BIGDATA: Modeling Simulation and Visulization for Medical Device Design

BIGDATA：医疗设备设计的建模仿真和可视化

• 批准号: 8655231
• 负责人: Daniel F Keefe
• 金额: $ 7.47万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8655231
• 关键词: Adopted; Area; Automobile Driving; Basic Science; Biological Sciences; Biomedical Engineering; Biomedical Technology; Biopsy; Cardiac; Complex; Computer Simulation; Computing Methodologies; Coupling; Data; Data Analyses; Data Set; Devices; Engineering; Future; Generations; Health; Human; Imagery; Medical Device; Medical Device Designs; Medical Imaging; Methods; Mission; National Institute of Biomedical Imaging and Bioengineering; Public Health; Research; Science; Scientist; Testing; Touch sensation; User-Computer Interface; Vacuum; Work; base; computerized tools; design; improved; insight; models and simulation; public health relevance; simulation; tool; virtual

DESCRIPTION (provided by applicant): The long-term objectives of this project are to enable a paradigm-shifting future for simulation-based engineering with big data and to demonstrate this future through specific applications to challenging problems in medical device design. The approach is to couple the valuable and intense amounts of medical imaging, physical simulation, and other life sciences data that are generated today with new computational tools that not only support automated data analysis but also powerfully leverage our own human capabilities to see, touch, explore, and analyze. The potential impact on health is profound. By adopting a human- centric approach to big data science, including significant new research in the areas of data visualization and human-computer interfaces, the work is expected to not only accelerate basic research and discovery but also make the results of big data science accessible to doctors, medical device engineers, and countless other creative thinkers who do not necessarily have a core background in computational methods. There are three specific aims: (1) Advancing medical device engineering through applications of new data- intensive design tools; (2) Developing a creative new as-direct-as-possible inverse method for simulation- based engineering; and (3) Coupling data-intensive virtual design with new tangible tools for working with big data. These aims are relevant to the mission of NIBIB. Public health will be improved by developing advanced biomedical technologies that radically improve the abilities of scientists, engineers, and doctors to move from data to insight as they work with vast, complex health datasets. The research will be applied to two driving medical device engineering problems: design of cardiac leads and design of vacuum assisted biopsy devices. The work is likely to result in new design insights for these devices. More importantly, the new data-intensive design methods and tools developed are expected to generalize to many other big data bioengineering problems, illuminating a path toward a new generation of data-intensive simulation-based engineering tools for improving public health by creating safer and more effective medical devices.

描述（由申请人提供）：该项目的长期目标是为基于大数据的基于模拟的工程提供范式转换未来，并通过针对医疗设备设计中挑战性问题的特定应用来证明这一未来。这种方法是将有价值的医学成像，物理模拟和其他生命科学数据与新的计算工具一起生成，这些工具不仅支持自动数据分析，而且还强大地利用了我们自己的人类能力来观察，触摸，探索和分析。对健康的潜在影响是深远的。通过对大数据科学采用以人为本的方法，包括在数据可视化领域和人力计算机界面领域的重大研究，预计这项工作不仅可以加速基础研究和发现，而且还可以使医生，医疗设备工程师以及其他无需在计算方法中具有核心背景的大数据科学的结果访问。 有三个特定的目标：（1）通过应用新数据密集型设计工具的应用来推进医疗设备工程； （2）为基于模拟的工程开发一种创造性的新AS-Direct-direct-trive-torvewers方法； （3）将数据密集型虚拟设计与用于使用大数据合作的新工具耦合。这些目标与尼比布的使命有关。通过开发先进的生物医学技术，从根本上提高了科学家，工程师和医生的能力，可以改善公共卫生。这项研究将应用于两个驾驶医疗器械工程问题：心脏导线的设计和真空辅助活检设备的设计。这项工作可能会为这些设备提供新的设计见解。更重要的是，新的数据密集型 预计开发的设计方法和工具将推广到许多其他大数据生物工程问题，从而通过创建更安全，更有效的医疗设备来阐明新一代基于数据密集型模拟的工程工具，以改善公共卫生。