Publications by authors named "Lars VAN Rengs"
Article Synopsis
- The study explores the accuracy of instrumented insoles in estimating tissue loads at common running injury sites, using data from 19 runners under various conditions.
- A neural network was trained on insole data to predict several types of stress and strain on the Achilles tendon and other joints, achieving strong correlation between modeled and predicted values.
- Results indicate that these insoles can provide accurate tissue loading estimates that outperform simpler metrics like step counts, allowing for better analysis of running injuries in real-time situations.
Understanding how loading and damage on common running injury locations changes across speeds, surface gradients, and step frequencies may inform training programs and help guide progression/rehabilitation after injuries. However, research investigating tissue loading and damage in running is limited and fragmented across different studies, thereby impairing comparison between conditions and injury locations. This study examined per-step peak load and impulse, cumulative impulse, and cumulative weighted impulse (hereafter referred to as cumulative damage) on three common injury locations (patellofemoral joint, tibia, and Achilles tendon) across different speeds, surface gradients, and cadences.
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