首页> 外文OA文献 >PORTABLE HEART ATTACK WARNING SYSTEM BY MONITORING THE ST SEGMENT VIA SMARTPHONE ELECTROCARDIOGRAM PROCESSING
【2h】

PORTABLE HEART ATTACK WARNING SYSTEM BY MONITORING THE ST SEGMENT VIA SMARTPHONE ELECTROCARDIOGRAM PROCESSING

机译:通过智能电话心电图处理监测ST段的便携式心脏攻击预警系统

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Cardiovascular disease (CVD) is the single leading cause of death in both developed and developing countries. The most deadly CVD is heart attack, which 7,900,000 Americans suffer each year, and 16% of cases are fatal. The Electrocardiogram (ECG) is the most widely adopted clinical tool to diagnose and assess the risk of CVD. Early diagnosis of heart attacks, by detecting abnormal ST segments within one hour of the onset of symptoms, is necessary for successful treatment. In clinical settings, resting ECGs are used to monitor patients automatically. However, given the sporadic nature of heart attacks, it is unlikely that the patient will be in a clinical setting at the onset of a heart attack. While Holter-based portable monitoring solutions offer 24 to 48-hour ECG recording, they lack the capability of providing any real-time feedback for the thousands of heart beats they record, which must be tediously analyzed offline.Processing ECG signals on a smartphone-based platform would unite the portability of Holter monitors and the real-time processing capability of state-of-the-art resting ECG machines to provide an assistive diagnosis for early heart attack warning. Furthermore, smartphones serve as an ideal platform for telemedicine and alert systems and have a portable form factor. To detect heart attacks via ECG processing, a real-time, accurate, context aware ST segment monitoring algorithm, based on principal component analysis and a support vector machine classifier is proposed and evaluated. Real-time feedback is provided by implementing a state-of-the-art, multilevel warning system ranging from audible notifications to text messages to points of contacts with the GPS location of the user. The smartphone test bed makes use of a novel, real-time verification system using a streaming database to analyze the strain of heart attack detection system under normal phone operation. Furthermore, the entire system is prototyped and fully functional, running on a smartphone to demonstrate the real-time, portable functionality of the platform. Experimental results show that a classification accuracy of 96% for ST segment elevation of individual beats can be achieved and all ST episodes were correctly detected during testing with the European ST database.
机译:在发达国家和发展中国家,心血管疾病(CVD)都是唯一的死亡主要原因。最致命的CVD是心脏病发作,每年有790万美国人遭受心脏病的折磨,其中16%的病例是致命的。心电图(ECG)是诊断和评估CVD风险的最广泛采用的临床工具。要成功治疗,必须通过在症状发作后一小时内检测出异常的ST段来对心脏病发作进行早期诊断。在临床环境中,静息ECG用于自动监测患者。但是,由于心脏病发作是零星的,因此患者不太可能在心脏病发作时就处于临床环境中。虽然基于Holter的便携式监控解决方案可以提供24至48小时的ECG记录,但它们无法为所记录的数千个心跳提供任何实时反馈,因此必须离线进行繁琐的分析。基于该平台的设备将Holter监护仪的便携性与最先进的静息ECG机器的实时处理能力结合在一起,为早期心脏病发作预警提供辅助诊断。此外,智能手机是远程医疗和警报系统的理想平台,并且具有可移植的外形。为了通过ECG处理检测心脏病发作,提出并评估了基于主成分分析和支持向量机分类器的实时,准确,上下文相关的ST段监视算法。实时反馈是通过实施最新的多级警告系统提供的,范围从声音通知,文本消息到与用户GPS位置的接触点。智能手机测试台利用新颖的实时验证系统,该系统使用流数据库来分析正常电话操作下心脏病发作检测系统的压力。此外,整个系统已原型化并具有完整功能,可在智能手机上运行,​​以演示平台的实时,便携式功能。实验结果表明,在使用欧洲ST数据库进行测试的过程中,单个节拍的ST段抬高可以达到96%的分类准确度,并且可以正确检测到所有ST发作。

著录项

  • 作者

    Oresko Joseph John;

  • 作者单位
  • 年度 2010
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号