A New Method for Measuring Meal Intake in Humans Via Automated Wrist Motion Tracking

Overview

Journal Appl Psychophysiol Biofeedback

Publisher Springer

Date 2012 Apr 11

PMID 22488204

Citations 63

Authors

Yujie Dong

Adam Hoover

Jenna Scisco

Eric Muth

Affiliations

Soon will be listed here.

Abstract

Measuring the energy intake (kcal) of a person in day-to-day life is difficult. The best laboratory tool achieves 95 % accuracy on average, while tools used in daily living typically achieve 60-80 % accuracy. This paper describes a new method for measuring intake via automated tracking of wrist motion. Our method uses a watch-like device with a micro-electro-mechanical gyroscope to detect and record when an individual has taken a bite of food. Two tests of the accuracy of our device in counting bites found that our method has 94 % sensitivity in a controlled meal setting and 86 % sensitivity in an uncontrolled meal setting, with one false positive per every 5 bites in both settings. Preliminary data from daily living indicates that bites measured by the device are positively related to caloric intake illustrating the potential of the device to monitor energy intake. Future research should seek to further explore the relationship between bites taken and kilocalories consumed to validate the device as an automated measure of energy intake.

Citing Articles

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References

Beasley J, Riley W, Jean-Mary J . Accuracy of a PDA-based dietary assessment program. Nutrition. 2005; 21(6):672-7. DOI: 10.1016/j.nut.2004.11.006. View

Flegal K, Carroll M, Ogden C, Curtin L . Prevalence and trends in obesity among US adults, 1999-2008. JAMA. 2010; 303(3):235-41. DOI: 10.1001/jama.2009.2014. View

Six B, Schap T, Zhu F, Mariappan A, Bosch M, Delp E . Evidence-based development of a mobile telephone food record. J Am Diet Assoc. 2010; 110(1):74-9. PMC: 3042797. DOI: 10.1016/j.jada.2009.10.010. View

Glanz K, Brug J, van Assema P . Are awareness of dietary fat intake and actual fat consumption associated?--a Dutch-American comparison. Eur J Clin Nutr. 1997; 51(8):542-7. DOI: 10.1038/sj.ejcn.1600442. View

Champagne C, Bray G, Kurtz A, Monteiro J, Tucker E, Volaufova J . Energy intake and energy expenditure: a controlled study comparing dietitians and non-dietitians. J Am Diet Assoc. 2002; 102(10):1428-32. DOI: 10.1016/s0002-8223(02)90316-0. View

Zhu F, Mariappan A, Boushey C, Kerr D, Lutes K, Ebert D . Technology-Assisted Dietary Assessment. Proc SPIE Int Soc Opt Eng. 2011; 6814:681411. PMC: 3224859. DOI: 10.1117/12.778616. View

Burke L, Wang J, Sevick M . Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc. 2010; 111(1):92-102. PMC: 3268700. DOI: 10.1016/j.jada.2010.10.008. View

McCabe-Sellers B . Advancing the art and science of dietary assessment through technology. J Am Diet Assoc. 2010; 110(1):52-4. DOI: 10.1016/j.jada.2009.10.014. View

Sazonov E, Schuckers S, Lopez-Meyer P, Makeyev O, Sazonova N, Melanson E . Non-invasive monitoring of chewing and swallowing for objective quantification of ingestive behavior. Physiol Meas. 2008; 29(5):525-41. PMC: 2582220. DOI: 10.1088/0967-3334/29/5/001. View

10.

Williamson D, Allen H, Martin P, Alfonso A, Gerald B, Hunt A . Comparison of digital photography to weighed and visual estimation of portion sizes. J Am Diet Assoc. 2003; 103(9):1139-45. DOI: 10.1016/s0002-8223(03)00974-x. View

11.

Black A, Cole T . Within- and between-subject variation in energy expenditure measured by the doubly-labelled water technique: implications for validating reported dietary energy intake. Eur J Clin Nutr. 2000; 54(5):386-94. DOI: 10.1038/sj.ejcn.1600970. View

12.

Lopez-Meyer P, Makeyev O, Schuckers S, Melanson E, Neuman M, Sazonov E . Detection of food intake from swallowing sequences by supervised and unsupervised methods. Ann Biomed Eng. 2010; 38(8):2766-74. PMC: 2901415. DOI: 10.1007/s10439-010-0019-1. View

13.

Zhu F, Bosch M, Woo I, Kim S, Boushey C, Ebert D . The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation. IEEE J Sel Top Signal Process. 2010; 4(4):756-766. PMC: 2941896. DOI: 10.1109/JSTSP.2010.2051471. View

14.

Kissileff H, Klingsberg G, Van Itallie T . Universal eating monitor for continuous recording of solid or liquid consumption in man. Am J Physiol. 1980; 238(1):R14-22. DOI: 10.1152/ajpregu.1980.238.1.R14. View

15.

Martin C, Anton S, York-Crowe E, Heilbronn L, VanSkiver C, Redman L . Empirical evaluation of the ability to learn a calorie counting system and estimate portion size and food intake. Br J Nutr. 2007; 98(2):439-44. DOI: 10.1017/S0007114507708802. View

16.

Schoeller D . Measurement of energy expenditure in free-living humans by using doubly labeled water. J Nutr. 1988; 118(11):1278-89. DOI: 10.1093/jn/118.11.1278. View

17.

Wing R, Phelan S . Long-term weight loss maintenance. Am J Clin Nutr. 2005; 82(1 Suppl):222S-225S. DOI: 10.1093/ajcn/82.1.222S. View

18.

Thompson F, Subar A, Loria C, Reedy J, Baranowski T . Need for technological innovation in dietary assessment. J Am Diet Assoc. 2010; 110(1):48-51. PMC: 2823476. DOI: 10.1016/j.jada.2009.10.008. View

19.

Yon B, Johnson R, Harvey-Berino J, Gold B . The use of a personal digital assistant for dietary self-monitoring does not improve the validity of self-reports of energy intake. J Am Diet Assoc. 2006; 106(8):1256-9. DOI: 10.1016/j.jada.2006.05.004. View

20.

Muller M, Bosy-Westphal A, Krawczak M . Genetic studies of common types of obesity: a critique of the current use of phenotypes. Obes Rev. 2010; 11(8):612-8. DOI: 10.1111/j.1467-789X.2010.00734.x. View