Elliot G Mitchell, Elizabeth M Heitkemper, Marissa Burgermaster, Matthew E Levine, Yishen Miao, Maria L Hwang, Pooja M Desai, Andrea Cassells, Jonathan N Tobin, Esteban G Tabak, David J Albers, Arlene M Smaldone, Lena Mamykina
Self-tracking can help personalize self-management interventions for chronic conditions like type 2 diabetes (T2D), but reflecting on personal data requires motivation and literacy. Machine learning (ML) methods can identify patterns, but a key challenge is making actionable suggestions based on personal health data. We introduce GlucoGoalie, which combines ML with an expert system to translate ML output into personalized nutrition goal suggestions for individuals with T2D. In a controlled experiment, participants with T2D found that goal suggestions were understandable and actionable...
May 2021: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems