Motivated by the growing interest in enhancing intuitive physical Human-Machine Interaction (HRI/HVI), this study aims to propose a robust tactile hand gesture recognition system. We performed a comprehensive evaluation of different hand gesture recognition approaches for a large area tactile sensing interface (touch interface) constructed from conductive textiles. Our evaluation encompassed traditional feature engineering methods, as well as contemporary deep learning techniques capable of real-time interpretation of a range of hand gestures, accommodating variations in hand sizes, movement velocities, applied pressure levels, and interaction points. Our extensive analysis of the various methods makes a significant contribution to tactile-based gesture recognition in the field of human-machine interaction.
@article{arxiv.2405.17038,
title = {Advancements in Tactile Hand Gesture Recognition for Enhanced Human-Machine Interaction},
author = {Chiara Fumelli and Anirvan Dutta and Mohsen Kaboli},
journal= {arXiv preprint arXiv:2405.17038},
year = {2024}
}