In-Ear Human-Computer Interaction
Using EarMag to Detect Head and Jaw Movements
M.J.F. van Oort (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Przemysław Pawełczak – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Ujwal Gadiraju – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Gabriel Sáenz – Graduation committee member (Jawsaver BV)
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Abstract
This thesis explores the use of in-ear magnetosensing (EarMag) as a novel sensing technique for detecting jaw and head movements in the context of human-computer interaction. While prior work has explored the use of acoustic, inertial, and visual sensing, the potential of EarMag remains to be explored. As a proof of concept, 17 orofacial physiotherapy-related exercises were collected from 21 participants using EarMag-enabled earables. A soft voting ensemble of support vector machine and random forest achieved 76% accuracy for five exercises on an unseen test set of ten users. While individual anatomical differences pose challenges for generalization, this work highlights the potential of EarMag for applications such as assistive technologies, silent speech interfaces, and biosignal tracking.