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MySnapFoodLog: Culturally Sensitive Food Photo-Logging App for Dietary Biculturalism Studies

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Book cover Advances in Visual Computing (ISVC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12510))

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Abstract

It is believed that immigrants to the U.S. have increased rates of chronic diseases due to their adoption of the Western diet. There is a need to better understand the dietary intake of these immigrants. Tracking food consumption can be easily done by using a food app, but there is currently no culturally-appropriate food tracking app that is relatively easy for participants and the research community to use. The MySnapFoodLog app was developed using the cross-platform Flutter framework to track users’ food consumption with the goal of using AI to recognize Filipino foods and determine if a meal is healthy or unhealthy. A pilot study demonstrates the feasibility of the app alpha release and the need for further data collection and training to improve the Filipino food recognition system.

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References

  1. Isolate class - dart:isolate class - Dart API, November 2019. https://api.dartlang.org/stable/2.6.1/dart-isolate/Isolate-class.html

  2. Technical overview - Flutter, November 2019. https://flutter.dev/docs/resources/technical-overview

  3. ML Kit for Firebase, July 2020. https://firebase.google.com/docs/ml-kit

  4. TensorFlow, July 2020. https://www.tensorflow.org/

  5. Azar, K.M.J., Chen, E., Holland, A.T., Palaniappan, L.P.: Festival foods in the immigrant diet. J. Immigrant Minority Health 15(5), 953–960 (2013). https://doi.org/10.1007/s10903-012-9705-4

  6. Brug, J., Glanz, K., Kok, G.: The relationship between self-efficacy, attitudes, intake compared to others, consumption, and stages of change related to fruit and vegetables. Am. J. Health Promotion 12(1), 25–30 (1997). https://doi.org/10.4278/0890-1171-12.1.25, pMID: 10170431

  7. Cordeiro, F., et al.: Barriers and negative nudges: exploring challenges in food journaling. In: Proceedings of ACM Conference on Human Factors in Computing Systems, pp. 1159–1162. ACM, Seoul, Republic of Korea, April 2015. https://doi.org/10.1145/2702123.2702155

  8. Dela Cruz, F.A., Galang, C.B.: The illness beliefs, perceptions, and practices of Filipino Americans with hypertension. J. Am. Acad. Nurse Practitioners 20(3), 118–127 (2008). https://doi.org/10.1111/j.1745-7599.2007.00301.x

  9. Huang, J., et al.: Speed/accuracy trade-offs for modern convolutional object detectors. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3296–3297, July 2017. https://doi.org/10.1109/CVPR.2017.351

  10. Karlsson, M.: Simple app for balanced eating | see how you eat coach 80/20 diet rule app, November 2019. https://seehowyoueat.com/

  11. Karlsson, M.: Bitesnap - photo food journal, June 2020. https://getbitesnap.com/

  12. Lin, T.Y., Dollar, P.: MS COCO API (2016). https://github.com/pdollar/coco

  13. Lin, T., et al.: Microsoft COCO: common objects in context. CoRR abs/1405.0312 (2014). http://arxiv.org/abs/1405.0312

  14. Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21–37. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46448-0_2

    Chapter  Google Scholar 

  15. Mummah, S.A., Mathur, M., King, A.C., Gardner, C.D., Sutton, S.: Mobile technology for vegetable consumption: a randomized controlled pilot study in overweight adults. JMIR mHealth uHealth 4(2), e51 (2016). https://doi.org/10.2196/mhealth.5146, http://mhealth.jmir.org/2016/2/e51/

  16. O’Loughlin, G., et al.: Using a wearable camera to increase the accuracy of dietary analysis. Am. J. Preventive Med. 44(3), 297–301 (2013). https://doi.org/10.1016/j.amepre.2012.11.007, http://www.sciencedirect.com/science/article/pii/S074937971200863X

  17. Rothman, A.J., Sheeran, P., Wood, W.: Reflective and automatic processes in the initiation and maintenance of dietary change. Ann. Behav. Med. 38(suppl\(\_\)1), s4–s17 (2009). https://doi.org/10.1007/s12160-009-9118-3

