ArticleNeurorehabilitation and neural repair2023
Multi-Site Identification and Generalization of Clusters of Walking Behaviors in Individuals With Chronic Stroke and Neurotypical Controls.
Article in Neurorehabilitation and neural repair, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 12 citations in OpenAlex.
- Neurorehabilitation in the 21st Century: New Science, New Strategies, New Expectations.Neurorehabilitation and neural repair · 2026Review
- Identification of Gait Patterns Associated with Paretic Propulsion and Velocity in Community-Dwelling Individuals with Stroke: A Multicenter Retrospective Study.Annals of biomedical engineering · 2026Article
- Neuromechanical gait signatures reveal holistic biomechanical responses to walking speed modulation in stroke survivors.Scientific reports · 2026Article
- Explainable machine learning for orthopedic decision-making: predicting functional outcomes of total hip replacement from gait biomechanics.Arthritis research & therapy · 2025Article
- Deep Temporal Clustering of Pathological Gait Recovery Patterns in Post-Stroke Patients Using Joint-Angle Trajectories: A Longitudinal Study.Bioengineering (Basel, Switzerland) · 2025Article
- Clinical assessments and gait characteristics by subtype classification using temporal and kinematic symmetry indices during gait in patients with chronic stroke.Journal of rehabilitation medicine · 2025Observational
- Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study.Bioengineering (Basel, Switzerland) · 2025Article
- Identification of Subtypes of Post-Stroke and Neurotypical Gait Behaviors Using Neural Network Analysis of Gait Cycle Kinematics.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025Article
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9 authors at 4 institutions in 1 country.
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Abstract
backgroundWalking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions.
objectivesWe used bilateral spatiotemporal and force data during walking to create a multi-site research sample to: (1) identify clusters of walking behaviors in people post-stroke and neurotypical controls and (2) determine the generalizability of these walking clusters across different research sites. We hypothesized that participants post-stroke will have different walking impairments resulting in different clusters of walking behaviors, which are also different from control participants.
methodsWe gathered data from 81 post-stroke participants across 4 research sites and collected data from 31 control participants. Using sparse
resultsWe identified 4 stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites.
conclusionsAlthough post-stroke walking patterns are heterogenous, these patterns can be systematically classified into distinct clusters based on spatiotemporal and force data. Future interventions could target the key features that characterize each cluster to increase the efficacy of interventions to improve mobility in people post-stroke.
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