Chewing is a core component of the intake process and micro-structure. Our early work focused on wearable/implant devices worn at/in the ear canal to capture food breakdown sounds conducted from mandible to skull. We found that the sounds are characteristic for certain foods and food types due to their material textures. For example, carrots and lettuce have wet-crisp cell structures that create specific acoustic patterns when chewed. Pattern classification of up to 19 foods was shown and is until today one of the highest number of foods discriminated by computers.
Chewing could help to estimate food weight and amount too, as chewing cycles could be monitored with the ear-worn sensor. Weight estimation error was ~20% for several foods, well below the confirmed errors of manual conducted self-reports. Currently, our work focused on chewing analysis integrated into smart eyeglasses. Results show that Electromyography (EMG) can be used to measure Temporalis muscle contraction during chewing and thus identify chewing in highly comfortable and unobtrusive, personalised 3D-printed eyeglasses.
- Digital development & production
"Monitoring chewing and eating in free-living using smart eyeglasses", IEEE Journal of Biomedical and Health Informatics, IEEE Xplore, 2018.,
"Personalizing 3D-printed smart eyeglasses to augment daily life", IEEE Computer, 2017.,
"Bite Glasses: Measuring Chewing Using EMG and Bone Vibration in Smart Eyeglasses", Proceedings of the 2016 ACM International Symposium on Wearable Computers (ISWC '16), ACM, September 2016.,
"Regular-look eyeglasses can monitor chewing", Proceedings of the 2016 ACM International Symposium on Wearable Computers (ISWC '16), ACM, September 2016.,
"Diet eyeglasses: Recognising food chewing using EMG and smart eyeglasses", Proceedings of the International Conference on Wearable and Implantable Body Sensor Networks (BSN' 16), IEEE, June 2016.,
"A Wearable Earpad Sensor for Chewing Monitoring", Sensors 2010: Proceedings of IEEE Sensors conference, IEEE, 2010.,
"Bite weight prediction from acoustic recognition of chewing", IEEE Transactions on Biomedical Engineering, June 2009.,
"Analysis of Chewing Sounds for Dietary Monitoring", UbiComp 2005: Proceedings of the 7th International Conference on Ubiquitous Computing, Springer Berlin, Heidelberg, September 2005.,