mDOT TR&D3 (Translation): Translation of Temporally Precise mHealth via Efficient and Embeddable Privacy-aware Biomarker Implementations

mDOT TR

• 批准号: 10541810
• 负责人: Emre Ertin
• 金额: $ 28.14万
• 依托单位: UNIVERSITY OF MEMPHIS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10541810
• 关键词: Address; Algorithms; Architecture; Awareness; Behavioral; Biological Markers; Cellular Phone; Chronic Disease; Clinic; Cloud Computing; Collaborations; Collection; Communication; Communities; Companions; Computational Technique; Computer software; Computing Methodologies; Data; Data Collection; Development; Devices; Digital biomarker; Disease Outcome; Eating; Ensure; Fatigue; Feedback; Frequencies; Generations; Health; Healthcare; Image; Individual; Infrastructure; Intelligence; Intervention; Lead; Life; Life Cycle Stages; Machine Learning; Medical; Medicine; Metadata; Methodology; Methods; Modality; Motion; Noise; Observational Study; Ohio; Participant; Patients; Personally Identifiable Information; Physiological; Physiology; Principal Investigator; Privacy; Research; Research Activity; Research Design; Research Personnel; Resource-limited setting; Resources; Risk; Running; Sampling; Services; Side; Signal Transduction; Smoking; Software Design; Stream; Stress; Structure; System; Technology; Time; Training; Translations; Trust; Universities; Work; biopsychosocial; cloud platform; craving; data reduction; data sharing; denoising; design; healthy lifestyle; high dimensionality; improved; mHealth; machine learning algorithm; mobile computing; multiple chronic conditions; next generation; open source; point of care; prevent; prototype; public health relevance; radio frequency; reconstruction; research study; sensor; signal processing; software development; synergism; technological innovation; technology research and development; tool; usability; wearable device; wearable platform; wearable sensor technology

Principal Investigator: Kumar, Santosh TR&D3: Translation of Temporally Precise mHealth via Efficient and Embeddable Privacy-aware Biomarker Implementations Lead: Dr. Emre Ertin, The Ohio State University; 10% effort (1.2 CM) Abstract: The mHealth Center for Discovery, Optimization & Translation of Temporally-Precise Interventions (the mDOT Center) will enable a new paradigm of temporally-precise medicine to maintain health and manage the growing burden of chronic diseases. The mDOT Center will develop and disseminate the methods, tools, and infrastructure necessary for researchers to pursue the discovery, optimization and translation of temporally- precise mHealth interventions. Such interventions, when dynamically personalized to the moment-to-moment biopsychosocial-environmental context of each individual, will precipitate a much-needed transformation in healthcare by enabling patients to initiate and sustain the healthy lifestyle choices necessary for directly managing, treating, and in some cases even preventing the development of medical conditions. Organized around three Technology Research & Development (TR&D) projects, mDOT represents a unique national resource that will develop multiple methodological and technological innovations and support their translation into research and practice by the mHealth community in the form of easily deployable wearables, apps for wearables and smartphones, and a companion mHealth cloud system, all open-source. TR&D3 will develop, validate and disseminate algorithms, tools and software/hardware designs for translation of temporally-precise mHealth interventions through resource efficient, real time, low-latency and privacy-aware implementation of an array of digital biomarkers that can be deployed at scale. Our approach is centered around a hierarchical computing framework that reduces the data into minimal modular abstractions called Micromarkers computed at the edge devices (Aim 1). Modular Micromarker abstractions are used to compress task-specific information relevant to biomarker computations at the edge devices while stripping nuisance variables such as hardware biases/drifts and background levels not pertinent to inference. Our hierarchical computing framework can be extended to implement high data rate sensor arrays at edge devices to be used at new point of care and ambulatory settings. This is accomplished through integrating a compressive sensing pre-processor to achieve signal acquisition in a resource constrained setting (Aim 2). Finally, TR&D3 will create computational mechanisms and a general biomarker privacy framework to enable participant control over the privacy-utility trade-offs during study design, data collection, and sharing of collected mHealth data for third party research when data cross trust domains (Aim 3). These technologies will be developed in collaboration with collaborative projects and will be disseminated to service projects to ensure that TR&D3 technologies can solve real problems facing the health research community and ensure the usability of these technologies by investigators who are external to the mDOT investigating team. TR&D3 will synergistically work in partnership with the other TR&D projects, the Training and Dissemination Core, and the Administration Core to maximize the societal impact of TR&D3 technologies. 1

首席研究员：库马尔，桑托什 TR&D3：通过高效且可嵌入的隐私意识实现时间精确的移动医疗 生物标记实施 负责人：Emre Ertin 博士，俄亥俄州立大学； 10% 努力 (1.2 CM) 摘要：移动医疗中心用于发现、优化和转化时间精确干预措施 （mDOT 中心）将实现时间精确医学的新范式，以维持健康和管理 慢性病负担日益加重。 mDOT 中心将开发和传播方法、工具、 以及研究人员追求时间发现、优化和翻译所必需的基础设施 精准的移动医疗干预。当这种干预措施根据时时刻刻进行动态个性化时 每个人的生物心理社会环境背景，将促成急需的转变 通过使患者能够启动并维持直接健康所需的健康生活方式选择来实现医疗保健 管理、治疗，在某些情况下甚至预防疾病的发展。有组织 mDOT 围绕三个技术研发 (TR&D) 项目代表了独特的国家 将开发多种方法和技术创新并支持其翻译的资源 移动医疗社区以易于部署的可穿戴设备、应用程序的形式参与研究和实践 可穿戴设备和智能手机，以及配套的 mHealth 云系统，全部都是开源的。 TR&D3 将开发、验证和传播用于翻译的算法、工具和软件/硬件设计 通过资源高效、实时、低延迟和隐私意识实现时间精确的移动医疗干预 实施一系列可大规模部署的数字生物标记。我们的方法围绕 一种分层计算框架，可将数据简化为称为微标记的最小模块化抽象 在边缘设备上计算（目标 1）。模块化微标记抽象用于压缩特定于任务的 与边缘设备上的生物标记计算相关的信息，同时去除诸如 硬件偏差/漂移和背景水平与推理无关。我们的分层计算框架 可以扩展以在边缘设备上实现高数据速率传感器阵列，以用于新的护理点和 流动设置。这是通过集成压缩传感预处理器来实现的 资源受限环境中的信号采集（目标 2）。最后，TR&D3 将创建计算 机制和通用生物标记隐私框架，使参与者能够控制隐私实用程序 研究设计、数据收集以及为第三方研究共享收集的移动医疗数据期间的权衡 当数据跨信任域时（目标 3）。 这些技术将与合作项目合作开发，并将传播给 确保TR&D3技术能够解决健康研究面临的实际问题的服务项目 社区并确保 mDOT 外部的调查人员可以使用这些技术 调查组。 TR&D3 将与其他 TR&D 项目、培训和 传播核心和管理核心，以最大限度地发挥 TR&D3 技术的社会影响。 1