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

Zheng Zeng; Linkai Tao; Hangyu Zhu; Yunfeng Zhu; Long Meng; Jiahao Fan; Chen Chen; Wei Chen

doi:10.1109/JTEHM.2023.3320713

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

IEEE J Transl Eng Health Med. 2023 Sep 29:12:56-65. doi: 10.1109/JTEHM.2023.3320713. eCollection 2024.

Authors

Zheng Zeng¹, Linkai Tao², Hangyu Zhu¹, Yunfeng Zhu¹, Long Meng¹, Jiahao Fan¹, Chen Chen³, Wei Chen^{1

3}

Affiliations

¹ Center for Intelligent Medical Electronics, School of Information Science and TechnologyFudan University Shanghai 200433 China.
² Department of Industrial DesignEindhoven University of Technology 5600 MB Eindhoven The Netherlands.
³ Human Phenome Institute, Fudan University Shanghai 201203 China.

Abstract

Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson's disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications.

Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels.

Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects.

Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from -50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively.

Conclusion: 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.

Keywords: Channel selection; electrooculography (EOG); feature selection; gaze estimation; saccade.

MeSH terms

Autism Spectrum Disorder* / diagnosis
Electrodes
Electrooculography / methods
Eye Movements
Humans
Parkinson Disease* / diagnosis

Grants and funding

This work was supported in part by the Shanghai Municipal Science and Technology International Research and Development Collaboration Project under Grant 20510710500, in part by the Shanghai Committee of Science and Technology under Grant 20S31903900, and in part by the National Natural Science Foundation of China under Grant 62001118.