Publications › COMSNETS 2025
Unlocking Eye Gestures with Earable Inertial Sensing for Accessible HCI
Abstract
Eye gestures are widely used in many applications, including device control, biometrics, visual analytics, and health-care, like Alzheimer’s, accessibility, etc. The conventional method for eye gesture detection needs visual information processing devices or smart glasses to capture the movement patterns of the eyeballs. In this paper, we present a novel framework that utilizes inertial measurement unit (IMU) sensors embedded in earable devices for real-time eye gesture detection, which can work as a complementary to visual information processing devices. The framework translates specific eye movements into actionable commands, enabling hands-free interaction for users with limited mobility. Through extensive experimentation with 14 participants across diverse activities such as sitting, walking, running, and driving, the framework demonstrated high accuracy in eye gesture recognition, achieving a macro F1 score of 0.85 on our self-collected dataset.
BibTeX
@inproceedings{chugh2025unlocking,
title={Unlocking Eye Gestures with Earable Inertial Sensing for Accessible HCI},
author={Chugh, G. and Chakraborty, S. and Chakraborty, S.},
booktitle={COMSNETS 2025},
year={2025},
url={https://doi.org/10.1109/comsnets63942.2025.10885707}
}