Earable -- an ear-worn biosignal sensing platform for cognitive state monitoring and human-computer interaction (demo)

Pham, Nhat, Kim, Taeho, Thayer, Frederick M., Nguyen, Anh and Vu, Tam 2019. Earable -- an ear-worn biosignal sensing platform for cognitive state monitoring and human-computer interaction (demo). Presented at: MobiSys '19: 17th Annual International Conference on Mobile Systems, Applications, and Services, Seoul, Republic of Korea, 17-21 June 2019. MobiSys '19: Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services. Association for Computing Machinery, pp. 685-686. 10.1145/3307334.3328582

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Abstract

Cognitive state monitoring is crucial for neurological disorders such as epilepsy, narcolepsy, insomnia, and many other human health concerns. The capability to continuously monitor an individual wearing the device and accurately provide early warnings of seizures or narcolepsy sleep attacks would be game-changing for these disorders. Beyond human health, complete hand-free/voice-free human-computer interaction is desirable for privacy-sensitive use cases or people with disabilities. To achieve this goal, we propose Earable, an ear-worn biosensing platform for cognitive state quantification and human-computer interaction. Earable can capture biosignal including brain waves activities, eyes movements, and facial muscle contractions from the back of the ears. Its form factor is convenient to use in everyday life. In this demo, we show two use cases for our Earable platform. First, as an example of cognitive state monitoring, our system plays relaxing music and dims the light when the user is trying to relax or sleep by detecting alpha and beta waves generated by the brain. Second, as an example of human-computer interaction, our system controls a drone with eye movements and facial muscle activity.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Association for Computing Machinery
ISBN:	978-1-4503-6661-8
Date of First Compliant Deposit:	14 August 2023
Date of Acceptance:	12 June 2019
Last Modified:	06 Sep 2023 07:15
URI:	https://orca.cardiff.ac.uk/id/eprint/161759

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