Your institute does not have access to this article
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
World Health Organization. Non-communicable diseases. 2018. https://www.who.int/nmh/publications/ncd-profiles-2018/en/.
Illner AK, Freisling H, Boeing H, Huybrechts I, Crispim SP, Slimani N. Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology. Int J Epidemiol. 2012;41:1187–203.
Thompson FE, Subar AF. Dietary assessment methodology. 4th edn. Nutrition in the Prevention and Treatment of Disease. Elsevier Inc.; 2017;5–48. https://doi.org/10.1016/B978-0-12-802928-2.00001-1.
Herrera MCA, Chan CB. Narrative review of new methods for assessing food and energy intake. Nutrients. 2018;10:1–19.
Doulah A, McCrory MA, Higgins JA, S E. A systematic review of technology-driven methodologies for estimation of energy intake. IEEE Access. 2019;7:49653–68.
Cade JE. Measuring diet in the 21st century: use of new technologies. Proc Nutr Soc. 2017;76:276–82.
Briggs MA, Rumbold PLS, Cockburn E, Russell M, Stevenson EJ. Agreement between two methods of dietary data collection in male adolescent academy-level soccer players. Nutrients. 2015;7:5948–60.
Subar AF, Freedman LS, Tooze JA, Kirkpatrick SI, Boushey C, Neuhouser ML, et al. Addressing current criticism regarding the value of self-report dietary data. J Nutr. 2015;145:2639–45.
Boushey CJ, Spoden M, Zhu FM, Delp EJ, Kerr DA. New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proc Nutr Soc. 2017;76:283–94.
Shim JS, Oh K, Kim HC. Dietary assessment methods in epidemiologic studies. Epidemiol Health. 2014;36:e2014009
Thompson FE, Dixit-Joshi S, Potischman N, Dodd KW, Kirkpatrick SI, Kushi LH, et al. Comparison of interviewer-administered and automated self-administered 24-hour dietary recalls in 3 diverse integrated health systems. Am J Epidemiol. 2015;181:970–8.
Beasley J, Riley WT, Jean-Mary J. Accuracy of a PDA-based dietary assessment program. Nutrition. 2005;21:672–7.
Beasley JM, Riley WT, Davis A, Singh J. Evaluation of a PDA-based dietary assessment and intervention program: a randomized controlled trial. J Am Coll Nutr. 2008;27:280–6.
Fowles ER, Gentry B. The feasibility of personal digital assistants (PDAs) to collect dietary intake data in low-income pregnant women. J Nutr Educ Behav. 2008;40:374–7.
Fukuo W, Yoshiuchi K, Ohashi K, Togashi H, Sekine R, Kikuchi H, et al. Development of a hand-held personal digital assistant-based food diary with food photographs for Japanese subjects. J Am Diet Assoc. 2009;109:1232–6. https://doi.org/10.1016/j.jada.2009.04.013.
Atienza AA, King AC, Oliveira BM, Ahn DK, Gardner CD. Using hand-held computer technologies to improve dietary intake. Am J Prev Med. 2008;34:514–8.
Labonté MÈ, Cyr A, Baril-Gravel L, Royer MM, Lamarche B. Validity and reproducibility of a web-based, self-administered food frequency questionnaire. Eur J Clin Nutr. 2012;66:166–73.
Kupis J, Johnson S, Hallihan G, Olstad DL. Assessing the usability of the automated self-administered dietary assessment tool (Asa24) among low-income adults. Nutrients. 2019;11:132.
Jia W, Li Y, Qu R, Baranowski T, Burke LE, Zhang H, et al. Automatic food detection in egocentric images using artificial intelligence technology. Public Health Nutr. 2019;22:1168–79.
Dong Y, Scisco J, Wilson M, Muth E, Hoover A. Detecting periods of eating during free-living by tracking wrist motion. IEEE J Biomed Heal Inform. 2014;18:1253–60.
Makeyev O, Lopez-Meyer P, Schuckers S, Besio W, Sazonov E. Automatic food intake detection based on swallowing sounds. Biomed Signal Process Control. 2012;7:649–56.
Fontana JM, Higgins JA, Schuckers SC, Bellisle F, Pan Z, Melanson EL, et al. Energy intake estimation from counts of chews and swallows. Appetite. 2015;85:14–21.
Farooq M, Doulah A, Parton J, McCrory MA, Higgins JA, Sazonov E. Validation of sensor-based food intake detection by multicamera video observation in an unconstrained environment. Nutrients. 2019;11:609.
Gemming L, Utter J, Ni Mhurchu C. Image-assisted dietary assessment: a systematic review of the evidence. J Acad Nutr Diet. 2015;115:64–77.
Rollo ME, Ash S, Lyons-Wall P, Russell AW. Evaluation of a mobile phone image-based dietary assessment method in adults with type 2 diabetes. Nutrients. 2015;7:4897–910.
Dong Y, Hoover A, Scisco J, Muth E. A new method for measuring meal intake in humans via automated wrist motion tracking. Appl Psychophysiol Biofeedback. 2012;37:205–15.
Scisco JL, Muth ER, Hoover AW. Examining the utility of a bite-count-based measure of eating activity in free-living human beings. J Acad Nutr Diet. 2014;114:464–9. https://doi.org/10.1016/j.jand.2013.09.017.
