Author(s):

  • Lucas M. Silva
  • Daniel A. Epstein

Abstract:

Journaling of consumed foods through digital devices is a popular self-tracking strategy for weight loss and eating mindfulness. Research has explored modalities, like photos and open-ended text and voice descriptions, to make journaling less burdensome and more descriptive than traditional barcode and database searches. However, less is known about how people prefer to journal foods when less constrained by limitations of databases, natural language processing, and image recognition. We deployed a food journal prototype supporting varied devices and input modalities, which 15 participants used to journal 1008 food logs over two weeks. Participants had diverse strategies for indicating what and how much they ate, varying from ambiguous foods to specifying varieties and using different measurements for clarifying amount. Some strategies were interpretable by natural language food identification and image classification services, while others point to open research questions. We finally discuss opportunities for accounting for variance in food journaling.

Documentation:

https://doi.org/10.1145/3461778.3462145

References:
  1. 7 Best Image Recognition APIs. Retrieved 10 February, 2021 from https://nordicapis.com/7-best-image-recognition-apis/
  2. Sofiane Abbar, Yelena Mejova, and Ingmar Weber. (2015). You Tweet What You Eat: Studying Food Consumption Through Twitter. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2015), 3197–3206. http://doi.org/10.1145/2702123.2702153
  3. Deemah Alqahtani, Caroline Jay, and Markel Vigo. (2020). The Role of Uncertainty as a Facilitator to Reflection in Self-Tracking. Proceedings of the Conference on Designing Interactive Systems (DIS 2020), 1807–1818. http://doi.org/10.1145/3357236.3395448
  4. Amazon Rekognition. Retrieved 10 February, 2021 from https://aws.amazon.com/rekognition/
  5. Oliver Amft, Mathias Stäger, Paul Lukowicz, and Gerhard Tröster. (2005). Analysis of Chewing Sounds for dietary monitoring. Proceedings of the International Conference on Ubiquitous Computing (Ubicomp 2005), 56–72. http://doi.org/10.1007/11551201_4
  6. Adrienne H. Andrew, Gaetano Borriello, and James Fogarty. (2013). Simplifying Mobile Phone Diaries: Design and Evaluation of a Food Index-Based Nutrition Diary. Proceedings of the International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth 2013), 260–263. http://doi.org/bbkk
  7. Amid Ayobi, Paul Marshall, and Anna L. Cox. (2020). Trackly: A Customisable and Pictorial Self-Tracking App to Support Agency in Multiple Sclerosis Self-Care. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2020), 1–15. http://doi.org/10.1145/3313831.3376809
  8. Barcode Lookup. Retrieved 10 February, 2021 from https://www.barcodelookup.com/
  9. Elizabeth Barrett-Connor. (1991). Nutrition epidemiology: How do we know what they ate? American Journal of Clinical Nutrition, 182–189. http://doi.org/10.1093/ajcn/54.1.182s
  10. Eric P.S. Baumer, Sherri Jean Katz, Jill E. Freeman, Phil Adams, Amy L. Gonzales, John Pollak, Daniela Retelny, Jeff Niederdeppe, Christine M. Olson, and Geri K. Gay. (2012). Prescriptive Persuasion and Open-Ended Social Awareness: Expanding the Design Space of Mobile Health. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2012), 475–484. http://doi.org/10.1145/2145204.2145279
  11. Abdelkareem Bedri, Gregory Abowd, Richard Li, Malcolm Haynes, Raj Prateek Kosaraju, Ishaan Grover, Temiloluwa Prioleau, Min Yan Beh, Mayank Goel, and Thad Starner. (2017). EarBit: Using Wearable Sensors to Detect Eating Episodes in Unconstrained Environments. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 1(3), 1–20. http://doi.org/10.1145/3130902
  12. Abdelkareem Bedri, Diana Li, Rushil Khurana, Kunal Bhuwalka, and Mayank Goel. (2020). FitByte: Automatic Diet Monitoring in Unconstrained Situations Using Multimodal Sensing on Eyeglasses. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2020), 1–12. http://doi.org/10.1145/3313831.3376869
