ArticleJournal of neuroengineering and rehabilitation2025
Post-stroke Stiff-Knee gait: are there different types or different severity levels?
Article in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- 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
- Determining the Validity of 2D Motion Capture for Estimating Lower Extremity Joint Quasi-Stiffness During Gait in Chronic Stroke Survivors.Restorative neurology and neuroscience · 2026Article
- A Longitudinal Study of Physical Function Factors Related to Lower Limb Circumduction During Gait in Acute Stroke Patients with Hemiparesis.Sensors (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
- Identification of stiff-knee gait in stroke survivors.BMC biomedical engineering · 2025Article
- Stiff Knee Gait After Stroke: The Potential Compensatory Role of Mid-Swing Rectus Femoris Activity.Case reports in neurological medicine · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Stiff-Knee gait (SKG) commonly occurs in individuals after stroke, loosely defined as reduced peak knee flexion angle during swing. The causes of SKG are multifaceted and debated. Further, clinical interventions have not been consistently effective, possibly resulting from multiple undiagnosed subtypes of SKG. Thus, our primary goal of this study is to explore the existence of potential subtypes associated with different levels of motor control complexity. We used retrospective kinematics, kinetics and muscle activity from 50 stroke survivors and 15 healthy, age-matched controls during treadmill walking. We used a time-series kernel k-means cluster analysis based on compensatory frontal plane kinematics associated with SKG to separate participants into three groups, Cluster A (hip hiking, lowest knee flexion, highest propulsion asymmetry, lowest gait speed), Cluster B (hip hiking and hip abduction, moderate knee flexion, middle gait speed) and Cluster C (highest knee flexion, highest gait speed). The highest proportion of individuals with SKG as diagnosed by a clinician were in Cluster A, but with a substantial proportion in Cluster B, indicating that these two clusters can be considered subtypes of SKG. Despite differences in kinematics and kinetics, we did not observe fundamental differences in underlying motor control between clusters as determined by non-negative matrix factorization of measured muscle activations. We conclude that the differences between clusters were most likely attributed to the severity of gait impairment, as reflected by slower gait speed and propulsion asymmetry, rather than being a different type of SKG.
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