• 智能计算 •

### 基于小波变换和粗糙集的早搏信号识别算法

1. 电子科技大学数学科学学院 成都611731;四川师范大学数学与软件科学学院 成都610068,电子科技大学数学科学学院 成都611731,四川省医学科学院心内科 成都610072
• 出版日期:2018-11-14 发布日期:2018-11-14
• 基金资助:
本文受四川师范大学科研项目(13KYL15),国家自然科学基金(61203285)资助

### Premature Beat Signal Recognition Algorithm Based on Wavelet Transform and Rough Set

TANG Xiao, SHU Lan and ZHENG Wei

• Online:2018-11-14 Published:2018-11-14

Abstract: The selection and extraction of electrocardiogram feature parameter are the base of the analysis of electrocardiogram(ECG).To improve recognition rate of detection algorithm and classification accuracy is the key to automatic analysis technology.Thus,a hybrid algorithm based on wavelet transform(WT) and attribute reduction of granular computing(GC) to detect premature beat signal of electrocardiogram(ECG) was present.At first,12 electrocardiogram feature parameters are chosen based on diagnostic criteria from cardiovascular experts.Then the feature detection algorithm based on wavelet transform is used for feature extraction,and an attribute reduction algorithm based on granular computing is also used for attribute reduction.Finally,the data are put into pattern classification and the result is verified by MIT-BIH database.As the experiment shows,the classification accuracy after reduction is much higher than it before reduction.Therefore,that reasonable selection of feature parameter is an important factor to improve the recognition efficiency was justified in this article.

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