An approach to determine myocardial ischemia by hidden Markov models

Xiaoying Tang; L. Xia; Weifeng Liu; Yuhua Peng; Tianxin Gao; Yanjun Zeng

doi:10.1080/10255842.2011.570341

An approach to determine myocardial ischemia by hidden Markov models

Xiaoying Tang, L. Xia, Weifeng Liu, Yuhua Peng^*, Tianxin Gao, Yanjun Zeng

^*Corresponding author for this work

School of Medical and Technology

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

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.

Original language	English
Pages (from-to)	1065-1070
Number of pages	6
Journal	Computer Methods in Biomechanics and Biomedical Engineering
Volume	15
Issue number	10
DOIs	https://doi.org/10.1080/10255842.2011.570341
Publication status	Published - Oct 2012

Keywords

feature extraction
hidden Markov models
model training
myocardial ischemia

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10.1080/10255842.2011.570341

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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.",

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author = "Xiaoying Tang and L. Xia and Weifeng Liu and Yuhua Peng and Tianxin Gao and Yanjun Zeng",

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AU - Tang, Xiaoying

AU - Xia, L.

AU - Liu, Weifeng

AU - Peng, Yuhua

AU - Gao, Tianxin

AU - Zeng, Yanjun

PY - 2012/10

Y1 - 2012/10

N2 - 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.

AB - 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.

KW - feature extraction

KW - hidden Markov models

KW - model training

KW - myocardial ischemia

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JO - Computer Methods in Biomechanics and Biomedical Engineering

JF - Computer Methods in Biomechanics and Biomedical Engineering

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An approach to determine myocardial ischemia by hidden Markov models

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Keywords

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