Acute Inferior Myocardial Infarction Detection Algorithm Based on BiLSTM Network of Morphological Feature Extraction

Wenchang XU; Wenming HE; Binquan YOU; Yu GUO; Kaicheng HONG; Yuhang CHEN; Suling XU; Xiaohe CHEN

doi:10.11999/JEIT200480

Volume 43 Issue 9

Sep. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(9): 2561-2568

Wenchang XU, Wenming HE, Binquan YOU, Yu GUO, Kaicheng HONG, Yuhang CHEN, Suling XU, Xiaohe CHEN. Acute Inferior Myocardial Infarction Detection Algorithm Based on BiLSTM Network of Morphological Feature Extraction[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2561-2568. doi: 10.11999/JEIT200480

Citation:

Wenchang XU, Wenming HE, Binquan YOU, Yu GUO, Kaicheng HONG, Yuhang CHEN, Suling XU, Xiaohe CHEN. Acute Inferior Myocardial Infarction Detection Algorithm Based on BiLSTM Network of Morphological Feature Extraction[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2561-2568. doi: 10.11999/JEIT200480

Citation:

Wenchang XU, Wenming HE, Binquan YOU, Yu GUO, Kaicheng HONG, Yuhang CHEN, Suling XU, Xiaohe CHEN. Acute Inferior Myocardial Infarction Detection Algorithm Based on BiLSTM Network of Morphological Feature Extraction[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2561-2568. doi: 10.11999/JEIT200480

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Acute Inferior Myocardial Infarction Detection Algorithm Based on BiLSTM Network of Morphological Feature Extraction

doi: 10.11999/JEIT200480 cstr: 32379.14.JEIT200480

1.
Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science, Suzhou 215163, China
2.
The Affiliated Hospital of Medical School, Ningbo University, Ningbo 315211, China
3.
Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou 215021, China

Funds: The National Key Research and Development Project (2017YFC1001803), The Major Science and Technology Program for Medicine and Health in Zhejiang Province (WKJ-ZJ-2012)

Received Date: 2020-06-15
Rev Recd Date: 2020-12-16

Available Online: 2021-01-05

Publish Date: 2021-09-16

Abstract

Abstract

Acute inferior myocardial infarction is a kind of heart disease with rapid progression and high mortality. In order to improve the diagnosis efficiency for inferior myocardial infarction, a novel algorithm for automatic detection of inferior myocardial infarction based on Bi-directional Long Short-Term Memory (BiLSTM) network of morphological feature extraction is proposed. Based on the clinical ECG signals of the cardiology center, noise is reduced and every heartbeat is segmented. According to the cardiology clinical guidelines and signal analysis, 12 lead waveform distance features and single lead waveform amplitude features are extracted. Additionally, the neural network structure of Long Short-Term Memory (LSTM) and BiLSTM are built from to the extracted features. It is cross-validated by Physikalisch-Technische Bundesanstalt (PTB) public database and chest pain center database, the accuracy reaches 99.72%, the precision and sensitivity reach 99.53% and 100%. At the same time, the F1-Score reaches 99.76. Furthermore, experimental results demonstrated that the accuracy of the novel algorithm is still 1% higher than that of other existing algorithms after adding the chest pain center database.
- Electrocardiogram,
- Artificial intelligence,
- Bidirectional Long Short-Term Memory (LSTM) neural network,
- Morphological feature,
- Miocardial infarction

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References(19)

References

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