SCH: INT: Mapping the Cardiac Acousteome: Biosensing and Computational Modeling Applied to Smart Diagnosis and Monitoring of Heart Conditions

SCH：INT：绘制心脏声学组图：生物传感和计算模型应用于心脏病的智能诊断和监测

• 批准号: 1344772
• 负责人: Rajat Mittal
• 金额: $ 198.05万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-12-01 至 2018-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1344772&HistoricalAwards=false
• 关键词: SCH; INT; Mapping; Cardiac; Acousteome

The goal of the project is to develop fundamental science, knowledge, tools, and technologies for smart diagnosis and monitoring of heart conditions based on automated cardiac auscultation. An innovative wearable multimodal acoustic array (the StethoVest) is proposed. This sensory array localizes and separates acoustic broadband sources in space by measuring spatial and temporal derivatives of the acoustic field. Using this StethoVest, first-of-their-kind maps of the cardiac acousteome are generated. These maps include not only 4D (3D space and time) measurements of heart sounds; they are accompanied by high-fidelity hemoacoustic simulations that delineate cause-and-effect, as well as simulation-guided source-identification algorithms that provide unprecedented diagnostic sensitivity and specificity. The simulations take cardiac imaging data as input, and simulate cardiac blood flow as well as the associated heart sounds. The latter part of this four-year project focuses on investigating the physics of aortic valve murmurs as well as StethoVest based screening for hypertrophic obstructive cardiomyopathy. Annual national expenditure on heart disease exceeds half a trillion dollars with over half a million deaths attributed to this disease each year. The proposed research leverages emerging capabilities in biosensing, computational modeling, imaging and signal processing, to produce a diagnostic technology that moves us away from management of heart disease that is mostly reactive, expensive and hospital-centric, towards an approach that is smart, proactive, patient-centric and cost-effective. The sound inventory generated from continuous, automated monitoring and interpretation of heart sounds has the potential to generate unprecedented understanding of human physiology. The project promotes interdisciplinary education and workforce development through involvement of undergraduates, graduate students, and postdocs in the research, development of courses and clinical training tools, and local and international outreach activities.

该项目的目的是开发基于自动化心理学的智能诊断和监测心脏状况的基础科学，知识，工具和技术。提出了创新的可穿戴多模式声学阵列（stethovest）。该感觉阵列通过测量声场的空间和时间衍生物来定位并分离空间中的声学宽带源。使用这种stethovest，产生了心脏大声疾病的第一届地图。 这些地图不仅包括4D（3D空间和时间）的心脏声音测量；它们伴随着描述因果的高保真性血声音模拟，以及模拟引导的源识别算法，这些算法提供了前所未有的诊断敏感性和特异性。模拟将心脏成像数据作为输入，并模拟心脏血流以及相关的心脏声音。该四年项目的后半部分着重于研究主动脉瓣杂音的物理学以及基于肥大性阻塞性心肌病的筛查。每年的全国性心脏病支出超过半百万美元，每年归因于该病的半百万次死亡。拟议的研究利用了在生物传感，计算建模，成像和信号处理中的新兴能力，以产生一种诊断技术，使我们摆脱了心脏病的管理，这种技术主要是反应性，昂贵且以医院为中心的，朝着一种智能，积极主动，积极主动，以患者为中心，以患者为中心和成本效益的方法。通过对心脏声音的连续，自动监测和解释产生的声音清单有可能产生对人类生理学的前所未有的理解。该项目通过参与本科生，研究生和博士后参与研究，课程开发和临床培训工具以及本地和国际外展活动，从而促进跨学科的教育和劳动力发展。