  13. Oscar Beijbom, Neel Joshi, Dan Morris, Scott Saponas, and Siddharth Khullar. (2015). Menu-match: Restaurant-Specific Food Logging From Images. Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV 2015), 844–851. http://doi.org/10.1109/WACV.2015.117
  14. Erin Beneteau, Olivia K. Richards, Mingrui Zhang, Julie A. Kientz, Jason Yip, and Alexis Hiniker. (2019). Communication Breakdowns Between Families and Alexa. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2019), 1–13. http://doi.org/10.1145/3290605.3300473
  15. Johnna Blair, Yuhan Luo, Ning F. Ma, Sooyeon Lee, and Eun Kyoung Choe. (2018). OneNote Meal: A Photo-Based Diary Study for Reflective Meal Tracking. AMIA Annual Symposium proceedings (AMIA 2018), 252–261. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371351/
  16. Marc Bolanos and Petia Radeva. (2016). Simultaneous Food Localization and Recognition. Proceedings of International Conference on Pattern Recognition (ICPR 2016), 0, 3140–3145. http://doi.org/10.1109/ICPR.2016.7900117
  17. Virginia Braun and Victoria Clarke. (2006). Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 3(2), 77–101. http://doi.org/10.1191/1478088706qp063oa
  18. Lora E. Burke, Molly B. Conroy, Susan M. Sereika, Okan U. Elci, Mindi A. Styn, Sushama D. Acharya, Mary A. Sevick, Linda J. Ewing, and Karen Glanz. (2011). The Effect of Electronic Self-Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial. Obesity, 19(2), 338–344. http://doi.org/10.1038/oby.2010.208
  19. Micael Carvalho, Rémi Cadène, David Picard, Laure Soulier, Nicolas Thome, and Matthieu Cord. (2018). Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings. ning Semantic Text-Image Embeddings. Proceedings of The Conference on Research & Development in Information Retrieval (SIGIR 2018), 35-44. http://doi.org/10.1145/3209978.3210036
  20. Beenish M. Chaudhry, Christopher Schaefbauer, Ben Jelen, Katie A. Siek, and Kay Connelly. (2016). Evaluation of a Food Portion Size Estimation Interface for a Varying Literacy Population. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2016), 5645–5657. http://doi.org/10.1145/2858036.2858554
  21. Juliana Chen, William Berkman, Manal Bardouh, Ching Yan Kammy Ng, and Margaret Allman-Farinelli. (2019). The Use of a Food Logging App in the Naturalistic Setting Fails to Provide Accurate Measurements of Nutrients and Poses Usability Challenges. Nutrition, 57, 208–216. http://doi.org/10.1016/j.nut.2018.05.003
  22. Juliana Chen, Janet E. Cade, and Margaret Allman-Farinelli. (2015). The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment. Journal of Medical Internet Research (JMIR 2015), 3(4), e104. http://doi.org/10.2196/mhealth.4334
  23. Eun Kyoung Choe, Saeed Abdullah, Mashfiqui Rabbi, Edison Thomaz, Daniel A. Epstein, Felicia Cordeiro, Matthew Kay, Gregory D. Abowd, Tanzeem Choudhury, James Fogarty, Bongshin Lee, Mark Matthews, and Julie A. Kientz. (2017). Semi-Automated Tracking: A Balanced Approach for Self-Monitoring Applications. IEEE Pervasive Computing, 16(1), 74–84. http://doi.org/10.1109/MPRV.2017.18
  24. Eun Kyoung Choe, Nicole B. Lee, Bongshin Lee, Wanda Pratt, and Julie A. Kientz. (2014). Understanding Quantified-Selfers’ Practices in Collecting and Exploring Personal Data. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2014), 1143–1152. http://doi.org/10.1145/2556288.2557372
  25. Munmun De Choudhury, Sanket Sharma, and Emre Kiciman. (2016). Characterizing Dietary Choices, Nutrition, and Language in Food Deserts Via Social Media. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2016), 1157–1170. http://doi.org/10.1145/2818048.2819956
  26. 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 (IMWUT), 2(1), 1–21. http://doi.org/10.1145/3191736
  27. [27]Chia-Fang Chung, Qiaosi Wang, Jessica Schroeder, Allison Cole, Jasmine Zia, James Fogarty, and Sean A. Munson. (2019). Identifying and Planning for Individualized Change. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 3(1), 1–27. http://doi.org/10.1145/3314394
