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Gait pattern classification in individuals with lower-limb amputation could help in developing personalized prosthetic prescriptions and tailored gait rehabilitation. However, systematic classifications of gait patterns in this population have been scarcely explored. This study aimed to determine whether the gait patterns in individuals with unilateral transfemoral amputation (UTFA) can be clustered into homogeneous subgroups using spatiotemporal parameters across a range of walking speeds. We examined spatiotemporal gait parameters, including step length and cadence, in 25 individuals with UTFA (functional level K3 or K4, all non-vascular amputations) while they walked on a split-belt instrumented treadmill at eight speeds. Hierarchical cluster analysis (HCA) was used to identify clusters with homogeneous gait patterns based on the relationships between step length and cadence. Furthermore, after cluster formation, post-hoc analyses were performed to compare the spatiotemporal parameters and demographic data among the clusters. HCA identified three homogeneous gait pattern clusters, suggesting that individuals with UTFA have several gait patterns. Further, we found significant differences in the participants' body height, sex ratio, and their prosthetic knee component among the clusters. Therefore, gait rehabilitation should be individualized based on body size and prosthetic prescription.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778493 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0279593 | PLOS |
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Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, USA.
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August 2025
Tecnologico de Monterrey, School of Medicine and Health Sciences, 64710 Monterrey, Nuevo León, Mexico.
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Objective: This study examined and contrasted both motor and non-motor symptoms in patients diagnosed with Parkinson's disease, stratified by the presence or absence of diabetes.
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Departments of Biochemistry & Medical Genetics, University of Manitoba, Winnipeg, R3T 2N2, Canada.
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Human Movement Laboratory, School of Health Sciences, Western Sydney University, Campbelltown, NSW, Australia; Translational Health Research Institute, School of Health Sciences, Western Sydney University, Campbelltown, NSW, Australia.
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September 2025
Cyber-physical Health and Assistive Robotics Technologies Research Group, University of Nottingham, United Kingdom; School of Computer Science, University of Nottingham, Nottingham, United Kingdom.
Neck pain is among the most prevalent musculoskeletal conditions worldwide. The underlying cause mostly remains unidentified, classified as non-specific neck pain. Pain can alter movement patterns and physiological responses, suggesting that certain biomechanical and physiological changes may serve as objective biomarkers for non-specific neck pain.
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