Post-Stroke Gait Kinematic and sEMG Waveforms for 43 Patients

Rocco Salvatore Calabrò published a secondary analysis of a public multimodal gait dataset on figshare in 2026. The dataset comprises waveform data from 138 able-bodied adults and 50 adults with stroke, focusing on 11 waveform domains including sagittal kinematics and surface electromyography. The retained analysis organized 43 stroke patients into three distinct gait states based on fused kinematic and sEMG data.

Use Cases

• Clustering post-stroke gait patterns based on fused kinematic and sEMG waveform data.
• Identifying key biomechanical contributors to gait states based on domain contributions like ankle angle and vastus lateralis sEMG.
• Designing side-aware state representations for adaptive robotic assistance controllers.
• Testing the stability of gait-state clustering under different data scaling and component reduction scenarios.

Strengths

• Derived from a public multimodal gait dataset with 188 total participants (138 able-bodied, 50 with stroke).
• Analysis retained 90% cumulative variance using functional principal component analysis, capped at specific components.
• Results show high resampling stability for a two-state solution (bootstrap adjusted Rand index 0.876).

Limitations

• Dataset is very small at 29.8 KB, indicating limited raw data scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• The analysis is exploratory and representational, not validated for clinical or real-time use.

Provenance

Source

Rocco Salvatore Calabrò

Collection Method

Secondary analysis of a public multimodal gait dataset.

Freshness

Last updated 2026-05-25 06:05:41