Literature DB >> 24845288

Automatic ingestion monitor: a novel wearable device for monitoring of ingestive behavior.

Juan M Fontana, Muhammad Farooq, Edward Sazonov.   

Abstract

Objective monitoring of food intake and ingestive behavior in a free-living environment remains an open problem that has significant implications in study and treatment of obesity and eating disorders. In this paper, a novel wearable sensor system (automatic ingestion monitor, AIM) is presented for objective monitoring of ingestive behavior in free living. The proposed device integrates three sensor modalities that wirelessly interface to a smartphone: a jaw motion sensor, a hand gesture sensor, and an accelerometer. A novel sensor fusion and pattern recognition method was developed for subject-independent food intake recognition. The device and the methodology were validated with data collected from 12 subjects wearing AIM during the course of 24 h in which both the daily activities and the food intake of the subjects were not restricted in any way. Results showed that the system was able to detect food intake with an average accuracy of 89.8%, which suggests that AIM can potentially be used as an instrument to monitor ingestive behavior in free-living individuals.

Entities:  

Mesh:

Year:  2014        PMID: 24845288      PMCID: PMC4161033          DOI: 10.1109/TBME.2014.2306773

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  25 in total

Review 1.  The control of food intake of free-living humans: putting the pieces back together.

Authors:  John M de Castro
Journal:  Physiol Behav       Date:  2010-05-05

Review 2.  Integrated prevention of obesity and eating disorders: barriers, developments and opportunities.

Authors:  David Sánchez-Carracedo; Dianne Neumark-Sztainer; Gemma López-Guimerà
Journal:  Public Health Nutr       Date:  2012-03-28       Impact factor: 4.022

3.  A Sensor System for Automatic Detection of Food Intake Through Non-Invasive Monitoring of Chewing.

Authors:  Edward S Sazonov; Juan M Fontana
Journal:  IEEE Sens J       Date:  2012       Impact factor: 3.301

4.  Bite weight prediction from acoustic recognition of chewing.

Authors:  Oliver Amft; Martin Kusserow; Gerhard Tröster
Journal:  IEEE Trans Biomed Eng       Date:  2009-03-04       Impact factor: 4.538

5.  Estimation of feature importance for food intake detection based on Random Forests classification.

Authors:  Juan M Fontana; Muhammad Farooq; Edward Sazonov
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

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

Authors:  Edward Sazonov; Stephanie Schuckers; Paulo Lopez-Meyer; Oleksandr Makeyev; Nadezhda Sazonova; Edward L Melanson; Michael Neuman
Journal:  Physiol Meas       Date:  2008-04-22       Impact factor: 2.833

7.  The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication.

Authors:  James I Hudson; Eva Hiripi; Harrison G Pope; Ronald C Kessler
Journal:  Biol Psychiatry       Date:  2006-07-03       Impact factor: 13.382

8.  A new method for measuring meal intake in humans via automated wrist motion tracking.

Authors:  Yujie Dong; Adam Hoover; Jenna Scisco; Eric Muth
Journal:  Appl Psychophysiol Biofeedback       Date:  2012-04-10

9.  Evaluation of Chewing and Swallowing Sensors for Monitoring Ingestive Behavior.

Authors:  Juan M Fontana; Edward S Sazonov
Journal:  Sens Lett       Date:  2013-03

10.  Biased over- or under-reporting is characteristic of individuals whether over time or by different assessment methods.

Authors:  A E Black; T J Cole
Journal:  J Am Diet Assoc       Date:  2001-01
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  51 in total

1.  Modifying eating behavior: novel approaches for reducing body weight, preventing weight regain, and reducing chronic disease risk.

Authors:  Nana Gletsu-Miller; Megan A McCrory
Journal:  Adv Nutr       Date:  2014-11-14       Impact factor: 8.701

Review 2.  Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review.

Authors:  Brooke M Bell; Ridwan Alam; Nabil Alshurafa; Edison Thomaz; Abu S Mondol; Kayla de la Haye; John A Stankovic; John Lach; Donna Spruijt-Metz
Journal:  NPJ Digit Med       Date:  2020-03-13

3.  Advances and Controversies in Diet and Physical Activity Measurement in Youth.

Authors:  Donna Spruijt-Metz; Cheng K Fred Wen; Brooke M Bell; Stephen Intille; Jeannie S Huang; Tom Baranowski
Journal:  Am J Prev Med       Date:  2018-08-19       Impact factor: 5.043

4.  EarBit: Using Wearable Sensors to Detect Eating Episodes in Unconstrained Environments.

Authors:  Abdelkareem Bedri; Richard Li; Malcolm Haynes; Raj Prateek Kosaraju; Ishaan Grover; Temiloluwa Prioleau; Min Yan Beh; Mayank Goel; Thad Starner; Gregory Abowd
Journal:  Proc ACM Interact Mob Wearable Ubiquitous Technol       Date:  2017-09

Review 5.  Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.

Authors:  L Sacchi; J H Holmes
Journal:  Yearb Med Inform       Date:  2016-08-02

Review 6.  Appetite responses to high-fat meals or diets of varying fatty acid composition: a comprehensive review.

Authors:  S Kaviani; J A Cooper
Journal:  Eur J Clin Nutr       Date:  2017-01-18       Impact factor: 4.016

7.  NeckSense: A Multi-Sensor Necklace for Detecting Eating Activities in Free-Living Conditions.

Authors:  Shibo Zhang; Yuqi Zhao; Dzung Tri Nguyen; Runsheng Xu; Sougata Sen; Josiah Hester; Nabil Alshurafa
Journal:  Proc ACM Interact Mob Wearable Ubiquitous Technol       Date:  2020-06

8.  The "Virtual Digital Twins" Concept in Precision Nutrition.

Authors:  Kalliopi Gkouskou; Ioannis Vlastos; Petros Karkalousos; Dimitrios Chaniotis; Despina Sanoudou; Aristides G Eliopoulos
Journal:  Adv Nutr       Date:  2020-11-16       Impact factor: 8.701

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

Authors:  Jungman Chung; Wonjoon Oh; Dongyoub Baek; Sunwoong Ryu; Won Gu Lee; Hyunwoo Bang
Journal:  J Vis Exp       Date:  2018-02-14       Impact factor: 1.355

10.  Between- and Within-Subjects Predictors of the Kilocalorie Content of Bites of Food.

Authors:  James N Salley; Adam W Hoover; Eric R Muth
Journal:  J Acad Nutr Diet       Date:  2019-02-16       Impact factor: 4.910

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