首页> 外文学位 >Intelligent diabetes assistant a telemedicine system for modeling and managing blood glucose.
【24h】

Intelligent diabetes assistant a telemedicine system for modeling and managing blood glucose.

机译:智能糖尿病助手远程医疗系统,用于建模和管理血糖。

获取原文
获取原文并翻译 | 示例

摘要

The creation of a diabetes management assistant that can remotely collect data, increase communication between patient and care provider, and automatically analyze all available information could improve the health of many diabetics. Individual models, taking into account nutrition, medication, and exercise, with appropriate mathematical modeling, can learn accurate representations of specific patients suitable for providing therapy advice.;The fundamental goal of effective diabetes management is for the patient to select behaviors that maintain glycemic homeostasis. Thus the goal of an intelligent diabetes assistant is to help the patient select optimal behaviors. To do this the assistant must be able to learn how a patient's choices will affect blood glucose. From the care providers perspective a system should he able to provide detailed and accurate data about the patient, increase interaction between patient and expert, and be efficient. This thesis describes an intelligent diabetes assistant (IDA) designed to meet these goals.;IDA uses a mobile phone application and other devices to measure the three primary components that affect blood glucose: meals, medication, and exercise. The data are used to learn models for predicting how behaviors around meal times affect postprandial blood glucose, and to create a new continuous physiological model that includes exercise. These models can then be used in a variety of ways to generate therapy advice for the patient and health care provider. The complete system is presented in this thesis.
机译:创建可以远程收集数据,增加患者与护理提供者之间的交流并自动分析所有可用信息的糖尿病管理助手可以改善许多糖尿病患者的健康状况。个体模型考虑到营养,药物和运动,并具有适当的数学模型,可以学习适合提供治疗建议的特定患者的准确代表。有效糖尿病管理的基本目标是使患者选择保持血糖稳态的行为。因此,智能糖尿病助手的目标是帮助患者选择最佳行为。为此,助手必须能够了解患者的选择将如何影响血糖。从护理提供者的角度来看,系统应该能够提供有关患者的详细而准确的数据,增加患者与专家之间的互动,并且要高效。本论文描述了一种旨在实现这些目标的智能糖尿病助手(IDA)。IDA使用手机应用程序和其他设备来测量影响血糖的三个主要成分:进餐,药物和运动。数据用于学习模型,以预测进餐时间周围的行为如何影响餐后血糖,并创建包括运动在内的新的连续生理模型。然后,可以通过多种方式使用这些模型来为患者和医疗保健提供者生成治疗建议。本文提出了完整的系统。

著录项

  • 作者

    Duke, David L.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Biology Bioinformatics.;Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 150 p.
  • 总页数 150
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:45:43

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号