Salley JN, Hoover AW, Wilson ML, Muth ER. Comparison between human and bite-based methods of estimating caloric intake. J Acad Nutr Diet. 2016;116:1568–77. https://doi.org/10.1016/j.jand.2016.03.007.
Eldridge AL, Piernas C, Illner AK, Gibney MJ, Gurinović MA, de Vries JHM, et al. Evaluation of new technology-based tools for dietary intake assessment—an ilsi europe dietary intake and exposure task force evaluation. Nutrients. 2019;11:55.
Sharp DB, Allman-Farinelli M. Feasibility and validity of mobile phones to assess dietary intake. Nutrition. 2014;30:1257–66. https://doi.org/10.1016/j.nut.2014.02.020.
Stumbo PJ. New technology in dietary assessment: a review of digital methods in improving food record accuracy. Proc Nutr Soc. 2013;72:70–6.
Martin CK, Han H, Coulon SM, Allen HR, Champagne CM, Anton SD. A novel method to remotely measure food intake of free-living individuals in real time: the remote food photography method. Br J Nutr. 2009;101:446–56.
Martin CK, Correa JB, Han H, Allen HR, Rood JC, Champagne CM, et al. Validity of the remote food photography method (RFPM) for estimating energy and nutrient intake in near real-time. Obesity. 2012;20:891–9. https://doi.org/10.1038/oby.2011.344/nature06264.
Kawano Y, Yanai K. FoodCam: a real-time food recognition system on a smartphone. Multimed Tools Appl. 2015;74:5263–87.
Pettitt C, Liu J, Kwasnicki RM, Yang GZ, Preston T, Frost G. A pilot study to determine whether using a lightweight, wearable micro-camera improves dietary assessment accuracy and offers information on macronutrients and eating rate. Br J Nutr. 2016;115:160–7.
Fang S, Shao Z, Kerr DA, Boushey CJ, Zhu F. An end-to-end image-based automatic food energy estimation technique based on learned energy distribution images: Protocol and methodology. Nutrients. 2019;11:877.
Sun M, Burke LE, Mao ZH, Chen Y, Chen HC, Bai Y, et al. Ebutton: A wearable computer for health monitoring and personal assistance. Proc Des Autom Conf. 2014;2014:1–6.
Jishiqi. Jishiqi Intelligent Tableware. http://www.jishiqi.net.
Arens-Volland AG, Spassova L, Bohn T. Promising approaches of computer-supported dietary assessment and management-current research status and available applications. Int J Med Inf. 2015;84:997–1008. https://doi.org/10.1016/j.ijmedinf.2015.08.006.
NetEase. Huawei releases creative video: even Marmot is using Mate 20’s AI calorie recognition. NetEase Technology. 2018. http://tech.163.com/18/1204/16/E26R4SP600097U7H.html.
PConline. Bixby gains new skills: evaluating the calorie content of food at a glance. PConline. 2018. https://pcedu.pconline.com.cn/1067/10670468.html.
Amoutzopoulos B, Steer T, Roberts C, Cade JE, Boushey CJ, Collins CE, et al. Traditional methods v. new technologies - dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisban. J Nutr Sci. 2018;7:1–10.
Maimaiti M, Zhao X, Jia M, Ru Y, Zhu S. How we eat determines what we become: opportunities and challenges brought by food delivery industry in a changing world in China. Eur J Clin Nutr. 2018;72:1282–6.
Timon CM, Van Den Barg R, Blain RJ, Kehoe L, Evans K, Walton J, et al. A review of the design and validation of web- and computer-based 24-h dietary recall tools. Nutr Res Rev. 2016;29:268–80.
Boushey CJ, Kerr DA, Wright J, Lutes KD, Ebert DS, Delp EJ. Use of technology in children’s dietary assessment. Eur J Clin Nutr. 2009;63:S50–7.
Hutchesson MJ, Rollo ME, Callister R, Collins CE. Self-monitoring of dietary intake by young women: online food records completed on computer or smartphone are as accurate as paper-based food records but more acceptable. J Acad Nutr Diet. 2015;115:87–94. https://doi.org/10.1016/j.jand.2014.07.036.
Daugherty BL, Schap TRE, Ettienne-Gittens R, Zhu FM, Bosch M, Delp EJ, et al. Novel technologies for assessing dietary intake: evaluating the usability of a mobile telephone food record among adults and adolescents. J Med Internet Res. 2012;14:156–67.
Dao MC, Subar AF, Warthon-medina M, Cade J, Golley RK, Forouhi NG, et al. Dietary assessment toolkits: an overview. Public Health Nutr. 2019;22:404–18. Europe PMC Funders Group.
Tellspec Inc. Tellspec Enterprise Scanner. https://www.who.int/nmh/publications/ncd-profiles-2018/en/.
This work was supported by the grant from the Cyrus Tang Foundation (419600-11102), with additional grants from the China Medical Board (CMB) Collaborating Program (15-216 and 12-108).
Conflict of interest
The authors declare that they have no conflict of interest.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Zhao, X., Xu, X., Li, X. et al. Emerging trends of technology-based dietary assessment: a perspective study. Eur J Clin Nutr 75, 582–587 (2021). https://doi.org/10.1038/s41430-020-00779-0