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Related Concept Videos

Deglutition01:25

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Swallowing, otherwise known as deglutition, facilitates the transport of food from the mouth to the stomach. It is a multifaceted process that involves both the tongue and the muscles of the throat and esophagus. Saliva and mucus aid in this process, which takes approximately 4 to 8 seconds for semi-solid or solid food and around 1 second for liquids or very soft food.
Swallowing can be divided into three stages: the voluntary phase, the pharyngeal phase, and the esophageal phase. Although the...
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Short-term regulation of food intake primarily involves neural signals from the gastrointestinal (GI) tract, blood nutrient levels, and GI tract hormones. Communication between the gut and brain via vagal nerve fibers plays a significant role in evaluating the contents of the gut. Clinical studies have shown that protein ingestion produces a more prolonged response in these nerve fibers compared to an equivalent amount of glucose. Additionally, the activation of stretch receptors caused by GI...
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Related Experiment Video

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Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

Automatic food intake detection based on swallowing sounds.

Oleksandr Makeyev1, Paulo Lopez-Meyer, Stephanie Schuckers

  • 1Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, 4 East Alumni Ave, Kingston, RI 02881, USA.

Biomedical Signal Processing and Control
|November 6, 2012
PubMed
Summary

This study introduces an automatic method to detect food intake by analyzing swallowing sounds. This technology aids in understanding eating behaviors and could be used in real-world settings.

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Area of Science:

  • Biomedical Engineering
  • Computational Health
  • Behavioral Science

Background:

  • Objective monitoring of ingestive behavior is crucial for understanding eating disorders and obesity.
  • Current methods for tracking food intake are often subjective or burdensome.
  • Developing automated, non-invasive techniques is a significant research goal.

Purpose of the Study:

  • To present a novel, fully automatic methodology for detecting food intake episodes.
  • To utilize acoustic signals of swallowing for objective ingestive behavior analysis.
  • To improve the understanding of eating patterns in relation to health conditions.

Main Methods:

  • A two-stage approach involving acoustic swallowing detection using mel-scale Fourier spectrum features and support vector machines.
  • Employing Principal Component Analysis and a smoothing algorithm to enhance swallowing detection accuracy.
  • Using the frequency of detected swallows as a predictor for food intake episodes.

Main Results:

  • Achieved average accuracies exceeding 80% for intra-subject and 75% for inter-subject models with a 30-second temporal resolution.
  • Demonstrated comparable detection accuracies between obese and lean subjects across 44.1 hours of data.
  • Validated the feasibility of food intake detection based on swallowing sounds, with 7305 swallows analyzed.

Conclusions:

  • The proposed methodology shows significant potential for the automatic monitoring of ingestive behavior.
  • Wearable, non-invasive acoustic sensors enable the application of this technique in free-living conditions.
  • This approach offers a promising tool for objective assessment in obesity and eating disorder research.