SCH: INT: Collaborative Research: Monitoring and Modeling Family Eating Dynamics (M2 FED): Reducing Obesity Without Focusing on Diet and Activity

SCH：INT：合作研究：家庭饮食动态监测和建模 (M2 FED)：在不关注饮食和活动的情况下减少肥胖

• 批准号: 1521740
• 负责人: Donna Spruijt-Metz
• 金额: $ 104.8万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1521740&HistoricalAwards=false
• 关键词: SCH; INT; Collaborative; Research; Monitoring; SCH; INT; Collaborative; Research; Monitoring

This project is funded under a joint solicitation between the National Science Foundation and the National Institutes of Health, named "Smart and Connected Health" (SCH), which aims to accelerate the development and use of innovative approaches that would support the much needed transformation of healthcare across the entire population. The obesity epidemic is the primary cause of recent increases in heart disease, diabetes, cancer, and other diseases that place an untenable strain on healthcare and public health. One of the primary behavioral causes, i.e. dietary intake, is a behavior that science has had little success in understanding, much less affecting. Recent advances in remote sensing have provided a new paradigm for tracking human behavior, but obesity-related efforts focused directly on diet and activity have been hampered by not only the accuracy of behavior tracking (especially dietary intake) but also the lack of behavioral theories and dynamic models for personalized just-in-time, adaptive interventions (JITAIs). Current behavioral science suggests that family eating dynamics (FED) have high potential to impact child and parent dietary intake and obesity rates. The confluence of technology research and behavioral science research creates the opportunity to change the focus of in situ obesity research and intervention from behaviors that have proven difficult to monitor, model, and modify (e.g., what and how much is being eaten) to the family mealtime and home food environment (e.g., who is eating, when, where, with whom, interpersonal stress), providing opportunities for monitoring and modeling (M2) behavior via remote sensing, and the potential for successful behavior modification via personalized, adaptable, real-time feedback.This project proposes M2FED, an integrated system of in-home beacons, wireless and wearable sensors, and smartphones that collects synchronized real-time FED data that will be used to iteratively develop dynamic, contextualized FED systems models based on that data. The technology, ideographic models, and techniques to iteratively develop those models can guide future JITAIs and thus have a downstream positive impact on diet and ultimately obesity. The project brings together behavioral scientists, system scientists, obesity experts, computer scientists, and electrical engineers to address fundamental challenges of remote, continuous data capture for real-time behavior modeling for obesity prevention and treatment. Behavioral scientists traditionally have not had access to real-time data and dynamic models, while engineers have not had the expertise to identify what to monitor and model or what feedback to provide. This project connects complimentary expertise to develop a dramatically different approach to childhood obesity, focusing on behaviors, i.e. FED rather than diet, that can be more accurately monitored and modeled and have greater potential for positive and long-term modification. Fundamental technology research challenges in realizing the M2FED system include unique individual in-home localization, eating detection, conversation stress and mood assessment in reverberant environments, and a system-of-systems framework that includes heterogeneous sensing and communication systems across the family system itself. Fundamental behavioral research challenges include real-time modeling of FED based on past and ongoing observations of FED states and intra- and interpersonal states and events that create temporal and causal impact on FED. While this project is performed within the context of the obesity/FED relationship (which itself has the potential for sweeping impacts on human health and healthcare costs), the project also generalizes a framework, including both an evidence-based system and an experimental platform that extends to systems and applications beyond childhood obesity and behavior modification. The multidisciplinary nature of this work also provides new outreach and educational opportunities, informing (and being informed by) the public and preparing a workforce that is better equipped to address the fundamental human-behavior-centric challenges of health management and wellness preservation.

该项目是在国家科学基金会与美国国立卫生研究院（National Institutes of National Institutes of National Institutes of National Institutes）之间的共同招标下资助的，该研究名为“ Smart and Connected Health”（SCH），该项目旨在加速创新方法的发展和使用，这些方法将支持整个人群中医疗保健的急需转变。肥胖症流行是最近增加心脏病，糖尿病，癌症和其他疾病的主要原因，这些疾病对医疗保健和公共卫生产生了严重的压力。主要的行为原因之一，即饮食摄入，是科学在理解方面几乎没有成功的行为。遥感的最新进展为跟踪人类行为提供了新的范式，但是与肥胖相关的努力直接关注饮食和活动不仅受到行为追踪的准确性（尤其是饮食摄入量）的准确性（尤其是饮食摄入量），而且还缺乏为个性化的即时及时的动态模型，适应性的干预措施（Jitaiis）。当前的行为科学表明，家庭饮食动态（FED）具有影响儿童和父母饮食摄入量和肥胖率的高潜力。技术研究和行为科学研究的融合创造了机会，将原位肥胖研究和干预的重点从被证明难以监测，模型和修改（例如，正在食用的东西和饮食时间和家庭食物）上的行为（例如，在何时何时何时何时待命）进行远程和模型（MONTHEMENDERSIDE（例如），并建模（MOTEDSERTION，以及MENTERINGE）（MONDECE）的传感（MOTED）的传感器（例如），并建立了跨越的方式（通过个性化，适应性的实时反馈进行行为修改。本项目提出了M2FED，这是一个集成的室内信标，无线和可穿戴传感器的集成系统，以及智能手机，这些系统将收集基于该数据的动态，上下文化的FED系统，以收集用于迭代的动态，上下文化的FED系统。技术，思想模型和迭代开发这些模型的技术可以指导未来的Jitais，从而对饮食和最终肥胖产生下游积极的影响。该项目汇集了行为科学家，系统科学家，肥胖专家，计算机科学家和电气工程师，以应对针对预防肥胖和治疗的实时行为建模的远程，连续数据捕获的基本挑战。行为科学家传统上无法访问实时数据和动态模型，而工程师没有专业知识来确定要监视的内容和模型或提供什么反馈。该项目将免费的专业知识联系起来，以开发出截然不同的儿童肥胖方法，专注于行为，即喂养而不是饮食，可以更准确地监测和建模，并具有更大的积极和长期修改的潜力。实现M2FED系统的基本技术研究挑战包括在混响环境中进行独特的个人内部定位，饮食探测，对话压力和情绪评估，以及一个系统系统框架，其中包括整个家庭系统的异构传感和通信系统。基本的行为研究挑战包括基于过去和正在进行的人们观察到的美联储的实时建模，对美联储国家以及人际内和人际交往，以及对美联储产生时间和因果影响的事件。尽管该项目是在肥胖/美联储关系的背景下执行的（本身具有对人类健康和医疗保健成本产生影响的潜力），但该项目还概括了一个框架，包括循证系统和实验平台，该框架扩展到了儿童肥胖和行为修改以外的系统和应用程序。这项工作的跨学科性质还提供了新的外展和教育机会，向公众提供了信息（并得到通知），并为劳动力做准备，该劳动力有能力解决以人为行为以人为行为为基本的健康管理和健康保护和保健的挑战。