Markov transfer field combined with modified MobileNetV2 for arrhythmia classification(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2023年第11期
- Page:
- 1395-1401
- Research Field:
- 医学信号处理与医学仪器
- Publishing date:
Info
- Title:
- Markov transfer field combined with modified MobileNetV2 for arrhythmia classification
- Author(s):
- JI Changpeng; DENG Wei; DAI Wei
- School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, China
- Keywords:
- cardiac arrhythmia Markov transfer field MobileNetV2 two-dimensional image attention mechanism
- PACS:
- R318；TP391
- DOI:
- DOI:10.3969/j.issn.1005-202X.2023.11.013
- Abstract:
- The automatic arrhythmia classification is critical for cardiovascular disease prevention. An approach for arrhythmia classification based on Markov transfer field (MTF) and modified MobileNetV2 network is presented. After preprocessing and data enhancement for the original electrocardiogram (ECG) signals, MTF maps the processed ECG segments into two-dimensional images with temporal correlation, and then a modified MobileNetV2 network which incorporates with efficient channel attention classifies the ECG signals of 4 types: normal beat, left bundle-branch block, right bundle-branch block, and paced beat. The results show that the modified MobileNetV2 is slightly more complex than the original MobileNetV2, and it has a classification accuracy of 99.71%, which is 0.89% higher than the original MobileNetV2, demonstrating that the proposed approach can achieve the effective arrhythmia classification.
Last Update: 2023-11-24