A behavioral sensing system that promotes positive lifestyle changes and improves metabolic control among adults with type 2 diabetes

The incidence of type 2 (insulin resistant) diabetes (T2D) is increasing, along with its complications of personal anguish and treatment costs. The American Diabetes Association recommends Lifestyle Modification (LM) both for the prevention and management of T2D. The basic premise of LM is that energy intake should be equal to energy output, or net carbohydrates consumed should roughly equal energy “burned” by physical activity to avoid hyperglycemia and its consequences. While these recommendations support healthy habits, lack of knowledge and motivation often result in “forgetting” to execute intended behaviors. Mobile technologies such a smartphones and wearables have the potential to educate, motivate and prompt individuals in situ to optimize these LMs and thereby favorably affect health. This paper presents a framework using wearable activity trackers and smartphones to promote positive behaviors such as reducing sedentary activity and promoting physical activity after meals. To evaluate the feasibility of the proposed approach, the technology and supporting algorithms were analyzed and evaluated in a group of healthy students. Specifically, we developed an eating detection algorithm fusing accelerometer and gyroscope data streams from a smart watch. We developed the proposed algorithm in a controlled laboratory study, and we present the preliminary results of our eating detection algorithm from the experiment.