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

机译:一种促进阳性生活方式的行为传感系统,并改善2型糖尿病成人的代谢控制

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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.
机译:2型(胰岛素)糖尿病(T2D)的发病率随着个人痛苦和治疗成本的并发症而增加。美国糖尿病协会推荐用于预防和管理T2D的生活方式改造(LM)。 LM的基本前提是,能量摄入量应等于能量输出,或消耗的净碳水化合物应通过体育活动大致相同的能量“燃烧”,以避免高血糖及其后果。虽然这些建议支持健康的习惯,但缺乏知识和动机通常会导致“忘记”执行预期行为。移动技术如此智能手机和可穿戴设备有可能教育,激励和提示的人原位优化这些LMS,从而有利地影响健康。本文介绍了一种使用可穿戴活动跟踪器和智能手机的框架,以促进积极行为,例如减少久坐活度和膳食后促进体育活动。为了评估所提出的方法的可行性,分析了技术和支持算法,并在一组健康的学生中进行了评估。具体而言,我们开发了一种融合的加速度计和来自智能手表的陀螺数据流的饮食检测算法。我们在受控实验室研究中开发了该算法,我们从实验中提出了我们的饮食检测算法的初步结果。

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