ArticleScientific data2026
A dataset for bilateral lower limb muscle synergy patterns in unilateral anterior cruciate ligament reconstructed patients.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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4 authors.
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Abstract
This data descriptor presents a bilateral lower limb muscle synergy dataset from 17 unilateral anterior cruciate ligament reconstruction athletes (9 men, 8 women; training experience > 4 years; national level one or two athletes) at 6 months post-surgery during stable gait testing. A cross-sectional study design was adopted. Surface electromyography signals from eight key muscles of both lower limbs were processed using non-negative matrix factorization to extract muscle synergy structures. The dataset comprehensively documents: (1) basic participant information; (2) K-STARTS functional test results; (3) gait mechanics parameters (gait speed, center of mass mediolateral displacement velocity, and center of pressure mediolateral displacement velocity); and (4) core muscle synergy indicators, including synergy weight matrix (W), activation coefficient matrix (H), number of synergies, muscle contribution weights, time to peak activation, activation level of synergy, proportion of significant activation duration, overall synergy activation level, and co-activation duration. This dataset provides systematic, reproducible, and standardized data support for analyzing bilateral lower limb neuromuscular control differences following anterior cruciate ligament reconstruction, and can be directly applied to symmetry analysis, functional assessment, and individualized rehabilitation research.
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