMS at 70% MVC were likely due to greater type I% MHC and smaller twitch forces of the higher threshold MUs for the females. Evidence is provided that muscle fiber composition may explain divergent MU behavior between sexes.

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