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Muscle Activity After Stroke: Perspectives on Deploying Surface Electromyography in Acute Care

ABSTRACT: After a stroke, clinicians and patients struggle to determine if and when muscle activity and movement will return. Surface electromyography (EMG) provides a non-invasive window into the nervous system that can be used to monitor muscle activity, but is rarely used in acute care. In this perspective paper, we share our experiences deploying EMG in the clinic to monitor stroke survivors. Our experiences have demonstrated that deploying EMG in acute care is both feasible and useful. We found that current technology can be used to comfortably and non-obtrusively monitor muscle activity, even for patients with no detectable muscle activity by traditional clinical assessments. Monitoring with EMG may help clinicians quantify muscle activity, track recovery, and inform rehabilitation. With further research, we perceive opportunities in using EMG to inform prognosis, enable biofeedback training, and provide metrics necessary for supporting and justifying care. To leverage these opportunities, we have identified important technical challenges and clinical barriers that need to be addressed. Affordable wireless EMG system that can provide high-quality data with comfortable, secure interfaces that can be worn for extended periods are needed. Data from these systems need to be quickly and automatically processed to create round-ready results that can be easily interpreted and used by the clinical team. We believe these challenges can be addressed by integrating and improving current methods and technology. Deploying EMG in the clinic can open new pathways to understanding and improving muscle activity and recovery for individuals with neurologic injury in acute care and beyond.

SUBMITTER: Steele K

PROVIDER: S-EPMC7538789 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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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:Investigating muscle activity and coactivation with surface electromyography (sEMG) gives insight into pathological muscle function during activities like walking in people with neuromuscular impairments, such as children with cerebral palsy (CP). There is large variation in the amount of coactivation reported during walking in children with CP, possibly due to the inconsistent handling of sEMG and in calculating the coactivation index. The aim of this study was to evaluate how different approaches of handling sEMG may affect the interpretation of muscle activity and coactivation, by looking at both absolute and normalized sEMG. Twenty-three ambulatory children with CP and 11 typically developing (TD) children participated. We conducted a three-dimensional gait analysis (3DGA) with concurrent sEMG measurements of tibialis anterior, soleus, gastrocnemius medialis, rectus femoris, and hamstring medialis. They walked barefoot at a self-selected, comfortable speed back and forth a 7-m walkway. The gait cycle extracted from the 3DGA was divided into six phases, and for each phase, root mean square sEMG amplitude was calculated (sEMG-RMS-abs), and also normalized to peak amplitude of the linear envelope (50-ms running RMS window) during the gait cycle (sEMG-RMS-norm). The coactivation index was calculated using sEMG-RMS-abs and sEMG-RMS-norm values and by using two different indices. Differences between TD children's legs and the affected legs of children with CP were tested with a mixed model. The between-subject muscle activity variability was more evenly distributed using sEMG-RMS-norm; however, potential physiological variability was eliminated as a result of normalization. Differences between groups in one gait phase using sEMG-RMS-abs showed opposite differences in another phase using sEMG-RMS-norm for three of the five muscles investigated. The CP group showed an increased coactivation index in two out of three muscle pairs using sEMG-RMS-abs and in all three muscle pairs using sEMG-RMS-norm. These results were independent of index calculation method. Moreover, the increased coactivation indices could be explained by either reduced agonist activity or increased antagonist activity. Thus, differences in muscle activity and coactivation index between the groups change after normalization. However, because we do not know the truth, we cannot conclude whether to normalize and recommend incorporating both.

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Muscle Activity After Stroke: Perspectives on Deploying Surface Electromyography in Acute Care

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