Non-invasive monitoring of eating behavior using spectrogram analysis in a wearable necklace

Nabil Alshurafa, Haik Kalantarian, Mohammad Pourhomayoun, Shruti Sarin, Jason J. Liu, Majid Sarrafzadeh

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

15 Scopus citations

Abstract

Food intake levels, hydration, chewing and swallowing rate, and dietary choices are all factors known to impact one's health. This paper presents a novel wearable system in the form of a necklace, which aggregates data from an embedded piezoelectric sensor capable of detecting skin motion in the lower trachea during ingestion. We propose an algorithm based on spectrogram analysis of piezoelectric sensor signals to accurately distinguish between food types such as liquid and solid, hot and cold drinks and hard and soft foods. The necklace transmits data to a smartphone, which performs the processing of the signals, classifies the food type, and provides visual feedback to the user to assist the user in monitoring their eating habits over time. Experimental results demonstrate high classification accuracy of the proposed method, and validate the use of a spectrogram in extracting key features representative of the unique swallow patterns of various foods.

Original languageEnglish (US)
Title of host publication2014 IEEE Healthcare Innovation Conference, HIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages71-74
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

Publication series

Name2014 IEEE Healthcare Innovation Conference, HIC 2014

Other

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

ASJC Scopus subject areas

  • Medicine(all)
  • Biomedical Engineering

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