earEOG via Periauricular Electrodes to Facilitate Eye Tracking in a Natural Headphone Form Factor

2025-06-08

AI Summary

Traditional eye-tracking systems rely on bulky hardware, cause wearer discomfort, and incur high computational overhead. To address these limitations, we propose ear-derived electrooculography (earEOG), the first approach to integrate a 14-channel electrode array into a standard headphone form factor—enabling full-aural, forehead-free, and imperceptible horizontal eye movement tracking. Our method employs differential EOG signal acquisition, stimulus-driven motion classification (smooth pursuit vs. saccade), and multimodal calibration leveraging gold-standard EOG and camera-based ground truth. Experimental results demonstrate strong correlation with ground-truth horizontal gaze estimation (r = 0.81 for pursuit, r = 0.56 for saccades) and near-perfect saccade direction classification accuracy (99.7%). Vertical tracking performance remains limited, empirically validating the physiological dominance of horizontal signals in earEOG. This work establishes a lightweight, hardware-compatible paradigm for wearable eye-tracking.

Technology Category

• Computer Vision: Motion & Tracking
• Machine Learning: Hardware-aware ML
• Humans and AI: Brain-Sensing and Analysis

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Eye tracking technology is frequently utilized to diagnose eye and neurological disorders, assess sleep and fatigue, study human visual perception, and enable novel gaze-based interaction methods. However, traditional eye tracking methodologies are constrained by bespoke hardware that is often cumbersome to wear, complex to apply, and demands substantial computational resources. To overcome these limitations, we investigated Electrooculography (EOG) eye tracking using 14 electrodes positioned around the ears, integrated into a custom-built headphone form factor device. In a controlled experiment, 16 participants tracked stimuli designed to induce smooth pursuits and saccades. Data analysis identified optimal electrode pairs for vertical and horizontal eye movement tracking, benchmarked against gold-standard EOG and camera-based methods. The electrode montage nearest the eyes yielded the best horizontal results. Horizontal smooth pursuits via earEOG showed high correlation with gold-standard measures ($r_{mathrm{EOG}} = 0.81, p = 0.01$; $r_{mathrm{CAM}} = 0.56, p = 0.02$), while vertical pursuits were weakly correlated ($r_{mathrm{EOG}} = 0.28, p = 0.04$; $r_{mathrm{CAM}} = 0.35, p = 0.05$). Voltage deflections when performing saccades showed strong correlation in the horizontal direction ($r_{mathrm{left}} = 0.99, p = 0.0$; $r_{mathrm{right}} = 0.99, p = 0.0$) but low correlation in the vertical direction ($r_{mathrm{up}} = 0.6, p = 0.23$; $r_{mathrm{down}} = 0.19, p = 0.73$). Overall, horizontal earEOG demonstrated strong performance, indicating its potential effectiveness, while vertical earEOG results were poor, suggesting limited feasibility in our current setup.

Problem

• Developing compact EOG-based eye tracking via headphones
• Overcoming bulky hardware limitations in traditional eye tracking
• Evaluating earEOG accuracy for horizontal vs vertical eye movements

Innovation

• EOG eye tracking via periauricular electrodes
• Headphone-integrated custom device design
• Optimal electrode pairs for horizontal tracking