  28. Chia Fang Chung, Elena Agapie, Jessica Schroeder, Sonali Mishra, James Fogarty, and Sean A. Munson. (2017). When Personal Tracking Becomes Social: Examining the Use of Instagram for Healthy Eating. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2017), 1674–1687. http://doi.org/10.1145/3025453.3025747
  29. Clarifai’s Food Model | AI Prediction of Specific Food in Meals. Retrieved 10 February, 2021 from https://www.clarifai.com/models/food
  30. Felicia Cordeiro, Elizabeth Bales, Erin Cherry, and James Fogarty. (2015). Rethinking the Mobile Food Journal: Exploring Opportunities for Lightweight Photo-Based Capture. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2015), 3207–3216. http://doi.org/10.1145/2702123.2702154
  31. Felicia Cordeiro, Daniel A. Epstein, Edison Thomaz, Elizabeth Bales, Arvind K. Jagannathan, Gregory D. Abowd, and James Fogarty. (2015). Barriers and Negative Nudges: Exploring Challenges in Food Journaling. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2015), 1159–1162. http://doi.org/10.1145/2702123.2702155
  32. Alaina Darby, Matthew W. Strum, Erin Holmes, and Justin Gatwood. (2016). A Review of Nutritional Tracking Mobile Applications for Diabetes Patient Use. Diabetes Technology & Therapeutics, 18(3), 200–212. http://doi.org/10.1089/dia.2015.0299
  33. Tamara Denning, Adrienne Andrew, Rohit Chaudhri, Carl Hartung, Jonathan Lester, Gaetano Borriello, and Glen Duncan. (2009). BALANCE: Towards a Usable Pervasive Wellness Application With Accurate Activity Inference. Proceedings of the 10th Workshop on Mobile Computing Systems and Applications (HotMobile’09), 5. http://doi.org/10.1145/1514411.1514416
  34. Pooja M Desai, Elliot G Mitchell, Maria L Hwang, Matthew E Levine, David J Albers, and Lena Mamykina. (2019). Personal Health Oracle: Explorations of Personalized Predictions in Diabetes Self-Management. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2019), 1–13. http://doi.org/10.1145/3290605.3300600
  35. E-health application categories used by U.S. adults 2017 | Statista. Retrieved 10 February, 2021 from https://www.statista.com/statistics/378850/top-mobile-health-application-categories-used-by-us-consumers/
  36. Edamam Nutrition Analysis API. Retrieved 10 February, 2021 https://developer.edamam.com/edamam-nutrition-api
  37. Daniel A. Epstein, Felicia Cordeiro, James Fogarty, Gary Hsieh, and Sean A. Munson. (2016). Crumbs: Lightweight Daily Food Challenges to Promote Engagement and Mindfulness. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2016), 5632–5644. http://doi.org/10.1145/2858036.2858044
  38. Amazon says 100 million Alexa devices have been sold – The Verge. Retrieved 10 February, 2021 https://www.theverge.com/2019/1/4/18168565/amazon-alexa-devices-how-many-sold-number-100-million-dave-limp
  39. Giannina Ferrara, Jenna Kim, Shuhao Lin, Jenna Hua, and Edmund Seto. (2019). A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates. JMIR mHealth and uHealth, 7(5), e9232. http://doi.org/10.2196/mhealth.9232
  40. FoodData Central – USDA. Retrieved 10 February, 2021 from https://fdc.nal.usda.gov/api-guide.html
  41. Google’s Cloud Vision API. Retrieved 10 February, 2021 from https://cloud.google.com/vision/docs/
  42. Google’s “smart” Food Diary is Actually Kind of Dumb. Retrieved 10 February, 2021 from https://www.theverge.com/2015/6/2/8707851/google-calories-food-photos-im2calories
  43. Nanna Gorm and Irina Shklovski. (2017). Participant Driven Photo Elicitation for Understanding Activity Tracking: Benefits and Limitations. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2017), 1350–1361. http://doi.org/10.1145/2998181.2998214
  44. Rúben Gouveia, Evangelos Karapanos, and Marc Hassenzahl. (2018). Activity Tracking in Vivo. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2018), 1–13. http://doi.org/10.1145/3173574.3173936
