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A wearable system for detecting eating activities with proximity sensors in the outer ear
Author(s) -
Abdelkareem Bedri,
Apoorva Verlekar,
Edison Thomaz,
Valerie Avva,
Thad Starner
Publication year - 2015
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2802083.2808411
Subject(s) - robustness (evolution) , wearable computer , computer science , inertial measurement unit , mastication , human–computer interaction , artificial intelligence , computer vision , dentistry , embedded system , medicine , biochemistry , chemistry , gene
This paper presents an approach for automatically detecting eating activities by measuring deformations in the ear canal walls due to mastication activity. These deformations are measured with three infrared proximity sensors encapsulated in an off-the-shelf earpiece. To evaluate our method, we conducted a user study in a lab setting where 20 participants were asked to perform eating and non-eating activities. A user dependent analysis demonstrated that eating could be detected with 95.3% accuracy. This result indicates that proximity sensing offers an alternative to acoustic and inertial sensing in eating detection while providing benefits in terms of privacy and robustness to noise.

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