Bilateral Muscle Synergy Patterns in ACL-Reconstructed Gait

Seventeen anterior cruciate ligament reconstructed patients provide data on muscle-synergy and electromyographic patterns during stable gait cycles. The dataset includes synergy modules, raw EMG data, and clinical covariates for integrated analysis. Hongxiang ZHANG authored this dataset, which was last updated in April 2026.

Use Cases

• Analyze inter-limb asymmetries by comparing 'Affected Side Synergy Module' muscle weight matrices W with 'Healthy Side Synergy Module' matrices.
• Model relationships between clinical covariates like 'ACL Return to Sport after Injury index score' and 'gait speed' from the 'Basic Information and Kinematic Data' file.
• Investigate neuromuscular control organization by examining 'time-to-peak activation', 'Activation Level of Synergy', and 'Proportion of Significant Activation Duration' metrics.
• Assess signal decomposition by analyzing VAF value changes across varying synergy numbers provided in the overall synergy parameter files.

Strengths

• Data from 17 subjects enables paired analysis of affected and healthy limbs.
• Includes eight specific lower-limb muscles (e.g., vastus lateralis, tibialis anterior) for detailed synergy comparison.
• Integrates raw EMG data, processed synergy parameters, and clinical covariates for multi-faceted analysis.

Limitations

• Small sample size of 17 patients limits statistical power and generalizability of findings.
• Dataset is tiny at 559.9 KB, indicating limited scope and depth of data.
• Lacks demographic or geographic details, introducing potential selection bias.

Provenance

Source

figshare, authored by Hongxiang ZHANG.

Collection Method

Electromyographic data collection from patients during gait cycles, processed into synergy modules and parameters.

Time Range

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Freshness

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Geography

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