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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Weichao Xu Chunqi Chang Hung, Y.S. Fung, P. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Electr. & Electron. Eng., Hong Kong Univ., Kowloon (Weichao Xu; Chunqi Chang; Hung, Y.S.) |
| Abstract | Atrial fibrillation (AF) is a type of abnormal heart rhythm exhibiting rapid and irregular patterns. Quantifying the extent of organization (regularity) is of great clinical importance for assessing the effectiveness of antiarrhythmic drugs as well as AF detection. In this paper we propose an organization index $(OI_{X})$ that quantifies AF organization based on the order statistics correlation coefficient (OSCC) previously developed by the present authors. For comparison, we also construct another similar index $(OI_{P}$ ) based on the classical Pearsonpsilas product-moment correlation coefficient (PPMCC). Statistical evidences suggest that (a) $OI_{X}$ is capable of distinguishing fibrillatory rhythms (AF) from nonfibrillatory rhythms, such as Atrial flutter (AFL); (b) $OI_{X}$ can reflect the effectiveness of adenosine, a drug commonly used during electrophysiological procedures; and (c) $OI_{X}$ performs better than $OI_{P}$ . |
| Starting Page | 366 |
| Ending Page | 369 |
| File Size | 530473 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424422548 |
| DOI | 10.1109/ITAB.2008.4570648 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-30 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Atrial fibrillation Statistics Rhythm Heart Databases Information technology Biomedical engineering Static VAr compensators Drug delivery Length measurement Volume under surface atrial flutter Frobenius norm order statistics correlation coefficient organization index Pearson’s product-moment correlation coefficient Three-way ROC |
| Content Type | Text |
| Resource Type | Article |
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