Publications by authors named "A S Faĭn"

Article Synopsis
  • * They developed a machine learning model capable of predicting MSKI risk based on a single jump test and assessed the influence of sex on lower-limb injury risk.
  • * The collaboration highlights the importance of having well-rounded teams with independent funding to tackle complex problems and evaluate wearable technology for military training adaptations.
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Objective: People with Marfan syndrome (MFS) have clinical symptoms of hip pain, but to date, there is limited knowledge about hip-related structural abnormalities in these patients. Therefore, the purpose of this cross-sectional study was to assess hip-related structural abnormalities and patient-reported outcomes (PRO) in a cohort of patients with MFS compared to healthy controls.

Methods: Nineteen individuals with MFS (17 females, 39.

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Background: Despite deleterious biomechanics associated with injury, particularly as it pertains to load carriage, there is limited research on the association between physical demands and variables captured with wearable sensors. While inertial measurement units (IMUs) can be used as surrogate measures of ground reaction force (GRF) variables, it is unclear if these data are sensitive to military-specific task demands.

Research Question: Can wearable sensors characterise physical load and demands placed on individuals in different load, speed and grade conditions?

Methods: Data were collected on 20 individuals who were self-reportedly free from current injury, recreationally active, and capable of donning 23 kg in the form of a weighted vest.

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Objective: Outside of pregnancy, proactive coping has been associated with both mental and physical well-being and with improved quality of life in chronic disease, but its effects in pregnancy are understudied. Our objective was to evaluate whether early pregnancy proactive coping was associated with adverse perinatal outcomes.

Study Design: This was a planned secondary analysis of nulliparous pregnant people recruited from a tertiary care center.

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The ability to estimate lower-extremity mechanics in real-world scenarios may untether biomechanics research from a laboratory environment. This is particularly important for military populations where outdoor ruck marches over variable terrain and the addition of external load are cited as leading causes of musculoskeletal injury As such, this study aimed to examine (1) the validity of a minimal IMU sensor system for quantifying lower-extremity kinematics during treadmill walking and running compared with optical motion capture (OMC) and (2) the sensitivity of this IMU system to kinematic changes induced by load, grade, or a combination of the two. The IMU system was able to estimate hip and knee range of motion (ROM) with moderate accuracy during walking but not running.

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