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

主要研究者：Kumar，Santosh TR&D3：通过高效和可嵌入的隐私感知转换时间精确的mHealth 生物标志物实施 负责人：俄亥俄州州立大学的Emre Ertin博士; 10%的努力（1.2 CM） 摘要：移动健康中心致力于发现、优化和翻译时间精确的干预措施 (the mDOT中心）将使一个新的模式，时间精确的医学，以保持健康和管理 慢性病日益加重的负担。mDOT中心将开发和传播方法，工具， 和基础设施所需的研究人员追求的发现，优化和翻译的时间- 精准的移动健康干预措施。这种干预，当动态个性化的时刻到时刻， 每个人的生物心理社会环境背景，将促成一个急需的转变， 通过使患者能够启动和维持健康的生活方式的选择， 管理，治疗，在某些情况下甚至防止医疗条件的发展。有组织 围绕三个技术研究与开发（TR&D）项目，mDOT代表了一个独特的国家 资源，将开发多种方法和技术创新，并支持其翻译 移动健康社区以可轻松部署的可穿戴设备、 可穿戴设备和智能手机，以及配套的mHealth云系统，全部开源。 TR&D3将开发，验证和传播算法，工具和软件/硬件设计，用于翻译 通过资源高效、真实的时间、低延迟和隐私感知，实现时间精确的移动医疗干预 实现了可以大规模部署的数字生物标志物阵列。我们的方法围绕 一个分层计算框架，将数据简化为称为Micromarks的最小模块抽象 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 与边缘设备处的生物标志物计算相关的信息，同时剥离干扰变量， 硬件偏差/漂移和背景电平与推断无关。我们的分层计算框架 可以扩展到在边缘设备处实现高数据速率传感器阵列，以用于新的护理点， 门诊设置。这是通过集成压缩感测预处理器来实现的。 在资源受限设置中的信号捕获（目标2）。最后，TR&D3将创建计算 机制和通用生物标志物隐私框架，以使参与者能够控制隐私实用程序 在研究设计、数据收集和为第三方研究共享所收集的mHealth数据期间进行权衡 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，并将传播到 服务项目，以确保TR&D3技术能够解决卫生研究所面临的真实的问题 社区，并确保这些技术的可用性的调查谁是外部的mDOT 调查队。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