Objective To evaluate muscle activity in the arms of adult stroke survivors with limited or no arm movement during acute care. Design Prospective observational study. Setting Acute care regional stroke center. Participants We recruited adults (N=21) who had a stroke within the previous 5 days who were admitted to a level 1 trauma hospital and had a National Institutes of Health Stroke Scale score >1 for arm function at the time of recruitment. A total of 21 adults (13 men, 8 women) with an average age of 60±15 years were recruited an average of 3±1 days after their stroke. Eleven (7 men, 4 women; age, 56±11y) had no observable or palpable arm muscle activity (Manual Muscle Test [MMT]=0) and 10 (6 men, 4 women; age, 64±1y) had detectable activity (MMT>0). Interventions Dual mode sensors (electromyography and accelerometry) were placed on the anterior deltoid, biceps, triceps, wrist extensors, and wrist flexors of the impaired arm. Main Outcome Measures The number of muscle contractions, as well as average duration, amplitude, and co-contraction patterns were evaluated for each participant. Results Muscle contractions were observed in all 5 muscles for all participants using electromyography (EMG) recordings. Contractions were easily identified from 30 minutes of monitoring for participants with an MMT >0, but up to 3 hours of monitoring was required for participants with an MMT=0 to detect contractions in all 5 muscles during standard care. Only the wrist extensors demonstrated significantly larger amplitude contractions for participants with an MMT>0 than those with an MMT=0. Co-contraction was rare, involving less than 10% of contractions. Co-contraction of 2 muscles most commonly aligned with the flexor synergy pattern commonly observed after stroke. For participants with an MMT=0, the number of contractions and maximum amplitude were moderately correlated with MMT scores at follow-up. Conclusions Muscle activity was detected with surface EMG recordings during standard acute care, even for individuals with no observable activity by clinical examination. Wearable sensors may be useful for monitoring early muscle activity and movement after stroke.

No abstract

Objective: To determine whether electromyography (EMG) can be used in acute stroke care to identify muscle activity in patients with no observable activity during clinical examination. Design: Stroke survivors admitted to a level one trauma hospital with initial NIH Stroke Scale scores of two or higher for arm function were recruited within five days of stroke (average 3 +/- 1 days), including eleven stroke survivors (7 male/4 female, age 56 +/- 11) with no observable or palpable arm muscle activity (Manual Muscle Test, MMT=0) and ten stroke survivors (6 male/4 female, age 64 +/- 1) with observable muscle activity (MMT>0). We placed wireless EMG sensors on five major muscle groups (anterior deltoid, biceps, triceps, wrist extensors, and wrist flexors) of the impaired arm for 3-4 hours during standard care. Results: We were able to identify muscle contractions in all five muscles for all participants from EMG recordings. Contractions were easily identified from 30-minutes of monitoring for participants with MMT>0, but up to three hours of monitoring was required for participants with MMT=0 to detect contractions in all five muscles during standard care. Only the wrist extensors demonstrated significantly larger amplitude contractions for participants with MMT>0 than MMT=0. Co-contraction was rare, involving less than 10% of contractions. Co-contraction of two muscles most commonly aligned with the flexor synergy pattern commonly observed after stroke. For participants with MMT=0, number of contractions and maximum amplitude in acute care were moderately correlated with MMT scores at follow-up. Conclusion: Muscle activity can be detected with surface EMG recordings during standard care, even for stroke survivors with no observable activity by clinical exam.

Background: Assessments of human movement are clinically important. However, accurate measurements are often unavailable due to the need for expensive equipment or intensive processing. For orthotists and therapists, shank-to-vertical angle is one critical measure used to assess gait and guide prescriptions. Smartphone-based sensors may provide a widely available platform to expand access to this measurement. Objectives: Assess accuracy and repeatability of smartphone-based measurement of shank-to-vertical angle compared to marker-based 3D motion analysis. Study design: Repeated-measures. Methods: Four licensed clinicians (two physical therapists and two orthotists) measured shank-to-vertical angle during gait with a smartphone attached to the anterior or lateral shank surface of unimpaired adults. We compared the shank-to-vertical angle calculated from the smartphone’s inertial measurement unit to marker-based measurements. Each clinician completed three sessions/day on two days with each participant to assess repeatability. Results: Average absolute differences in shank-to-vertical angle measured with a smartphone versus marker-based 3D motion analysis during gait were 0.67 ± 0.25° and 4.89 ± 0.72°, with anterior or lateral smartphone positions, respectively. The inter- and intra-day repeatability of shank-to-vertical angle were within 2° for both smartphone positions. Conclusions: Smartphone sensors can be used to measure shank-to-vertical angle with high accuracy and repeatability during unimpaired gait, providing a widely available tool for quantitative gait assessments. Clinical relevance Smartphone sensors demonstrated high accuracy and repeatability for monitoring shank-to-vertical angle during gait. Measurement of shank-to-vertical angle from the front of the shank was more accurate than the side of the shank. Smartphones may expand access to quantitative assessments of gait.