Number of classes from ECG and its application to ECG analysis

Qi, J.; Mo, Z.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 19(2): 225-228

2002


ISSN/ISBN: 1001-5515
PMID: 12224286
Document Number: 544221
The aim of this study was to detect QRS complex powers accurately. ECG was approximated by lines. It produced number of classes with main features of the whole ECG. Then these number of classes were analyzed in detail. The QRS detection rate reached 99.9% as validated by using single lead signals from MIT/BIH database. Complex powers can be recognized accurately with this method.

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