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一种通过隐马尔可夫模型确定心肌缺血的方法。

An approach to determine myocardial ischemia by hidden Markov models.

作者信息

Tang Xiaoying, Xia Li, Liu Weifeng, Peng Yuhua, Gao Tianxin, Zeng Yanjun

机构信息

School of Life Science and Technology, Beijing Institute of Technology, Beijing 100081, P.R. China.

出版信息

Comput Methods Biomech Biomed Engin. 2012;15(10):1065-70. doi: 10.1080/10255842.2011.570341. Epub 2012 Jan 23.

Abstract

A hidden Markov model (HMM) of electrocardiogram (ECG) signal is presented for detection of myocardial ischemia. The time domain signals that are recorded by the ECG before and during the episode of local ischemia were pre-processed to produce input sequences, which is needed for the model training. The model is also verified by test data, and the results show that the models have certain function for the detection of myocardial ischemia. The algorithm based on HMM provides a possible approach for the timely, rapid and automatic diagnosis of myocardial ischemia, and also can be used in portable medical diagnostic equipment in the future.

摘要

提出了一种用于检测心肌缺血的心电图(ECG)信号隐马尔可夫模型(HMM)。对局部缺血发作之前和期间由心电图记录的时域信号进行预处理以生成输入序列,这是模型训练所需要的。该模型也通过测试数据进行了验证,结果表明这些模型对心肌缺血检测具有一定作用。基于HMM的算法为心肌缺血的及时、快速和自动诊断提供了一种可能的方法,并且未来还可用于便携式医疗诊断设备。

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