External Research Materials for "A Privacy-Preserving Skeleton Object Detection Framework for Fall Monitoring Using RF-DETR Nano and YOLOv11n"

This deposit contains processed research outputs supporting the manuscript “A Privacy-Preserving Skeleton Object Detection Framework for Fall Monitoring Using RF-DETR Nano and YOLOv11n”. The materials include epoch-level training metrics for four detector-representation pipelines, image-level predictions for the synchronized internal test set, aggregate evaluation results from the independent UR Fall Detection Dataset, frame-level outputs from 42 self-recorded real-world videos, publication figures, methodological pseudocode, and a data dictionary. The deposit supports a controlled comparison of RGB and skeleton representations using RF-DETR Nano and YOLOv11n. Original third-party datasets, trained weights, and raw self-recorded videos are not included.