[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3410531.3414309acmconferencesArticle/Chapter ViewAbstractPublication PagesubicompConference Proceedingsconference-collections
short-paper

Intraoral temperature and inertial sensing in automated dietary assessment: a feasibility study

Published: 04 September 2020 Publication History

Abstract

Recent advances in Automated Dietary Monitoring (ADM) with wearables have shown promising results in eating detection in naturalistic environments. However, determining what an individual is consuming remains a significant challenge. In this paper, we present results of a food type classification study based on a sub-centimeter scale wireless intraoral sensor that continuously measures temperature and jawbone movement. We explored the feasibility of classifying nine different types of foods into five classes based on their water-content and typical serving temperature in a controlled environment (n=4). We demonstrated that the system can classify foods into five classes with a weighted accuracy of 77.5% using temperature-derived features only and with a weighted accuracy of 85.0% using both temperature- and acceleration-derived features. Despite the limitations of our study, these results are encouraging and suggest that intraoral computing might be a viable direction for ADM in the future.

References

[1]
Oliver Amft, Mathias Stäger, Paul Lukowicz, and Gerhard Tröster. 2005. Analysis of chewing sounds for dietary monitoring. In International Conference on Ubiquitous Computing. Springer, 56--72.
[2]
Abdelkareem Bedri, Diana Li, Rushil Khurana, Kunal Bhuwalka, and Mayank Goel. 2020. FitByte: Automatic Diet Monitoring in Unconstrained Situations Using Multimodal Sensing on Eyeglasses. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1--12.
[3]
Abdelkareem Bedri, Richard Li, Malcolm Haynes, Raj Prateek Kosaraju, Ishaan Grover, Temiloluwa Prioleau, Min Yan Beh, Mayank Goel, Thad Starner, and Gregory Abowd. 2017. EarBit: Using Wearable Sensors to Detect Eating Episodes in Unconstrained Environments. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 37.
[4]
JE Choi, C Loke, JN Waddell, KM Lyons, JA Kieser, and M Farella. 2015. Continuous measurement of intra-oral p H and temperature: development, validation of an appliance and a pilot study. Journal of oral rehabilitation 42, 8 (2015), 563--570.
[5]
Keum San Chun, Sarnab Bhattacharya, and Edison Thomaz. 2018. Detecting Eating Episodes by Tracking Jawbone Movements with a Non-Contact Wearable Sensor. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (2018), 4.
[6]
Keum San Chun, Hyoyoung Jeong, Rebecca Adaimi, and Edison Thomaz. 2020. Eating Episode Detection with Jawbone-Mounted Inertial Sensing. Engineering in Medicine and Biology Conference (2020).
[7]
Ilka Dove. 2014. Analysis of radio propagation inside the human body for in-body localization purposes. Master's thesis. University of Twente.
[8]
Hongsheng He, Fanyu Kong, and Jindong Tan. 2015. Dietcam: Multiview food recognition using a multikernel svm. IEEE journal of biomedical and health informatics 20, 3 (2015), 848--855.
[9]
Christine M Hunter, Alan L Peterson, Lisa M Alvarez, Walker C Poston, Antoinette R Brundige, C Keith Haddock, David L Van Brunt, and John P Foreyt. 2008. Weight management using the internet: a randomized controlled trial. American journal of preventive medicine 34, 2 (2008), 119--126.
[10]
D R Jacobs. 2012. Challenges in research in nutritional epidemiology. Nutritional Health (2012), 29--42.
[11]
Cheng-Yuan Li, Yen-Chang Chen, Wei-Ju Chen, Polly Huang, and Hao-hua Chu. 2013. Sensor-embedded teeth for oral activity recognition. In Proceedings of the 2013 international symposium on wearable computers. ACM, 41--44.
[12]
Steven W Lichtman, Krystyna Pisarska, Ellen Raynes Berman, Michele Pestone, Hillary Dowling, Esther Offenbacher, Hope Weisel, Stanley Heshka, Dwight E Matthews, and Steven B Heymsfield. 1992. Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. New England Journal of Medicine 327, 27 (1992), 1893--1898.
[13]
Faidon Magkos and Mary Yannakoulia. 2003. Methodology of dietary assessment in athletes: concepts and pitfalls. Current Opinion in Clinical Nutrition & Metabolic Care 6, 5 (2003), 539--549.
[14]
K B Michels. 2001. A renaissance for measurement error. International journal of epidemiology 30, 3 (June 2001), 421--422.
[15]
Mark Mirtchouk, Christopher Merck, and Samantha Kleinberg. 2016. Automated estimation of food type and amount consumed from body-worn audio and motion sensors. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 451--462.
[16]
Rachel J Moore, Jeffrey TF Watts, James AA Hood, and David J Burritt. 1999. Intraoral temperature variation over 24 hours. The European Journal of Orthodontics 21, 3 (1999), 249--261.
[17]
Seon-Joo Park, Akmaljon Palvanov, Chang-Ho Lee, Nanoom Jeong, Young-Im Cho, and Hae-Jeung Lee. 2019. The development of food image detection and recognition model of Korean food for mobile dietary management. Nutrition Research and Practice 13, 6 (2019), 521--528.
[18]
Barry M Popkin, Kristen E D'Anci, and Irwin H Rosenberg. 2010. Water, hydration, and health. Nutrition reviews 68, 8 (2010), 439--458.
[19]
Giovanni Schiboni and Oliver Amft. 2018. Automatic Dietary Monitoring Using Wearable Accessories. In Seamless Healthcare Monitoring. Springer, 369--412.
[20]
Jee-Seon Shim, Kyungwon Oh, and Hyeon Chang Kim. 2014. Dietary assessment methods in epidemiologic studies. Epidemiology and health 36 (2014).
[21]
Edison Thomaz, Irfan Essa, and Gregory D Abowd. 2015. A practical approach for recognizing eating moments with wrist-mounted inertial sensing. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 1029--1040.
[22]
Peter Tseng, Bradley Napier, Logan Garbarini, David L Kaplan, and Fiorenzo G Omenetto. 2018. Functional, RF-Trilayer Sensors for Tooth-Mounted, Wireless Monitoring of the Oral Cavity and Food Consumption. Advanced Materials 30, 18 (2018), 1703257.
[23]
Sajith Vellappally, Abdulaziz A Al Kheraif, Sukumaran Anil, and Ashraf A Wahba. 2019. IoT medical tooth mounted sensor for monitoring teeth and food level using bacterial optimization along with adaptive deep learning neural network. Measurement 135 (2019), 672--677.
[24]
Shibo Zhang, Yuqi Zhao, Dzung Tri Nguyen, Runsheng Xu, Sougata Sen, Josiah Hester, and Nabil Alshurafa. 2019. NeckSense: A Multi-Sensor Necklace for Detecting Eating Activities in Free-Living Conditions. arXiv preprint arXiv:1911.07179 (2019).
[25]
ZPower. 2019. Microbatteries. https://www.zpowerbattery.com/rechargeable-microbatteries/ Accessed: 2020-04-29.