  45. Alexandros Graikos, Vasileios Charisis, Dimitrios Iakovakis, Stelios Hadjidimitriou, and Leontios Hadjileontiadis. (2020). Single Image-Based Food Volume Estimation Using Monocular Depth-Prediction Networks. Universal Access in Human-Computer Interaction. Applications and Practice (HCII 2020), 532–543. http://doi.org/10.1007/978-3-030-49108-6_38
  46. Andrea Grimes, Martin Bednar, Jay David Bolter, and Rebecca E Grinter. (2008). EatWell: Sharing Nutrition-Related Memories in a Low-Income Community. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2008), 87-96. http://doi.org/10.1145/1460563.1460579
  47. Andrea Grimes and Richard Harper. (2008). Celebratory Technology: New Directions for Food Research in HCI. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008), 467–476. http://doi.org/10.1145/1357054.1357130
  48. William D. Heizer, Susannah Southern, and Susan McGovern. (2009). The Role of Diet in Symptoms of Irritable Bowel Syndrome in Adults: A Narrative Review. Journal of the American Dietetic Association, 109(7), 1204–1214. http://doi.org/10.1016/j.jada.2009.04.012
  49. Uta Hinrichs and Sheelagh Carpendale. (2011). Gestures in The Wild: Studying Multi-Touch Gesture Sequences on Interactive Tabletop Exhibits. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2011), 3023–3032. http://doi.org/10.1145/1978942.1979391
  50. Jack F. Hollis, Christina M. Gullion, Victor J. Stevens, Phillip J. Brantley, Lawrence J. Appel, Jamy D. Ard, Catherine M. Champagne, Arlene Dalcin, Thomas P. Erlinger, Kristine Funk, Daniel Laferriere, Pao Hwa Lin, Catherine M. Loria, Carmen Samuel-Hodge, William M. Vollmer, and Laura P. Svetkey. (2008). Weight Loss During the Intensive Intervention Phase of the Weight-Loss Maintenance Trial. American Journal of Preventive Medicine, 35(2), 118–126. http://doi.org/10.1016/j.amepre.2008.04.013
  51. Eunkyung Jo, Hyeonseok Bang, Myeonghan Ryu, Eun Jee Sung, Sungmook Leem, and Hwajung Hong. (2020). MAMAS: Supporting Parent – Child Mealtime Interactions Using Automated Tracking and Speech Recognition. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW1). http://doi.org/10.1145/3392876
  52. Jisu Jung, Kalina Yacef, Margaret Allman-farinelli, Judy Kay, Lyndal Wellard-Cole, Colin Cai, Irena Koprinska, and Margaret Allman-Farinelli. (2020). Foundations for Systematic Evaluation and Benchmarking of a Mobile Food Logger in a Large-scale Nutrition Study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 4(2), 47. http://doi.org/10.1145/3397327
  53. Ravi Karkar, Jessica Schroeder, Daniel A. Epstein, Laura R. Pina, Jeffrey Scofield, James Fogarty, Julie A. Kientz, Sean A. Munson, Roger Vilardaga, and Jasmine Zia. (2017). TummyTrials: A Feasibility Study of Using Self-Experimentation to Detect Individualized Food Triggers. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2017), 2017-May, 6850–6863. http://doi.org/10.1145/3025453.3025480
  54. Young-Ho Kim, Jae Ho Jeon, Bongshin Lee, Eun Kyoung Choe, and Jinwook Seo. (2017). OmniTrack: A Flexible Self-Tracking Approach Leveraging Semi-Automated Tracking. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 1(3), 1– 28. http://doi.org/10.1145/3130930
  55. Mandy Korpusik, Zachary Collins, and James Glass. (2017). Semantic Mapping of Natural Language Input to Database Entries Via Convolutional Neural Networks. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), 5685–5689. http://doi.org/10.1109/ICASSP.2017.7953245
  56. Mandy Korpusik and James Glass. (2017). Spoken Language Understanding for a Nutrition Dialogue System. IEEE/ACM Transactions on Audio Speech and Language Processing, 25(7), 1450–1461. http://doi.org/10.1109/TASLP.2017.2694699
  57. Ian Li, Anind Dey, and Jodi Forlizzi. (2010). A Stage-Based Model of Personal Informatics Systems. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2010), 1, 557–566. http://doi.org/10.1145/1753326.1753409
  58. Brian Y. Lim, Xinni Chng, and Shengdong Zhao. (2017). Trade-off between Automation and Accuracy in Mobile Photo Recognition Food Logging. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2017), 53–59. http://doi.org/10.1145/3080631.3080640
