Publications by authors named "Martin Seyres"

Hypothesis And Background: Shoulder instability (SI) is a complex impairment, and identifying biomarkers that differentiate subgroups is challenging. Children and adolescents with SI (irrespective of etiology) have differences in their movement and muscle activity profiles compared to age- and sex-matched controls (2-tailed). There are limited fundamental movement and muscle activity data for identifying different mechanisms for SI in children and adolescents that can inform subgrouping and treatment allocation.

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One of the recommendations for individuals with knee osteoarthritis (OA) is the use of specific footwear, such as sturdy or cushioned shoes. However, the long-term use effects of using cushioned shoes on the pain and spatiotemporal gait parameters in individuals with knee OA are yet to be reported. We therefore aimed to compare the efficacy of cushioned sport footwear versus sham shoes on motor functions, pain and gait characteristics of individuals with knee OA who used the shoes for 3 months.

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Virtual reality enables the manipulation of a patient's perception, providing additional motivation to real-time biofeedback exercises. We aimed to test the effect of manipulated virtual kinematic intervention on measures of active and passive range of motion (ROM), pain, and disability level in individuals with traumatic stiff shoulder. In a double-blinded study, patients with stiff shoulder following proximal humerus fracture and non-operative treatment were randomly divided into a non-manipulated feedback group (NM-group; = 6) and a manipulated feedback group (M-group; = 7).

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Background: Single camera markerless motion capture has the potential to facilitate at home movement assessment due to the ease of setup, portability, and affordable cost of the technology. However, it is not clear what the current healthcare applications of single camera markerless motion capture are and what information is being collected that may be used to inform clinical decision making. This review aims to map the available literature to highlight potential use cases and identify the limitations of the technology for clinicians and researchers interested in the collection of movement data.

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Article Synopsis
  • Individuals with post-polio syndrome (PPS) experience falls and related damage, prompting research into fall predictors based on their gait.
  • Analysis of gait data from 50 PPS patients revealed correlations between their walking patterns, fall frequency, and fear of falling, with specific gait parameters significantly explaining fall risk.
  • The study concludes that measuring gait variability could be a useful approach in developing tailored fall prevention strategies for PPS patients.
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