Literature DB >> 28463209

Monitoring Chewing and Eating in Free-Living Using Smart Eyeglasses.

Rui Zhang, Oliver Amft.   

Abstract

We propose to 3-D-print personal fitted regular-look smart eyeglasses frames equipped with bilateral electromyography recording to monitor temporalis muscles' activity for automatic dietary monitoring. Personal fitting supported electrode-skin contacts are at temple ear bend and temple end positions. We evaluated the smart monitoring eyeglasses during in-lab and free-living studies of food chewing and eating event detection with ten participants. The in-lab study was designed to explore three natural food hardness levels and determine parameters of an energy-based chewing cycle detection. Our free-living study investigated whether chewing monitoring and eating event detection using smart eyeglasses is feasible in free-living. An eating event detection algorithm was developed to determine intake activities based on the estimated chewing rate. Results showed an average food hardness classification accuracy of 94% and chewing cycle detection precision and recall above 90% for the in-lab study and above 77% for the free-living study covering 122 hours of recordings. Eating detection revealed the 44 eating events with an average accuracy above 95%. We conclude that smart eyeglasses are suitable for monitoring chewing and eating events in free-living and even could provide further insights into the wearer's natural chewing patterns.

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Year:  2017        PMID: 28463209     DOI: 10.1109/JBHI.2017.2698523

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  13 in total

Review 1.  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

2.  Valuing the Diversity of Research Methods to Advance Nutrition Science.

Authors:  Richard D Mattes; Sylvia B Rowe; Sarah D Ohlhorst; Andrew W Brown; Daniel J Hoffman; DeAnn J Liska; Edith J M Feskens; Jaapna Dhillon; Katherine L Tucker; Leonard H Epstein; Lynnette M Neufeld; Michael Kelley; Naomi K Fukagawa; Roger A Sunde; Steven H Zeisel; Anthony J Basile; Laura E Borth; Emahlea Jackson
Journal:  Adv Nutr       Date:  2022-08-01       Impact factor: 11.567

3.  Accelerometer-Based Detection of Food Intake in Free-living Individuals.

Authors:  Muhammad Farooq; Edward Sazonov
Journal:  IEEE Sens J       Date:  2018-03-08       Impact factor: 3.301

Review 4.  Future Directions for Integrative Objective Assessment of Eating Using Wearable Sensing Technology.

Authors:  Andy Skinner; Zoi Toumpakari; Christopher Stone; Laura Johnson
Journal:  Front Nutr       Date:  2020-07-02

5.  Sensor-Based Smart Clothing for Women's Menopause Transition Monitoring.

Authors:  Jie Luo; Aihua Mao; Zhongwen Zeng
Journal:  Sensors (Basel)       Date:  2020-02-17       Impact factor: 3.576

Review 6.  How Important Is Eating Rate in the Physiological Response to Food Intake, Control of Body Weight, and Glycemia?

Authors:  Georgia Argyrakopoulou; Stamatia Simati; George Dimitriadis; Alexander Kokkinos
Journal:  Nutrients       Date:  2020-06-10       Impact factor: 5.717

Review 7.  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

8.  Retrieval and Timing Performance of Chewing-Based Eating Event Detection in Wearable Sensors.

Authors:  Rui Zhang; Oliver Amft
Journal:  Sensors (Basel)       Date:  2020-01-20       Impact factor: 3.576

9.  Counting Bites With Bits: Expert Workshop Addressing Calorie and Macronutrient Intake Monitoring.

Authors:  Nabil Alshurafa; Annie Wen Lin; Fengqing Zhu; Roozbeh Ghaffari; Josiah Hester; Edward Delp; John Rogers; Bonnie Spring
Journal:  J Med Internet Res       Date:  2019-12-04       Impact factor: 5.428

10.  DynDSE: Automated Multi-Objective Design Space Exploration for Context-Adaptive Wearable IoT Edge Devices.

Authors:  Giovanni Schiboni; Juan Carlos Suarez; Rui Zhang; Oliver Amft
Journal:  Sensors (Basel)       Date:  2020-10-27       Impact factor: 3.847

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