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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zetao Lin Yaozheng Ge Guoliang Tao |
| Copyright Year | 2005 |
| Description | Author affiliation: State Key Lab. of Fluid Power Transmission & Control, Zhejiang Univ., Hangzhou (Zetao Lin; Yaozheng Ge; Guoliang Tao) |
| Abstract | To satisfy the difficult requirements of ECG analysis such as large data volume, high accuracy and real-time, a classification algorithm for arrhythmia based on clustering analysis is developed. According to things-of-one-kind-come-together principle, this algorithm uses the similarity of heart cases of the same category and, at the same time, incorporates the factor of individual differences. It analyzes arrhythmia by clustering QRS complex waveforms and applies rhythm analysis as the subordinate method. Verified by eight records of MIT-BIH arrhythmia standard heart electricity database, the clustering correct rate reaches above 90%, which shows that this algorithm can analyze arrhythmia effectively |
| Starting Page | 3857 |
| Ending Page | 3860 |
| File Size | 225940 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780387414 |
| DOI | 10.1109/IEMBS.2005.1615302 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-01-17 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Clustering algorithms Data analysis Algorithm design and analysis Electrocardiography Rhythm Heart rate Sequential analysis Low pass filters Databases Biomedical engineering QRS complex Algorithm Clustering analysis Arrhythmia similarity |
| Content Type | Text |
| Resource Type | Article |
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