Models, signals, and distributed bio-behavioral control of exercise in diabetes

糖尿病运动的模型、信号和分布式生物行为控制

• 批准号: 8971447
• 负责人: MARC D BRETON
• 金额: $ 297.99万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8971447
• 关键词: Accounting; Acute; Address; Adherence; Algorithms; Architecture; Artificial Pancreas; Automation; Behavior Control; Blood Glucose; Carbohydrates; Cellular Phone; Clinical Trials; Complex; Data; Data Analyses; Data Collection; Databases; Decision Support Systems; Detection; Development; Devices; Diabetes Mellitus; Dose; Ecosystem; Education; Ensure; Exercise; Exposure to; Face; Feasibility Studies; Feedback; Fright; Glucose; Hearing; Heart Rate; Home environment; Hour; Human; Hyperglycemia; Hypoglycemia; Illinois; Injection of therapeutic agent; Inpatients; Institutes; Insulin; Insulin-Dependent Diabetes Mellitus; Intake; Lead; Left; Life; Medical Device; Metabolic; Modeling; Monitor; Names; Patients; Pattern; Philosophy; Physical activity; Physiological; Physiology; Pump; Research; Research Infrastructure; Risk; Running; Safety; Signal Transduction; Specificity; System; Technology; Testing; Time; Universities; Update; Validation; Variant; Virginia; base; blood glucose regulation; clinically relevant; cloud based; design; detector; empowered; feeding; fitness; glycemic control; improved; novel; pancreas development; programs; psychosocial; public health relevance; safety study; sensor; simulation

 DESCRIPTION (provided by applicant): Physically active patients with type 1 diabetes (T1D) face a very specific challenge in their management of glycaemia: physical activity can dramatically alter glucose homeostasis both acutely and over a period of several hours. The magnitude of this behaviorally triggered physiological disturbance is highly variable and depends on a number of factors such as insulin- on-board, prandial state, and fitness to name only a few. These complex interactions and associated fear of hypoglycemia often lead to avoidance of physical activity. We propose to address this specific hurdle of living with diabetes by empowering patients through a network of medical devices, assembled into an adaptive artificial pancreas (AP) platform, tailored to the needs and choices of each patient. This project unites two leading groups in artificial pancreas development, the University of Virginia Center for Diabetes Technology and the Illinois Institute of Technology Center for Diabetes Research and Education. We propose to leverage our extensive technology portfolio in AP platform, closed loop algorithms, exercise detection and quantification, and modelling to address the following specific aims: 1. Patient-specific exercise risk alert system informing patients at the onset of exercise of likely hypoglycemia based on: (i) tuning a risk detector to each patient using DiAs cloud functionalities, and (ii) personalized simulation-based advice on treatment adaptation. 2. Exercise-informed automated insulin dosing: Upgrade to AP control system using exercise sensing to track metabolic risk and adjust insulin to maintain safe BG levels. 3. Fully-integrated Exercise-adapted AP system: We hypothesize that an exercise-informed AP system with both feed-forward (1) and feedback (2) components, freeing the patient from obligatory additional devices will improve glycemic safety and technology acceptance. We will demonstrate feasibility, safety, and efficacy of each of the proposed modules, independently and in concert, through three human clinical trials: two short term inpatient demonstration trials and one final longer term (4 months) home trial. This final trial will also explore psychosocial aspects of exercising with our platform, and start addressing key aspects of safety, accounting for adherence and technology acceptance of such a complex system. We expect the proposed system to enhance the safety and efficacy of AP in real life conditions. By creating a novel data infrastructure and optimal exercise control algorithms, this project has also the potential to generate clinically relevant derivatives for other mode of treatment.

 描述（由申请人提供）：体力活动的1型糖尿病（T1 D）患者在管理糖尿病时面临非常特殊的挑战：体力活动可在急性和数小时内显著改变葡萄糖稳态。这种行为触发的生理紊乱的程度是高度可变的，并且取决于许多因素，例如胰岛素-机载、膳食状态和健身，仅举几例。这些复杂的相互作用和对低血糖的相关恐惧往往导致避免体力活动。我们建议通过医疗设备网络赋予患者权力来解决糖尿病患者生活的这一特定障碍，这些医疗设备组装成一个自适应人工胰腺（AP）平台，根据每位患者的需求和选择量身定制。该项目联合了人工胰腺开发的两个领导小组，弗吉尼亚大学中心， 糖尿病技术和伊利诺斯州技术研究所糖尿病研究和教育中心。我们建议利用我们在AP平台，闭环算法，运动检测和量化以及建模方面的广泛技术组合来解决以下具体目标：1.患者特定的运动风险警报系统在运动开始时通知患者可能的低血糖，其基于：（i）使用DiAs云功能将风险检测器调整到每个患者，以及（ii）关于治疗适应的个性化基于模拟的建议。2.自动化胰岛素给药：升级到AP控制系统，使用运动传感来跟踪代谢风险并调整胰岛素以维持安全的血糖水平。3.完全集成的运动适应性AP系统：我们假设，具有前馈（1）和反馈（2）组件的运动知情AP系统，使患者免于强制性的额外设备，将提高血糖安全性和技术接受度。我们将通过三项人体临床试验来独立和协同证明每个拟议模块的可行性，安全性和有效性：两项短期住院示范试验和一项最终的长期（4个月）家庭试验。这项最终试验还将探索使用我们的平台进行锻炼的心理社会方面，并开始解决安全性的关键方面，解释这种复杂系统的依从性和技术接受度。我们期望所提出的系统，以提高AP在真实的生活条件下的安全性和有效性。通过创建一个新的数据基础设施和最佳的运动控制算法，该项目也有可能为其他治疗模式产生临床相关的衍生物。

项目成果

Automatically accounting for physical activity in insulin dosing for type 1 diabetes.

• DOI: 10.1016/j.cmpb.2020.105757
• 发表时间: 2020-12
• 期刊: Computer methods and programs in biomedicine
• 影响因子: 6.1
• 作者: Ozaslan B;Patek SD;Fabris C;Breton MD
• 通讯作者: Breton MD

In Silico Analysis of an Exercise-Safe Artificial Pancreas With Multistage Model Predictive Control and Insulin Safety System.

• DOI: 10.1177/1932296819879084
• 发表时间: 2019-11-01
• 期刊: Journal of diabetes science and technology
• 影响因子: 5
• 作者: Garcia-Tirado, Jose;Colmegna, Patricio;Breton, Marc D
• 通讯作者: Breton, Marc D

Improving Glucose Prediction Accuracy in Physically Active Adolescents With Type 1 Diabetes.

• DOI: 10.1177/1932296818820550
• 发表时间: 2019-07-01
• 期刊: Journal of diabetes science and technology
• 影响因子: 5
• 作者: Hobbs, Nicole;Hajizadeh, Iman;Cinar, Ali
• 通讯作者: Cinar, Ali

Safety and Feasibility Evaluation of Step Count Informed Meal Boluses in Type 1 Diabetes: A Pilot Study.

1 型糖尿病中步数知情膳食推注的安全性和可行性评估：一项试点研究。

• DOI: 10.1177/1932296821997917
• 发表时间: 2022
• 期刊: Journal of diabetes science and technology
• 影响因子: 5
• 作者: Ozaslan,Basak;Brown,SueA;Pinnata,Jennifer;Barnett,CharlotteL;Carr,Kelly;Wakeman,ChristianA;Clancy-Oliveri,Mary;Breton,MarcD
• 通讯作者: Breton,MarcD