Development of a Pre-Hospital Ultra-Wide Band Radar Cardiac Function Monitor
院前超宽带雷达心功能监测仪的研制
基本信息
- 批准号:7273954
- 负责人:
- 金额:$ 14.7万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2007
- 资助国家:美国
- 起止时间:2007-06-01 至 2009-05-30
- 项目状态:已结题
- 来源:
- 关键词:AffectAlgorithmsAnestheticsAnimal ModelAnimalsApplications GrantsArrhythmiaArtificial HeartBlood PressureBradycardiaCardiacCardiopulmonary ResuscitationCaregiversCaringCause of DeathCharacteristicsChestClothingComputer Systems DevelopmentDataDetectionDevelopmentDevicesEducational process of instructingElectrocardiogramFamily suidaeGuidelinesHandHealth PersonnelHeartHeart ArrestHeart RateHospitalsHumanInvasiveLaboratory AnimalsLocationLogistic RegressionsMeasuresMechanicsMedicalMedical DeviceMonitorMotionOrganOutputPalpablePatientsPerformancePhasePhysiologic pulsePositioning AttributePulse takingRadarRangeRateReceiver Operator CharacteristicsResuscitationRight ventricular structureSense OrgansSignal TransductionSpecificitySternumStroke VolumeSystemTachycardiaTechniquesTestingTimeTraumaUnited StatesVentricular Fibrillationatrioventricular nodebasecomputerized data processingcostfetalheart motionimprovedmortalityprototypereceptorsensorsoftware development
项目摘要
DESCRIPTION (provided by applicant): Cardiac arrest is a leading cause of death in the United States. Despite 40 years of teaching resuscitation techniques and pre-hospital system development to provide pre-hospital medical care rapidly, mortality remains high. It has recently been recognized that not performing chest compressions for relatively short periods of time during resuscitation may be responsible for a significant percentage of the high mortality. Resuscitation guidelines call for the stopping of chest compressions for the determination of the presence or absence of a carotid pulse by healthcare personnel when performing cardiopulmonary resuscitation, yet performance of pulse checks is time consuming and the results are often incorrect. LifeWave has developed an ultra-wideband radar sensor capable of detecting cardiac motion. We propose to develop the software algorithms that will allow this device to quickly determine whether or not a patient's cardiac motion is consistent with a palpable carotid pulse. This Phase 1 grant application has 2 specific aims: 1) Develop an algorithm that uses LifeWave's ultra-wideband radar signal to differentiate between the presence and absence of mechanical heart motion equivalent to the presence or absence of a palpable carotid pulse. We will use the radar sensor to record from animals with a range of heart rates and levels of cardiac contractility. We will use signal processing and statistical techniques to develop an algorithm that identifies whether or not the amount of cardiac motion present is consistent with the presence of a palpable carotid pulse (systolic blood pressure > 60 mmHg). We hypothesize that we will be able to differentiate between the presence and absence of a carotid pulse with 95% sensitivity and 70% specificity from 5 seconds of recorded data. 2) Show that the combination of the LifeWave medical radar and the signal processing algorithm developed in specific aim 1 can determine the mechanical heart motion associated with the presence or absence of a palpable carotid pulse during resuscitation of an animal model of sudden cardiac arrest. We hypothesize that by using the algorithm developed in specific aim 1, we will be able to differentiate between the presence and absence of a palpable carotid pulse with 95% sensitivity and 70% specificity from 5 seconds of data recording. Accomplishment of these two specific aims will show the ability of our ultra-wideband radar device to detect cardiac motion during resuscitation from cardiac arrest and prepare us for a phase II application and the development of a stand-alone radar monitor. Cardiac arrest is a leading cause of death in the United States. Despite 40 years of teaching resuscitation techniques and pre-hospital system development to provide pre-hospital medical care rapidly, mortality remains high. We propose to develop a radar-based pulse detection device that will decrease the amount of time spent performing pulse checks during resuscitation and not spent performing chest compressions. We hope that this device will improve survival following cardiac arrest.
