ArticleFrontiers in neuroscience2019
Absolute Eye Gaze Estimation With Biosensors in Hearing Aids.
Article in Frontiers in neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- earEOG via periauricular electrodes to facilitate eye tracking in a natural headphone form factor.Scientific reports · 2025Article
- Improved tactile speech robustness to background noise with a dual-path recurrent neural network noise-reduction method.Scientific reports · 2024Article
- Comparing In-ear EOG for Eye-Movement Estimation With Eye-Tracking: Accuracy, Calibration, and Speech Comprehension.Frontiers in neuroscience · 2022Article
- EEGs Vary Less Between Lab and Home Locations Than They Do Between People.Frontiers in computational neuroscience · 2021Article
- Assessment of Vestigial Auriculomotor Activity to Acoustic Stimuli Using Electrodes In and Around the Ear.Trends in hearingArticle
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
People with hearing impairment typically have difficulties following conversations in multi-talker situations. Previous studies have shown that utilizing eye gaze to steer audio through beamformers could be a solution for those situations. Recent studies have shown that in-ear electrodes that capture electrooculography in the ear (EarEOG) can estimate the eye-gaze relative to the head, when the head was fixed. The head movement can be estimated using motion sensors around the ear to create an estimate of the absolute eye-gaze in the room. In this study, an experiment was designed to mimic a multi-talker situation in order to study and model the EarEOG signal when participants attempted to follow a conversation. Eleven hearing impaired participants were presented speech from the DAT speech corpus (Bo Nielsen et al., 2014), with three targets positioned at -30°, 0° and +30° azimuth. The experiment was run in two setups: one where the participants had their head fixed in a chinrest, and the other where they were free to move their head. The participants' task was to focus their visual attention on an LED-indicated target that changed regularly. A model was developed for the relative eye-gaze estimation, taking saccades, fixations, head movement and drift from the electrode-skin half-cell into account. This model explained 90.5% of the variance of the EarEOG when the head was fixed, and 82.6% when the head was free. The absolute eye-gaze was also estimated utilizing that model. When the head was fixed, the estimation of the absolute eye-gaze was reliable. However, due to hardware issues, the estimation of the absolute eye-gaze when the head was free had a variance that was too large to reliably estimate the attended target. Overall, this study demonstrated the potential of estimating absolute eye-gaze using EarEOG and motion sensors around the ear.
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