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In clinical movement biomechanics, kinematic measurements are collected to characterise the motion of articulating joints and investigate how different factors influence movement patterns. Representative time-series signals are calculated to encapsulate (complex and multidimensional) kinematic datasets succinctly. Exacerbated by numerous difficulties to consistently define joint coordinate frames, the influence of local frame orientation and position on the characteristics of the resultant kinematic signals has been previously proven to be a major limitation.

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Objective: Lower limb malalignment can complicate symptoms and accelerate knee osteoarthritis (OA), necessitating consideration in study population selection. In this study, we develop and validate a deep learning model that classifies leg alignment as "normal" or "malaligned" from knee antero-posterior (AP)/postero-anterior (PA) radiographs alone, using an adjustable hip-knee-ankle (HKA) angle threshold.

Material And Methods: We utilized 8878 digital radiographs, including 6181 AP/PA full-leg x-rays (LLRs) and 2697 AP/PA knee x-rays (2292 with positioning frame, 405 without).

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Introduction: As illustrated by the "Walker Dip," there is growing concern regarding the lack of combat casualty care during peacetime. Surgical volume and case complexity are paramount for training and skill sustainment. We sought to quantify the recent orthopedic trauma surgical case load of all military orthopedic surgeons across the Military Health System (MHS).

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Purpose: The use of intramedullary fixation of AO type 31-A1 fractures is rising, despite evidence of non-superiority when compared with extramedullary fixation. The aim of this study was to evaluate mobility and living status for extramedullary fixation (EMF) versus intramedullary fixation (IMF) in Dutch hospitals during the initial hospital stay and until three-months after trauma.

Methods: Data on patient characteristics, mobility, living status, complications, reoperation, and mortality were extracted from the Dutch Hip Fracture Audit Indicator Taskforce.

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AI-assisted Digital Video Analysis Reveals Changes in Gait Among Three-Day Event Horses During Competition.

J Equine Vet Sci

January 2025

University of Florida Department of Animal Sciences, 2250 Shealy Dr., Gainesville, FL, United States, 32611; UF Genetics Institute, 2033 Mowry Rd., Gainesville, FL, United States, 32611. Electronic address:

The value and welfare of a performance horse are closely tie to locomotor behaviors, but we lack objective and quantitative measures for these characteristics, and qualitative approaches for assessing gait do not provide measures suitable for large-scale biomechanical research studies. Digital video analysis utilizing artificial intelligence-based strategies promise to meet the need for an economical, accurate, repeatable and objective technique for field quantification of equine locomotion. Here we describe pilot work using a consumer-level digital video camera to capture high-resolution and high-speed videos of horses moving at the trot during mandatory inspections for international-level eventing competitions.

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