A novel approach for chewing detection based on a wearable PPG sensor
Autor: | Lingchuan Zhou, Vasileios Papapanagiotou, Christos Diou, Anastasios Delopoulos, Janet van den Boer, Monica Mars |
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Rok vydání: | 2016 |
Předmět: |
Engineering
Wearable computer 01 natural sciences Signal Task (project management) 03 medical and health sciences 0302 clinical medicine Dietary monitoring Photoplethysmogram Electronic engineering Humans Life Science Computer vision 030212 general & internal medicine Photoplethysmography Eating behaviour Sensory Science and Eating Behaviour Monitoring Physiologic VLAG Signal processing business.industry 010401 analytical chemistry Signal Processing Computer-Assisted Equipment Design Pipeline (software) 0104 chemical sciences Sensoriek en eetgedrag Mastication sense organs Artificial intelligence business Algorithms |
Zdroj: | EMBC Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Institute of Electrical and Electronics Engineers Inc. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
Popis: | Monitoring of human eating behaviour has been attracting interest over the last few years, as a means to a healthy lifestyle, but also due to its association with serious health conditions, such as eating disorders and obesity. Use of self-reports and other non-automated means of monitoring have been found to be unreliable, compared to the use of wearable sensors. Various modalities have been reported, such as acoustic signal from ear-worn microphones, or signal from wearable strain sensors. In this work, we introduce a new sensor for the task of chewing detection, based on a novel photoplethysmography (PPG) sensor placed on the outer earlobe to perform the task. We also present a processing pipeline that includes two chewing detection algorithms from literature and one new algorithm, to process the captured PPG signal, and present their effectiveness. Experiments are performed on an annotated dataset recorded from 21 individuals, including more than 10 hours of eating and non-eating activities. Results show that the PPG sensor can be successfully used to support dietary monitoring. |
Databáze: | OpenAIRE |
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