Publications by authors named "A Falisse"
Article Synopsis
- Hamstring injuries are frequent in field sports, especially during accelerative running, yet previous studies mainly examined constant-speed running mechanics.
- Researchers analyzed hamstring lengths and velocities in 10 participants across both accelerative and constant-speed running trials, revealing that accelerative running leads to longer hamstring lengths and higher lengthening velocities, particularly at speeds below 75% of maximum.
- The findings suggest that coaches and sports medicine professionals should focus on the specific demands of accelerative running, as it creates conditions that could increase the risk of hamstring injuries.
Article Synopsis
- Human pose estimation models often struggle with accuracy when detecting joint kinematics due to sparse keypoint detection, but OpenCap aims to improve this with a new deep learning model called the marker enhancer.
- A larger and more diverse training dataset, compiled from motion capture data involving 1,176 subjects, has been created to enhance the model's performance on various movements, even those not included in the training set.
- The updated marker enhancer has shown significant improvements in kinematic accuracy for benchmark and unseen movements compared to previous versions, making OpenCap a more reliable tool for researchers needing accurate movement measurements.
Background: Hamstring strain injuries are associated with significant time away from sport and high reinjury rates. Recent evidence suggests that hamstring injuries often occur during accelerative running, but investigations of hamstring mechanics have primarily examined constant speed running on a treadmill. To help fill this gap in knowledge, this study compares hamstring lengths and lengthening velocities between accelerative running and constant speed overground running.
View Article and Find Full Text PDFMeasures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.
View Article and Find Full Text PDFPhysical function decline due to aging or disease can be assessed with quantitative motion analysis, but this currently requires expensive laboratory equipment. We introduce a self-guided quantitative motion analysis of the widely used five-repetition sit-to-stand test using a smartphone. Across 35 US states, 405 participants recorded a video performing the test in their homes.
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