利用心电图谱域分析识别心脏缺血

R. Valupadasu, B. R. Chunduri
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引用次数: 1

摘要

印度是世界上心脏病发病率最高的国家。心脏病是所有慢性病中最可预测和最可预防的疾病,如果不采取行动控制这种疾病,到2015年印度将有6200万心脏病患者。心肌缺血(也称为心绞痛)是一种由心脏暂时缺乏富氧血液引起的心脏病。心脏缺血(CI)是一种心脏疾病,包括由动脉狭窄引起的心脏问题,动脉狭窄使缺氧的血液无法到达心脏肌肉。这可能会导致心脏病发作,没有事先警告。本文介绍了在区分正常健康人的心电图和缺血病人的心电图方面所做的工作。利用心电信号的快速傅里叶变换(FFT)提取信息,为心脏缺血易感信号提供依据。主要目的是设计一种算法,使医生能够根据心电信号的频谱分析来诊断心脏缺血。任何病人4分钟的心电图就足以检测出缺血的可能性。正常窦性心律数据来自MIT-BIH NSR数据库。缺血数据来源于欧洲ST-T数据库。数据采集周期为1小时。在MIT-BIH数据库和欧洲ST-T数据库上对算法进行了测试,并用MATLAB对结果进行了验证。这个概念可以用来分析心电信号,以识别其他心脏疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Cardiac Ischemia Using Spectral Domain Analysis of Electrocardiogram
India has highest incidence of heart related diseases in the world. If no initiative is taken to check the disease the most predictable and preventable among all chronic diseases, India will have 62 million heart patients by 2015. Myocardial ischemia (also known as angina) is a heart condition caused by a temporary lack of oxygen-rich blood to the heart. Cardiac ischemia (CI) is a heart disease that covers heart issues caused by narrowing of the arteries which makes less oxygenated blood to reach the heart muscle. This may lead to heart attack with no prior warning. This paper introduces the work that has been done to distinguish the Electrocardiogram (ECG) of a normal healthy human from that of an ischemia patient. Fast Fourier Transform (FFT) on ECG Signal was used to extract information and providing the basis with which a signal suggesting predisposition of the patient who suffers from Cardiac ischemia. The main aim is to design algorithm that enable the doctors to diagnose cardiac ischemia on the basis of spectral analysis of an ECG signal. 4 min. of ECG of any patient is enough to detect possibility of ischemia. Normal Sinus Rhythm Data is obtained from MIT-BIH NSR Database. Ischemia data is obtained from European ST-T Database. The data is taken for duration of 1 hour. The algorithm was tested on MIT-BIH database and European ST-T Database and the verification of results using MATLAB is done. This concept can be utilized to analyze ECG signals to identify other heart diseases.
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