描述(由申请人提供):心脏骤停是美国的主要死因。尽管40年来一直在教授复苏技术和院前系统发展,以迅速提供院前医疗护理,但死亡率仍然很高。最近已经认识到,在复苏期间相对短的时间内不进行胸部按压可能是造成高死亡率的显著原因。复苏指南要求医护人员在进行心肺复苏时停止胸外按压以确定颈动脉脉搏的存在或不存在,但是脉搏检查的执行是耗时的并且结果通常是不正确的。LifeWave开发了一种能够检测心脏运动的超宽带雷达传感器。我们建议开发软件算法,使该设备能够快速确定患者的心脏运动是否与可触及的颈动脉脉搏一致。该第一阶段拨款申请有两个具体目标:1)开发一种算法,该算法使用LifeWave的超宽带雷达信号来区分机械心脏运动的存在和不存在,相当于存在或不存在可触及的颈动脉脉搏。我们将使用雷达传感器记录动物的心率和心脏收缩力水平。我们将使用信号处理和统计技术来开发一种算法,该算法可以识别存在的心脏运动量是否与可触及的颈动脉脉搏(收缩压> 60 mmHg)的存在一致。我们假设,我们将能够区分颈动脉搏动的存在和不存在,从5秒的记录数据中具有95%的灵敏度和70%的特异性。2)证明LifeWave医用雷达和特定目标1中开发的信号处理算法的组合可以确定与心脏骤停动物模型复苏期间存在或不存在可触及颈动脉脉搏相关的机械心脏运动。我们假设,通过使用特定目标1中开发的算法,我们将能够从5秒的数据记录中区分可触及颈动脉脉搏的存在和不存在,灵敏度为95%,特异性为70%。这两个具体目标的实现将显示我们的超宽带雷达设备在心脏骤停复苏过程中检测心脏运动的能力,并为第二阶段应用和独立雷达监测器的开发做好准备。在美国,心脏骤停是导致死亡的主要原因。尽管40年来一直在教授复苏技术和院前系统发展,以迅速提供院前医疗护理,但死亡率仍然很高。我们建议开发一种基于雷达的脉搏检测设备,该设备将减少在复苏期间执行脉搏检查所花费的时间,而不是执行胸外按压。我们希望这个装置能提高心脏骤停后的存活率。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
GREGORY P WALCOTT其他文献
GREGORY P WALCOTT的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('GREGORY P WALCOTT', 18)}}的其他基金
Effect of Pulmonary Vasodilation on the Efficacy of Cardiopulmonary Resuscitation
肺血管扩张对心肺复苏效果的影响
- 批准号:
8197940 - 财政年份:2010
- 资助金额:
$ 14.7万 - 项目类别:
Effect of Pulmonary Vasodilation on the Efficacy of Cardiopulmonary Resuscitation
肺血管扩张对心肺复苏效果的影响
- 批准号:
8047914 - 财政年份:2010
- 资助金额:
$ 14.7万 - 项目类别:
Defibrillation mechanisms during ischemic arrhythmias
缺血性心律失常期间的除颤机制
- 批准号:
6630622 - 财政年份:2002
- 资助金额:
$ 14.7万 - 项目类别:
Defibrillation of Ischemic Ventricular Fibrillation
缺血性心室颤动的除颤
- 批准号:
6537709 - 财政年份:2001
- 资助金额:
$ 14.7万 - 项目类别:
Defibrillation of Ischemic Ventricular Fibrillation
缺血性心室颤动的除颤
- 批准号:
6727538 - 财政年份:2001
- 资助金额:
$ 14.7万 - 项目类别:
Defibrillation of Ischemic Ventricular Fibrillation
缺血性心室颤动的除颤
- 批准号:
6333860 - 财政年份:2001
- 资助金额:
$ 14.7万 - 项目类别:
Defibrillation of Ischemic Ventricular Fibrillation
缺血性心室颤动的除颤
- 批准号:
6638579 - 财政年份:2001
- 资助金额:
$ 14.7万 - 项目类别:
Defibrillation mechanisms during ischemic arrhythmias
缺血性心律失常期间的除颤机制
- 批准号:
7121203 - 财政年份:
- 资助金额:
$ 14.7万 - 项目类别:
相似海外基金
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
- 批准号:
2337776 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
- 批准号:
2338816 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
- 批准号:
2338846 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
- 批准号:
2348261 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
- 批准号:
2348346 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
- 批准号:
2348457 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
- 批准号:
2404989 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
- 批准号:
2339310 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
- 批准号:
2339669 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Continuing Grant
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
- 批准号:
EP/Y029089/1 - 财政年份:2024
- 资助金额:
$ 14.7万 - 项目类别:
Research Grant














{{item.name}}会员




