Explainable AI Based Neck Direction Prediction and Analysis Using YOLOV8

This research focuses on the detection and analysis of neck rotation during head impacts using the YOLOv8 model, with the goal of enhancing preventive healthcare measures. Accurately monitoring the neck’s position and orientation is crucial for predicting its movement direction during such impacts. The study simulates mild head impacts by replicating neck movements like flexion and lateral rotation, inspired by scenarios commonly seen in American football. Data is collected from ten subjects—five male and five female. The YOLOv8 model is employed to detect and track neck rotation in real-time using video footage, offering high accuracy in determining directional movement