| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10322606 | Expert Systems with Applications | 2011 | 9 Pages |
Abstract
⺠In this paper, we have reported an innovative mechanism of cardiovascular disease detection directly from the compressed ECG. ⺠We have experimented on 20 different ECG segments, where 13 ECG segments were normal and 7 ECG segments were abnormal. ⺠The proposed data mining based approach could classify all the 13 normal and 7 abnormal ECG signals directly from the compressed ECG (i.e. 100% accuracy was obtained without performing decompression). ⺠Our proposed algorithm also successfully identified the initialization of abnormality, where in a particular segment normal and abnormal ECG signal was present.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Fahim Sufi, Ibrahim Khalil, Abdun Naser Mahmood,