I-Corps: A real-time dietary decision support system for the prevention and management of diabetes.

这个I-Corps项目的更广泛的影响/商业潜力是改善糖尿病和糖尿病前期人群的饮食依从性和健康结果。近3000万美国成年人患有II型糖尿病。II型糖尿病是一个严重的公共卫生问题，因为其并发症，包括心血管疾病、肾衰竭、失明和截肢，极大地影响了患者的健康和生活质量。为了有效地自我管理他们的疾病，患者面临着通过遵循饮食指导和防止过度体重增加来控制他们的葡萄糖水平的艰巨任务。数字健康产品有可能通过提供实时、互动的自我管理帮助来提高患者对这些建议的依从性。然而，现有的移动的糖尿病自我管理应用局限于它们作为葡萄糖跟踪器的功能。该项目的目标是开发一个主动的饮食相关决策支持系统，该系统是个性化的，以持续监测葡萄糖浓度。软件和传感器技术的整合将带来一种更有效和个性化的方法来预防II型糖尿病患者的疾病进展。这个I-Corps项目研究了使用可穿戴传感器的生物输入的商业可行性，以消除对卡路里跟踪的需要，并开发个性化和动态的实时食物相关决策支持。我们的专有算法使用连续葡萄糖读数作为生物反馈，以帮助糖尿病患者决定吃什么和什么时候吃。先前的研究已经证明，使用便携式血糖仪改善超重非糖尿病人群的自我调节饮食行为，可以改善血糖控制和持续减肥。这项技术将把这种基于证据的生物行为干预方法实时应用于2型糖尿病和前驱糖尿病患者。用户界面将是一个具有图形输出的移动的平台，以协助“即时”决策以及监测其血糖变异性。该平台将为患者提供汇总统计数据，并与医疗保健提供者共享。

The broader impact/commercial potential of this I-Corps project is to improve dietary compliance and health outcomes in diabetic and pre-diabetic populations. Almost 30 million Americans adults have Type II diabetes. Type II diabetes is a serious public health concern, as its complications, which include cardiovascular disease, kidney failure, blindness and amputations, greatly affect patients' health and quality of life. To effectively self-manage their disease, patients face the difficult task of controlling their glucose levels by following dietary guidance and preventing excessive weight gain. Digital health products have the potential to improve patient adherence to these recommendations by providing real-time, interactive self-management aid. Yet, existing mobile diabetes self-management applications are limited to their function as glucose trackers. The goal of the proposed project is to develop a proactive diet-related decision-making support system that is personalized to continuously monitored glucose concentrations. The integration of software and sensor technology will result in a more efficient and individualized method to prevent disease progression in Type II diabetics.This I-Corps project examines the commercial feasibility of using biological inputs from wearable sensors to eliminate the need for calorie-tracking and develop personalized and dynamic real-time food-related decision support. Our proprietary algorithms use continuous glucose readings as biological feedback to assist diabetic patients with decisions about what and when to eat. Previous studies have demonstrated improved glycemic control and sustained weight loss using portable glucometers to improve self-regulated eating behavior in overweight non-diabetic populations. The proposed technology will translate this evidence-based biobehavioral intervention approach to Type 2 and pre-diabetic patients in real-time. The user interface will be a mobile platform with graphical outputs to assist with 'in-the-moment' decision-making as well as to monitor their glucose variability. The platform will provide summary statistics for patients that can be shared with their healthcare providers.