期刊
JOURNAL OF SPORT REHABILITATION
卷 30, 期 5, 页码 731-736出版社
HUMAN KINETICS PUBL INC
DOI: 10.1123/jsr.2020-0307
关键词
sample entropy; neuromuscular function; ACLR; volitional activation; quadriceps weakness; electromyography; muscle inhibition
This study utilized sample entropy analysis to characterize neuromuscular deficits in quadriceps electromyographic activity after ACL reconstruction. The findings revealed a significant reduction in vastus medialis sample entropy after ACLR, indicating a correlation with poorer activation post-reconstruction.
Context: Traditionally, quadriceps activation failure after anterior cruciate ligament reconstruction (ACLR) is estimated using discrete isometric torque values, providing only a snapshot of neuromuscular function. Sample entropy (SampEn) is a mathematical technique that can measure neurologic complexity during the entirety of contraction, elucidating qualities of neuromuscular control not previously captured. Objective: To apply SampEn analyses to quadriceps electromyographic activity in order to more comprehensively characterize neuromuscular deficits after ACLR. Design: Cross-sectional. Setting: Laboratory. Participants: ACLR: n =18; controls: n = 24. Interventions: All participants underwent synchronized unilateral quadriceps isometric strength, activation, and electromyography testing during a superimposed electrical stimulus. Main Outcome Measures: Group differences in strength, activation, and SampEn were evaluated with t tests. Associations between SampEn and quadriceps function were evaluated with Pearson product-moment correlations and hierarchical linear regressions. Results: Vastus medialis SampEn was significantly reduced after ACLR compared with controls (P = .032). Vastus medialis and vastus lateralis SampEn predicted significant variance in activation after ACLR (r(2) = .444; P = .003). Conclusions: Loss of neurologic complexity correlates with worse activation after ACLR, particularly in the vastus medialis. Electromyographic SampEn is capable of detecting underlying patterns of variability that are associated with the loss of complexity between key neurophysiologic events after ACLR.
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