2041 Quantitative Assessment of Post Stroke Upper Extremity Weakness Classified by Degree of Clinical Weakness on the Medical Research Council Muscle Grading Scale

• DOI: 10.1227/neu.0000000000003360_2041
• Publication Date: 2025-03-14T13:41:40Z
• Authors: Serajh Esmail; Ronald Sahyouni; Ryan Sindewald; Michael G. Brandel; David Rafael Sant...; Nikhil Krishna Mu...; Alexander A. Khal...

INTRODUCTION: Post-stroke motor deficits pose a substantial public health challenge, impacting approximately 40 million individuals globally and leading to significant long-term disability. Rehabilitation efforts, both conventional and novel, achieve less than 60% recovery of upper extremity motor function. To date, no study has assessed electromyographic (EMG) recovery in patients with motor deficits due to stroke.

METHODS: With IRB approval, patients (> 18 years) admitted for ischemic or hemorrhagic subcortical stroke with isolated motor deficits and no cognitive impairments, were recruited. EMG activity during biceps flexion was recorded on both affected and unaffected arms using the ANR M40 Muscle Sense Probe placed on the distal third of the humerus of the biceps brachii muscle. Statistical analyses were conducted to evaluate differences in muscle response and their correlation with the Medical Research Council (MRC) Muscle Grading Scale.

RESULTS: EMG analysis of a patient with a left M2 stroke, resulting in global aphasia and right upper extremity weakness, revealed significant correlations between EMG amplitudes and MRC grades. The unaffected left arm exhibited higher EMG amplitudes and MRC scores compared to the affected right arm. Notably, left vs. right arm without weight showed a t-statistic of 6.826 (p=0.0024), and with weight, a t-statistic of 5.657 (p=0.0048).

CONCLUSIONS: This sentinel analysis demonstrates significant correlations that underscore the clinical relevance of EMG activity in assessing muscle strength post-stroke. The findings reveal that the unaffected arm exhibits higher EMG amplitudes and MRC scores compared to the affected arm. These results support our ongoing efforts to expand EMG waveform datasets to enhance understanding of stroke-related muscular impairment.