The Development of a Data Glove-Based System for Assisting the Solution of Puzzles

In recent years, advanced wearable devices have made it possible to reconstruct real-world activities in the XR environment. In this paper, we aim to develop a human-interactive operation assistant system using pressure distribution data from gloves by applying One-Dimensional Convolutional Neural Network(IDCNN). The IDCNN model showed 98.83% accuracy. A human interactive operation assistant system proves that 1.52 times faster average solution time than without this system and improves the number of errors while doing the task. This study can help us to develop more advanced tactile sensor data glove applications.