EgoExplorer's contributions include: placing vision, motion, touch, and finger details into the same wearable collection framework; using a calibration-plus-constraint method to demonstrate that sparse sensing can also yield relatively high-quality motion reconstruction; and directly linking the dataset with humanoid retargeting, shortening the path from human demonstration to robot policy.