Non-invasive monitoring of chewing and swallowing for objective quantification of ingestive behavior

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.

Wearable Food Intake Monitoring Technologies: A Comprehensive Review

“…A strain sensor is also feasible for detecting vibration in chewing events. Sazonov and Fontana [86] embedded a strain sensor below the outer ear to capture the motion of the lower jaw caused by the posterior border of the mandible's ramus relative to the temporal bone [87].…”

“…Sazonov et al [87] developed a system containing a throat microphone placed over the laryngopharynx in the throat. The signal is strong in this position because it is close to the origin of the swallowing sound.…”

Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review (Preprint)

“…Because of the known limitation of existing dietary assessment methods, the research community is motivated to develop new solutions aimed at (semi-)automating the assessment of dietary intake. While the automated methods of real-time image-based detection [14][15][16][17][18][19][20][21][22][23][24] and real-time detection of food intake by biomechanical sensors or hand-held devices [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42] have seen significant progress [15,24] in terms of identifying foods and estimating portion sizes [14][15][16][17][18][19][20][21][22][23][24] detecting wrist or hand motion [25][26][27][28]…”

“…image-assisted and image-based assessment [14][15][16][17][18][19][20][21][22][23][24] and the detection of food intake by biomechanical sensors or hand-held devices [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42]. Significant progress has been made in image-assisted and image-based food recording that has resulted in the improved accuracy of dietary self-report [15,24].…”

“…Significant progress has been made in image-assisted and image-based food recording that has resulted in the improved accuracy of dietary self-report [15,24]. Similarly, wearable technology including gyroscopes, microphones, and mechanical or electrical impedance sensors have been adapted to detect wrist or hand motion [25][26][27][28][29][30][31] or patterns of chewing or swallowing indicative of food intake (eg, number of bites) [32][33][34][35][36][37][38][39][40][41]. However, design and proof-of-concept data suggest the automation of dietary assessment remains out of reach for the time being.…”