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

16 Scopus citations

Abstract

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.
Pages161-164
Number of pages4
ISBN (Electronic)9781467363648
DOIs
StatePublished - Feb 10 2014
Event2014 IEEE Healthcare Innovation Conference, HIC 2014 - Seattle, United States
Duration: Oct 8 2014Oct 10 2014

Other

Other2014 IEEE Healthcare Innovation Conference, HIC 2014
CountryUnited States
CitySeattle
Period10/8/1410/10/14

Keywords

  • nutrition
  • spectrogram
  • swallow detection

ASJC Scopus subject areas

  • Medicine(all)
  • Biomedical Engineering

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    Kalantarian, H., Alshurafa, N., Pourhomayoun, M., Sarin, S., Le, T., & Sarrafzadeh, M. (2014). Spectrogram-based audio classification of nutrition intake. In 2014 IEEE Healthcare Innovation Conference, HIC 2014 (pp. 161-164). [7038899] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HIC.2014.7038899