A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements.

Zheng ZengLinkai TaoHangyu ZhuYunfeng ZhuLong Meng Jiahao Fan Chen Chen Wei Chen

Published in: IEEE journal of translational engineering in health and medicine (2023)

We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson's disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications.

Keyphrases

autism spectrum disorder
attention deficit hyperactivity disorder
high resolution
healthcare
machine learning
working memory
intellectual disability
mass spectrometry
human health
gold nanoparticles
carbon nanotubes
neural network