  18. Salmenius-Suominen, H., Lehtovirta, M., Vepsäläinen, H., Konttinen, H., Erkkola, M.: Visual food diary for social support, dietary changes and weight loss. iproc 2(1), e38 (2016). https://doi.org/10.2196/iproc.6135, http://www.iproc.org/2016/1/e38/

  19. Serafica, R., Angosta, A.D.: Acculturation and changes in body mass index, waist circumference, and waist-hip ratio among Filipino Americans with hypertension. J. Am. Soc. Hypertension 10(9), 733–740 (2016). https://doi.org/10.1016/j.jash.2016.07.002, http://www.sciencedirect.com/science/article/pii/S1933171116304430

  20. Serafica, R., Knurick, J., Morris, B.T.: Concept analysis of dietary biculturalism in Filipino immigrants within the context of cardiovascular risk. Nursing Forum 53(2), 241–247 (2018). https://doi.org/10.1111/nuf.12232, https://onlinelibrary.wiley.com/doi/abs/10.1111/nuf.12232

  21. Serafica, R., Lukkahatai, N., Morris, B.T., Webber, K.: The use of social media and mEMA technology in comparing compliance rate among users. Asian/Pacific Island Nurs. J. 3(4) (2019). https://doi.org/10.31372/20180304.1019, https://dx.doi.org/10.31372%2F20180304.1019

  22. Serafica, R.C., Lane, S.H., Ceria-Ulep, C.D.: Dietary acculturation and predictors of anthropometric indicators among Filipino Americans. SAGE Open 3(3) (2013). https://doi.org/10.1177/2158244013495543

  23. Sodjinou, R., Agueh, V., Fayomi, B., Delisle, H.: Dietary patterns of urban adults in Benin: relationship with overall diet quality and socio-demographic characteristics. Eur. J. Clin. Nutr. 63, 222–228 (2009). https://doi.org/10.1038/sj.ejcn.1602906

  24. Webber, K., Serafica, R., Morris, B., Warner, D., Cooper, T.: Dietary habits and chronic disease risk of Filipino immigrants in Las Vegas, NV. In: Annual Meeting of The Obesity Society. Las Vegas, NV (Nov 2019), poster

    Google Scholar 

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Acknowledgment

Student pilot data coders Denise Warner, Tanya Cooper, and Natasha Lishing. Alpha release developers Aditya Rajuladevi, Jenny Yao, Yuria Mann, and Xinyu Wang.

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Authors and Affiliations

  1. University of Nevada, Las Vegas, Las Vegas, NV, 89154, USA

    Paul Stanik III, Brendan Tran Morris & Reimund Serafica

  2. University of Arkansas, Fayetteville, AR, 72701, USA

    Kelly Harmon Webber

Authors
  1. Paul Stanik III
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  2. Brendan Tran Morris
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  3. Reimund Serafica
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  4. Kelly Harmon Webber
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Corresponding author

Correspondence to Paul Stanik III .

Editor information

Editors and Affiliations

  1. University of Nevada Reno, Reno, NV, USA

    George Bebis

  2. Stony Brook University, Stony Brook, NY, USA

    Zhaozheng Yin

  3. Drexel University, Philadelphia, PA, USA

    Edward Kim

  4. RWTH Aachen University, Aachen, Germany

    Jan Bender

  5. University of Edinburgh, Edinburgh, UK

    Kartic Subr

  6. IBM Research – Cambridge, Cambridge, MA, USA

    Bum Chul Kwon

  7. University of Waterloo, Waterloo, ON, Canada

    Jian Zhao

  8. Graz University of Technology, Graz, Austria

    Denis Kalkofen

  9. The Hong Kong Polytechnic University, Hong Kong, Hong Kong

    George Baciu

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Stanik III, P., Morris, B.T., Serafica, R., Webber, K.H. (2020). MySnapFoodLog: Culturally Sensitive Food Photo-Logging App for Dietary Biculturalism Studies. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science(), vol 12510. Springer, Cham. https://doi.org/10.1007/978-3-030-64559-5_37

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  • DOI: https://doi.org/10.1007/978-3-030-64559-5_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64558-8

  • Online ISBN: 978-3-030-64559-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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