  59. Lose It! – Weight Loss That Fits. Retrieved February 10, 2021 from https://www.loseit.com/
  60. Kai Lukoff, Taoxi Li, Yuan Zhuang, and Brian Y. Lim. (2018). TableChat: Mobile Food Journaling to Facilitate Family Support for Healthy Eating. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1–28. http://doi.org/10.1145/3274383
  61. Lena Mamykina, Matthew E. Levine, Patricia G. Davidson, Arlene M Smaldone, Noemie Elhadad, and David J Albers. (2016). Data-driven health management: reasoning about personally generated data in diabetes with information technologies. Journal of the American Medical Informatics Association, 23(3), 526–531. http://doi.org/10.1093/jamia/ocv187
  62. Lena Mamykina, Elizabeth Mynatt, Patricia Davidson, and Daniel Greenblatt. (2008). MAHI: Investigation of Social Scaffolding for Reflective Thinking in Diabetes Management. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008), 477. http://doi.org/10.1145/1357054.1357131
  63. Weiqing Min, Shuqiang Jiang, Linhu Liu, Yong Rui, and Ramesh Jain. (2019). A Survey on Food Computing. ACM Computing Surveys, 52(5), 1–36. http://doi.org/10.1145/3329168
  64. Jimmy Moore, Pascal Goffin, Miriah Meyer, Philip Lundrigan, Neal Patwari, Katherine Sward, and Jason Wiese. (2018). Managing In-home Environments through Sensing, Annotating, and Visualizing Air Quality Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2(3), 1–28. http://doi.org/10.1145/3264938
  65. Austin Myers, Nick Johnston, Vivek Rathod, Anoop Korattikara, Alex Gorban, Nathan Silberman, Sergio Guadarrama, George Papandreou, Jonathan Huang, and Kevin Murphy. (2015). Im2Calories: Towards an automated mobile vision food diary. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 1233–1241. http://doi.org/10.1109/ICCV.2015.146
  66. MyFitnessPal: Calorie Counter, Diet & Exercise Journal. Retrieved February 10, 2021 from https://www.myfitnesspal.com/
  67. Jon Noronha, Eric Hysen, Haoqi Zhang, and Krzysztof Z Gajos. (2011). PlateMate: Crowdsourcing Nutrition Analysis from Food Photographs. Proceedings of the Annual Symposium on User Interface Software and Technology (UIST 2011), 1-12. http://doi.org/10.1145/2047196.2047198
  68. NPR Study Says 118 Million Smart Speakers Owned by U.S. Adults – Voicebot.ai. Retrieved February 10, 2021 from https://voicebot.ai/2019/01/07/npr-study-says-118-million-smart-speakers-owned-by-u-s-adults/
  69. Nutritionix Nutrition API. Retrieved February 10, 2021 from https://www.nutritionix.com/business/api
  70. Hyungik Oh, Jonathan Nguyen, Soundarya Soundararajan, and Ramesh Jain. (2018). Multimodal Food Journaling. Proceedings of the International Workshop on Multimedia for Personal Health and Health Care (HealthMedia 2018), 39–47. http://doi.org/10.1145/3264996.3265000
  71. Tauhidur Rahman, Alexander T. Adams, Mi Zhang, Erin Cherry, Bobby Zhou, Huaishu Peng, and Tanzeem Choudhury. (2014). BodyBeat: Amobile system for sensing non-speech body sounds. Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys 2014), 2–13. http://doi.org/10.1145/2594368.2594386
  72. RapidAPI – Top Nutrition APIs. Retrieved February 10, 2021 from https://rapidapi.com/collection/nutrition
  73. Jaime Ruiz, Yang Li, and Edward Lank. (2011). User-Defined Motion Gestures for Mobile Interaction. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2011), 197–206. http://doi.org/10.1145/1978942.1978971
  74. Amaia Salvador, Michal Drozdzal, Xavier Giro-I-Nieto, and Adriana Romero. (2019). Inverse Cooking: Recipe Generation from Food Images. Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR 2019), 10445–10454. http://doi.org/10.1109/CVPR.2019.01070
  75. Jessica Schroeder, Jane Hoffswell, Chia Fang Chung, James Fogarty, Sean Munson, and Jasmine Zia. (2017). Supporting Patient-Provider Collaboration to Identify Individual Triggers Using Food and Symptom Journals. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2017), 1726–1739. http://doi.org/10.1145/2998181.2998276
