Dataset Information

Muscle activation during maximum voluntary contraction and m-wave related in healthy but not in injured conditions: Implications when normalizing electromyography.

ABSTRACT: BACKGROUND:Electromyography signal amplitude is influenced by a variety of factors. Normalization strategies aimed at decreasing signal variability include using peak electromyography signal during a maximum voluntary contraction and peak-to-peak M-wave amplitude. However, whether these normalization methods are comparable has not been investigated in injured populations. This study investigated the relationship between peak signal during maximum voluntary contraction and M-wave amplitude in individuals with a unilateral Achilles tendon rupture. Secondarily, we observed whether the two normalizations strategies would yield similar results when evaluating between limb differences in muscle activity during a jump task. METHODS:Eleven individuals 1-3?years after a unilateral Achilles tendon rupture were included in this study. Surface electromyography was used on the medial and lateral gastrocnemii bilaterally. Peak maximum voluntary contraction, M-wave amplitude, and electromyography during a jumping task were collected. FINDINGS:A strong relationship was observed between peak maximum voluntary contraction and M-wave amplitude on the uninjured (r?=?0.71-0.88, P??0.05). The two normalization techniques did not produce different results when comparing the uninjured and ruptured sides. INTERPRETATION:The findings of this study suggest that M-wave normalization yields similar results as peak maximum voluntary contraction-normalized electromyography in uninjured conditions. M-wave normalization may be a useful strategy in an injured population where a maximal muscle contraction is unsafe or impaired.

SUBMITTER: Zellers JA

PROVIDER: S-EPMC6823141 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Muscle activation during maximum voluntary contraction and m-wave related in healthy but not in injured conditions: Implications when normalizing electromyography.

Zellers Jennifer A JA Parker Sheridan S Marmon Adam A Grävare Silbernagel Karin K

Clinical biomechanics (Bristol, Avon) 20190705

<h4>Background</h4>Electromyography signal amplitude is influenced by a variety of factors. Normalization strategies aimed at decreasing signal variability include using peak electromyography signal during a maximum voluntary contraction and peak-to-peak M-wave amplitude. However, whether these normalization methods are comparable has not been investigated in injured populations. This study investigated the relationship between peak signal during maximum voluntary contraction and M-wave amplitud ...[more]

PMID: 31326725

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Project description:Walking after stroke is often described as requiring excessive muscle co-contraction, yet, evidence that co-contraction is a ubiquitous motor control strategy for this population remains inconclusive. Co-contraction, the simultaneous activation of agonist and antagonist muscles, can be assessed with electromyography (EMG) but is often described qualitatively. Here, our goal is to determine if co-contraction is associated with gait impairments following stroke. Fifteen individuals with chronic stroke and nine healthy controls walked on an instrumented treadmill at self-selected speed. Surface EMGs were collected from the medial gastrocnemius (MG), soleus (SOL), and tibialis anterior (TA) of each leg. EMG envelope amplitudes were assessed in three ways: (1) no normalization, (2) normalization to the maximum value across the gait cycle, or (3) normalization to maximal M-wave. Three co-contraction indices were calculated across each agonist/antagonist muscle pair (MG/TA and SOL/TA) to assess the effect of using various metrics to quantify co-contraction. Two factor ANOVAs were used to compare effects of group and normalization for each metric. Co-contraction during the terminal stance (TSt) phase of gait is not different between healthy controls and the paretic leg of individuals post-stroke, regardless of the metric used to quantify co-contraction. Interestingly, co-contraction was similar between M-max and non-normalized EMG; however, normalization does not impact the ability to resolve group differences. While a modest correlation is revealed between the amount of TSt co-contraction and walking speed, the relationship is not sufficiently strong to motivate further exploration of a causal link between co-contraction and walking function after stroke. Co-contraction does not appear to be a common strategy employed by individuals after stroke. We recommend exploration of alternative EMG analysis approaches in an effort to learn more about the causal mechanisms of gait impairment following stroke.

Project description:Manipulative actions involving unstable interactions with the environment require controlling mechanical impedance through muscle co-contraction. While much research has focused on how the central nervous system (CNS) selects the muscle patterns underlying a desired movement or end-point force, the coordination strategies used to achieve a desired end-point impedance have received considerably less attention. We recorded isometric forces at the hand and electromyographic (EMG) signals in subjects performing a reaching task with an external disturbance. In a virtual environment, subjects displaced a cursor by applying isometric forces and were instructed to reach targets in 20 spatial locations. The motion of the cursor was then perturbed by disturbances whose effects could be attenuated by increasing co-contraction. All subjects could voluntarily modulate co-contraction when disturbances of different magnitudes were applied. For most muscles, activation was modulated by target direction according to a cosine tuning function with an offset and an amplitude increasing with disturbance magnitude. Co-contraction was characterized by projecting the muscle activation vector onto the null space of the EMG-to-force mapping. Even in the baseline the magnitude of the null space projection was larger than the minimum magnitude required for non-negative muscle activations. Moreover, the increase in co-contraction was not obtained by scaling the baseline null space projection, scaling the difference between the null space projections in any block and the projection of the non-negative minimum-norm muscle vector, or scaling the difference between the null space projections in the perturbed blocks and the baseline null space projection. However, the null space projections in the perturbed blocks were obtained by linear combination of the baseline null space projection and the muscle activation used to increase co-contraction without generating any force. The failure of scaling rules in explaining voluntary modulation of arm co-contraction suggests that muscle pattern generation may be constrained by muscle synergies.

Dataset Information

Muscle activation during maximum voluntary contraction and m-wave related in healthy but not in injured conditions: Implications when normalizing electromyography.

Publications

Muscle activation during maximum voluntary contraction and m-wave related in healthy but not in injured conditions: Implications when normalizing electromyography.

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