Nutrition has a big impact on health, including major diseases such as heart disease, osteoporosis, and cancer. Our work is designed to help people keep track of the nutrional content of foods they have eaten. Our work uses shopping receipts to generate suggestions about healthier food items that could help to supplement missing nutrients. Our application, based on shopping receipt data, provides access to ambiguous suggestions for more nutritious purchases.
Our goal is to contribute a better understanding of how a sensor-based application can be integrated in everyday life. To do this, we chose an approach that can easily be replicated for many users, deployed, and tested for months at a time. We are currently in the process of conducting a diary study that can provide data on which we can train our prediction algorithms. We conducted a formative user study that suggested that receipts may provide enough information to extend our work by also estimating what people are actually eating, as opposed to simply what they are purchasing. We are also interviewing and observing people's shopping and food managing habits to further inform the system design.