ECG SOFTWARE TO DETECT ACUTE MYOCARDIAL INFARCTION

为了提高急性心肌梗死检测的准确性，提出了心电图机、心电图机、软件的发展。这项工作是基于R.塞尔维斯特博士和J·所罗门博士在计算机化心电图学领域的开创性工作。使用先进的心脏电生理计算机模型，我们建议创建一个丰富而健壮的合成心电信号数据库。这些合成的心电和来自长滩纪念心电数据库的学习子集的心电将被用于开发用于解释性心电算法的规则和标准。最终的解释算法将使用从纪念数据库中选择的大型测试子集进行测试。我们建议开发解释软件，与商业解释心电算法相比，该软件将显著改善急性心肌梗死的检测、定位和大小。我们预计，这一努力将显著改善患者护理，并降低与心脏病发作相关的医疗成本。建议的商业应用：心电是第一个在胸痛患者身上进行的测试。改进检测急性心肌梗死的心电软件将显著缩短治疗时间，增加限制或逆转心脏损害的机会。具有准确MI检测能力的基于ECG的设备的市场每年超过3亿美元。建议的软件可用于心电图仪、除颤器和急性护理监测设备。

The development of electrocardiograph, ECG, software is proposed to improve the accuracy of the detection of acute myocardial infarcts, AMIs. This effort is based on the pioneering work of Dr. R. Selvester and J. Solomon in the field of computerized electrocardiography. Using an advanced electrophysiological computer model of the heart, we propose to create a rich and robust database of synthetic ECG signals. A combination of these synthetic ECGs and ECGs from a learning subset of the Long Beach Memorial ECG database will be used to develop rules and criteria for use in an interpretive ECG algorithm. The resulting interpretive algorithm will be tested using a large test subset chosen from the Memorial database. We propose to develop interpretive software that will significantly improve the detection, location, and sizing of acute myocardial infarcts over that of commercial interpretive ECG algorithms. We expect that this effort will lead to significant improvement in patient care and reduced healthcare costs associated with heart attacks. PROPOSED COMMERCIAL APPLICATIONS: The ECG is the first test that is performed on a patient with chest pain. An improvement in ECG software to detect an acute MI would significantly reduce the time to therapy and increase the chance of limiting or reversing cardiac damage. The market for ECGs based equipment with accurate MI detection capability is over $300 million dollars annually. The proposed software could be used in electrocardiographs, defibriliators, and acute care monitoring equipment.