Cited By

View all
  • (2024)Densor: An Intraoral Battery-Free Sensing PlatformProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997468:4(1-30)Online publication date: 21-Nov-2024
  • (2024)Functional Now, Wearable Later: Examining the Design Practices of Wearable TechnologistsProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676615(71-81)Online publication date: 5-Oct-2024
  • (2023)Passive Sensors for Detection of Food IntakeEncyclopedia of Sensors and Biosensors10.1016/B978-0-12-822548-6.00086-8(218-234)Online publication date: 2023
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
ISWC '20: Proceedings of the 2020 ACM International Symposium on Wearable Computers
September 2020
107 pages
ISBN:9781450380775
DOI:10.1145/3410531
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 September 2020

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. automated dietary monitoring
  2. human activity recognition
  3. intraoral sensing
  4. intraoral temperature

Qualifiers

  • Short-paper

Conference

UbiComp/ISWC '20

Acceptance Rates

Overall Acceptance Rate 38 of 196 submissions, 19%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)15
  • Downloads (Last 6 weeks)1
Reflects downloads up to 12 Dec 2024

Other Metrics

Citations

Cited By

View all
  • (2024)Densor: An Intraoral Battery-Free Sensing PlatformProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997468:4(1-30)Online publication date: 21-Nov-2024
  • (2024)Functional Now, Wearable Later: Examining the Design Practices of Wearable TechnologistsProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676615(71-81)Online publication date: 5-Oct-2024
  • (2023)Passive Sensors for Detection of Food IntakeEncyclopedia of Sensors and Biosensors10.1016/B978-0-12-822548-6.00086-8(218-234)Online publication date: 2023
  • (2022)Enhancing Nutrition Care Through Real-Time, Sensor-Based Capture of Eating Occasions: A Scoping ReviewFrontiers in Nutrition10.3389/fnut.2022.8529849Online publication date: 2-May-2022
  • (2022)Applications and Techniques for Fast Machine Learning in ScienceFrontiers in Big Data10.3389/fdata.2022.7874215Online publication date: 12-Apr-2022
  • (2022)Understanding People's Perceptions of Approaches to Semi-Automated Dietary MonitoringProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35502886:3(1-27)Online publication date: 7-Sep-2022
  • (2022)Towards Socially Acceptable Food Type Recognition2022 18th International Conference on Mobility, Sensing and Networking (MSN)10.1109/MSN57253.2022.00110(671-678)Online publication date: Dec-2022
  • (2021)ISWC 2020IEEE Pervasive Computing10.1109/MPRV.2020.304411920:1(45-49)Online publication date: 1-Jan-2021
  • (2021)TeethVib: Monitoring Teeth Functional Occlusion Through Retainer Vibration Sensing2021 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)10.1109/CHASE52844.2021.00018(92-96)Online publication date: Dec-2021

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media