Abstract
A model-based method for real-time ECG diagnosis has been formulated in which information from multiple leads is processed simultaneously with a set of multivariable, linear, time-invariant filters in parallel. A diagnosis is reached by examining the filter outputs (residuals) using statistical criteria. Individual criteria diagnostics are fused into a single, final diagnostic. The methodology is applied to the discrimination of complete RBBB and LBBB from normals, using the QRS complex from 30 independent cases of a standard database. The cases are assigned randomly into a design set and a testing set of 15 cases each. Correct diagnosis assessment is 100% for the design set, and 93% and for the testing set. The method is extendible to other types of cardiac abnormalities and to multiple, distinct physiologic sensing devices.
Original language | English |
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Pages (from-to) | 457-460 |
Number of pages | 4 |
Journal | Computers in Cardiology |
Volume | 0 |
Issue number | 0 |
State | Published - 1996 |