  76. Alex Sciuto, Arnita Saini, Jodi Forlizzi, and Jason I. Hong. (2018). “Hey Alexa, what’s up?”: Studies of In-Home Conversational Agent Usage. Proceedings of the Conference on Designing Interactive Systems (DIS 2018), 857–868. http://doi.org/10.1145/3196709.3196772
  77. Katie A. Siek, Kay H. Connelly, Yvonne Rogers, Paul Rohwer, Desiree Lambert, and Janet L. Welch. (2006). When Do We Eat? An Evaluation of Food Items Input into an Electronic Food Monitoring Application. 2006 Pervasive Health Conference and Workshops, 1–10. http://doi.org/10.1109/PCTHEALTH.2006.361684
  78. Spoonacular food API. Retrieved February 10, 2021 from https://spoonacular.com/food-api
  79. Zhida Sun, Sitong Wang, Wenjie Yang, Onur Yürüten, Chuhan Shi, and Xiaojuan Ma. (2020). “A Postcard from Your Food Journey in the Past”: Promoting Self-Refection on Social Food Posting. Proceedings of the Conference on Designing Interactive Systems (DIS 2020), 1819–1832. http://doi.org/10.1145/3357236.3395475
  80. Edison Thomaz, Aman Parnami, Irfan Essa, and Gregory D. Abowd. (2013). Feasibility of Identifying Eating Moments from First-Person Images Leveraging Human Computation. Proceedings of the International SenseCam & Pervasive Imaging Conference (SenseCam 2013), 26–33. http://doi.org/10.1145/2526667.2526672
  81. Christopher C. Tsai, Gunny Lee, Fred Raab, Gregory J. Norman, Timothy Sohn, William G. Griswold, and Kevin Patrick. (2007). Usability and Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric Balance. Mobile Networks and Applications, 12(2–3), 173–184. http://doi.org/10.1007/s11036-007-0014-4
  82. Yunan Wang, Jing Jing Chen, Chong Wah Ngo, Tat Seng Chua, Wanli Zuo, and Zhaoyan Ming. (2019). Mixed dish recognition through multi-label learning. Proceedings of the 11th Workshop on Multimedia for Cooking and Eating Activities (CEA 2019), 1–8. http://doi.org/10.1145/3326458.3326929
  83. Donald A Williamson, ; H Raymond Allen, ; Pamela, Davis Martin, Anthony J Alfonso, Bonnie Gerald, and Alice Hunt. (2003). Comparison of Digital Photography to Weighed and Visual Estimation of Portion Sizes. Journal of American Dietetic Associattion, 103, 1139–1145. https://doi.org/10.1016/S0002-8223(03)00974-X
  84. Jacob O Wobbrock, Meredith Ringel Morris, and Andrew D Wilson. (2009). Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2009), 1083–1092. http://doi.org/10.1145/1518701.1518866
  85. Hui Wu, Michele Merler, Rosario Uceda-Sosa, and John R. Smith. (2016). Learning to Make Better Mistakes: Semantics-Aware Visual Food Recognition. Proceedings of the International Conference on Multimedia (MM 2016), 172–176. http://doi.org/10.1145/2964284.2967205
  86. WW (Weight Watchers): Weight Loss & Wellness Help. Retrieved February 10, 2021 from https://www.weightwatchers.com
  87. Shulin Yang, Mei Chen, Dean Pomerleau, and Rahul Sukthankar. (2010). Food Recognition Using Statistics of Pairwise Local Features. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2010), 2249–2256. http://doi.org/10.1109/CVPR.2010.5539907
  88. ‎YouFood Photo Food Journal on the App Store. Retrieved February 10, 2021 from https://apps.apple.com/us/app/youfood-photo-food-journal/id719841416
  89. Shibo Zhang, Yuqi Zhao, Dzung Tri Nguyen, Runsheng Xu, Sougata Sen, Josiah Hester, and Nabil Alshurafa. (2020). NeckSense: A Multi-Sensor Necklace for Detecting Eating Activities in Free-Living Conditions. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 4(2), 1–26. http://doi.org/10.1145/3397313
  90. Jasmine K. Zia, Chia-Fang Chung, Jessica Schroeder, Sean A. Munson, Julie A. Kientz, James Fogarty, Elizabeth Bales, Jeanette M. Schenk, and Margaret M. Heitkemper. (2017). The Feasibility, Usability, and Clinical Utility of Traditional Paper Food and Symptom Journals for Patients with Irritable Bowel Syndrome. Neurogastroenterology & Motility, 29(2), e12935. http://doi.org/10.1111/nmo.12935
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