ID.EARS: One-Ear EEG Device with Biosignal Noise for Real-Time Gesture Recognition and Various Interactions

要旨

In-ear EEG research has traditionally treated biological signals other than brainwaves, such as electromyography (EMG) and electrooculography (EOG), as unwanted noise to be removed. However, instead of discarding these signals, we developed ID.EARS, a single-ear, dry electrode-based device that utilizes these signals for real-time gesture input. We first identified the optimal position for EEG measurement around the ear using the Alpha Attenuation Response (AAR) test and collected biological signals that occur alongside brainwaves at this location. Using these signals, we created a real-time artifact detection model capable of recognizing five specific gestures: blinking, left and right winking, teeth clenching, and chewing. This model achieved over 90% accuracy in cross-validation experiments. Leveraging this model and device, we propose several application scenarios, including music control, accessibility features, MR/XR control, and healthcare services. This innovative approach extends the use of ear-EEG devices beyond healthcare, opening up possibilities for natural user interfaces.

著者
Hyunjin An
Digital health team, Suwon, Korea, Republic of
Eunkyu Oh
Samsung Electronics, Suwon, Korea, Republic of
Yoosung Kim
Samsung Electronics, Seoul, Korea, Republic of
Seonho Kim
samsung electronics , Suwon, Korea, Republic of
Dasom Park
Samsung electronics., Suwon, Korea, Republic of
Changhoon Oh
Yonsei University, Seoul, Korea, Republic of
DOI

10.1145/3706598.3714185

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714185

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Biosensing for Interactions

Annex Hall F205
7 件の発表
2025-05-01 18:00:00
2025-05-01 19:30:00
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