Post-Stroke Gait Kinematic and sEMG Waveform Data for 43 Patients

138 able-bodied adults and 50 adults with stroke contributed to this public multimodal gait dataset. The analysis retained a strict complete-case stroke cohort of 43 individuals, organized into three gait states based on 11 waveform domains including sagittal kinematics and surface electromyography. Rocco Salvatore Calabrò published this secondary analysis on figshare in May 2026.

Use Cases

• Developing side-aware gait-state representations for adaptive lower-limb neurorobotics based on paretic and non-paretic waveform views.
• Clustering post-stroke gait patterns based on fused kinematic and sEMG data to identify distinct patient states.
• Analyzing the contribution of specific domains like ankle angle and vastus lateralis sEMG to gait-state differentiation.
• Testing the stability of gait-state assignments under different data scaling or dimensionality reduction scenarios.

Strengths

• Dataset includes data from 138 able-bodied adults and 50 adults with stroke, providing a control and patient cohort.
• Analysis is based on 11 waveform domains, each represented by 1,001 time-normalized points, offering high temporal resolution.
• Results are derived from a strict complete-case stroke cohort of 43 individuals, ensuring data consistency for the primary analysis.
• The retained three-state solution was chosen for its interpretability and preservation of explicit multimodal side-aware structure.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Secondary analysis of a public multimodal gait dataset.

Collection Method

Functional principal component analysis and clustering (Ward hierarchical and K-means) performed on waveform data.

Freshness

Last updated 2026-05-25 06:05:42; freshness should be verified.