Spectrogram-based audio classification of nutrition intake

Haik Kalantarian, Nabil Alshurafa, Mohammad Pourhomayoun, Shruti Sarin, Tuan Le, Majid Sarrafzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations


Acoustic monitoring of food intake in an unobtrusive, wearable form-factor can encourage healthy dietary choices by enabling individuals to monitor their eating patterns, maintain regularity in their meal times, and ensure adequate hydration levels. In this paper, we describe a system capable of monitoring food intake by means of a throat microphone, classifying the data based on the food being consumed among several categories through spectrogram analysis, and providing user feedback in the form of mobile application. We are able to classify sandwich swallows, sandwich chewing, water swallows, and none, with an F-Measure of 0.836.

Original languageEnglish (US)
Title of host publication2014 IEEE Healthcare Innovation Conference, HIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781467363648
StatePublished - Feb 10 2014
Event2014 IEEE Healthcare Innovation Conference, HIC 2014 - Seattle, United States
Duration: Oct 8 2014Oct 10 2014

Publication series

Name2014 IEEE Healthcare Innovation Conference, HIC 2014


Other2014 IEEE Healthcare Innovation Conference, HIC 2014
Country/TerritoryUnited States


  • nutrition
  • spectrogram
  • swallow detection

ASJC Scopus subject areas

  • General Medicine
  • Biomedical Engineering


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