ECG waveform segmentation based on improved U-Net model(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2022年第10期
- Page:
- 1274-1279
- Research Field:
- 医学信号处理与医学仪器
- Publishing date:
Info
- Title:
- ECG waveform segmentation based on improved U-Net model
- Author(s):
- XU Bolin; CAI Wenjie; YANG Mingfei; ZHANG Biao
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
- Keywords:
- Keywords: electrocardiogram improved U-Net model algorithm verification segmentation
- PACS:
- R318；TP391
- DOI:
- DOI:10.3969/j.issn.1005-202X.2022.10.016
- Abstract:
- Abstract: A new algorithm based on U-Net framework is proposed for ECG waveform segmentation, taking the ECG signal of fixed length as the input, and then outputting the images of P wave, QRS wave and T wave. The method can locate the starting and ending points of each characteristic wave. A novel model structure of multi-channel dilated convolution with attention mechanism is put forward, and a data enhancement formula is designed to increase the diversity of data. The proposed method is trained and tested on LUDB, and the generalization ability of the algorithm is verified on QTDB. The experimental results show that the average sensitivity, average positive prediction rate, and average F1 score of the proposed algorithm are 99.41%, 98.90%, 98.75% on LUDB, and 98.65%, 98.43%, 98.23% on QTDB, indicating that the proposed algorithm performs better and has excellent generalization performance.
Last Update: 2022-10-27