Running Related Injury

Running-related injuries are a significant concern, prompting research into predicting and preventing them. Current research focuses on using computer vision and machine learning algorithms, such as neural networks and random forests, to analyze movement patterns (e.g., knee angles, body posture) and identify risk factors for injuries like ACL tears. These methods leverage data from various sources, including wearable sensors and video recordings, aiming to improve injury prediction and prevention strategies. The ultimate goal is to develop effective tools for personalized risk assessment and intervention, enhancing athlete safety and reducing healthcare burdens.