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Comparison of EMG power during sleep from the submental and frontalis muscles.

ABSTRACT: ObjectiveSubmentalis electromyography (sEMG) and frontalis electromyography (fEMG) muscle activities have been used to assist in the staging of sleep and detection of disruptions in sleep. This study was designed to assess the concordance between sEMG and fEMG power, by and across sleep stages.MethodsForty-three records with simultaneous acquisition of differential signals from the submental and frontalis muscles were evaluated. Sleep stages were assigned using the poly-somnography signals based on majority agreement of five technicians. The sEMG and fEMG signals were identically filtered and aligned prior to cross-correlation analysis.ResultsA strong concordance between sEMG and fEMG power was observed, with 95% of the records exhibiting at least moderate agreement. During rapid eye movement (REM) sleep, sEMG power was significantly less than fEMG power, but exhibited four times greater across-subject variability. fEMG power during wake and non-REM (NREM) sleep was greater than sEMG power, but with 50% less variability. Differences in wake and N1 mean power and between the other sleep stages were more distinct in the fEMG recordings. Relative changes in sEMG and fEMG power across wake, NREM, and REM stages were essentially identical with median by-subject cross correlations of 0.98 and interquartile ranges of 0.97 and 0.99, respectively.ConclusionThe fEMG and sEMG power values were similar during wakefulness and sleep; however, the frontalis exhibits substantially less between-subject variability. This study established face validity for the use of fEMG in the detection of wake and stages of sleep, and for future applications toward assessment of quantitative REM sleep muscle activity in REM sleep behavior disorder.

SUBMITTER: Levendowski DJ

PROVIDER: S-EPMC6287659 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Project description:IntroductionInverse dynamics joint kinetics are often used to infer contributions from underlying groups of muscle-tendon units (MTUs). However, such interpretations are confounded by multiarticular (multi-joint) musculature, which can cause inverse dynamics to over- or under-estimate net MTU power. Misestimation of MTU power could lead to incorrect scientific conclusions, or to empirical estimates that misguide musculoskeletal simulations, assistive device designs, or clinical interventions. The objective of this study was to investigate the degree to which ankle joint power overestimates net plantarflexor MTU power during the Push-off phase of walking, due to the behavior of the flexor digitorum and hallucis longus (FDHL)-multiarticular MTUs crossing the ankle and metatarsophalangeal (toe) joints.MethodsWe performed a gait analysis study on six healthy participants, recording ground reaction forces, kinematics, and electromyography (EMG). Empirical data were input into an EMG-driven musculoskeletal model to estimate ankle power. This model enabled us to parse contributions from mono- and multi-articular MTUs, and required only one scaling and one time delay factor for each subject and speed, which were solved for based on empirical data. Net plantarflexing MTU power was computed by the model and quantitatively compared to inverse dynamics ankle power.ResultsThe EMG-driven model was able to reproduce inverse dynamics ankle power across a range of gait speeds (R2 ≥ 0.97), while also providing MTU-specific power estimates. We found that FDHL dynamics caused ankle power to slightly overestimate net plantarflexor MTU power, but only by ~2-7%.ConclusionsDuring Push-off, FDHL MTU dynamics do not substantially confound the inference of net plantarflexor MTU power from inverse dynamics ankle power. However, other methodological limitations may cause inverse dynamics to overestimate net MTU power; for instance, due to rigid-body foot assumptions. Moving forward, the EMG-driven modeling approach presented could be applied to understand other tasks or larger multiarticular MTUs.

Project description:Recent evidence suggests the minimization of muscular effort rather than of the size of bodily sway may be the primary, nervous system goal when regulating the human, standing posture. Different programs have been proposed for balance training; none however has been focused on the activation of postural muscles during standing. In this study we investigated the possibility of minimizing the activation of the calf muscles during standing through biofeedback. By providing subjects with an audio signal that varied in amplitude and frequency with the amplitude of surface electromyograms (EMG) recorded from different regions of the gastrocnemius and soleus muscles, we expected them to be able to minimize the level of muscle activation during standing without increasing the excursion of the center of pressure (CoP). CoP data and surface EMG from gastrocnemii, soleus and tibialis anterior muscles were obtained from 10 healthy participants while standing at ease and while standing with EMG biofeedback. Four sensitivities were used to test subjects' responsiveness to the EMG biofeedback. Compared with standing at ease, the two most sensitive feedback conditions induced a decrease in plantar flexor activity (~15%; P < 0.05) and an increase in tibialis anterior EMG (~10%; P < 0.05). Furthermore, CoP mean position significantly shifted backward (~30 mm). In contrast, the use of less sensitive EMG biofeedback resulted in a significant decrease in EMG activity of ankle plantar flexors with a marginal increase in TA activity compared with standing at ease. These changes were not accompanied by greater CoP displacements or significant changes in mean CoP position. Key results revealed subjects were able to keep standing stability while reducing the activity of gastrocnemius and soleus without loading their tibialis anterior muscle when standing with EMG biofeedback. These results may therefore posit the basis for the development of training protocols aimed at assisting subjects in more efficiently controlling leg muscle activity during standing.

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Comparison of EMG power during sleep from the submental and frontalis muscles.

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