Non-invasive monitoring of chewing and swallowing for objective quantification of ingestive behavior
- 22 April 2008
- journal article
- Published by IOP Publishing in Physiological Measurement
- Vol. 29 (5), 525-541
- https://doi.org/10.1088/0967-3334/29/5/001
Abstract
A methodology of studying of ingestive behavior by non-invasive monitoring of swallowing (deglutition) and chewing (mastication) has been developed. The target application for the developed methodology is to study the behavioral patterns of food consumption and producing volumetric and weight estimates of energy intake. Monitoring is non-invasive based on detecting swallowing by a sound sensor located over laryngopharynx or by a bone conduction microphone and detecting chewing through a below-the-ear strain sensor. Proposed sensors may be implemented in a wearable monitoring device, thus enabling monitoring of ingestive behavior in free living individuals. In this paper, the goals in the development of this methodology are two-fold. First, a system comprised of sensors, related hardware and software for multimodal data capture is designed for data collection in a controlled environment. Second, a protocol is developed for manual scoring of chewing and swallowing for use as a gold standard. The multi-modal data capture was tested by measuring chewing and swallowing in twenty one volunteers during periods of food intake and quiet sitting (no food intake). Video footage and sensor signals were manually scored by trained raters. Inter-rater reliability study for three raters conducted on the sample set of 5 subjects resulted in high average intra-class correlation coefficients of 0.996 for bites, 0.988 for chews, and 0.98 for swallows. The collected sensor signals and the resulting manual scores will be used in future research as a gold standard for further assessment of sensor design, development of automatic pattern recognition routines, and study of the relationship between swallowing/chewing and ingestive behavior.This publication has 39 references indexed in Scilit:
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