Key result
An SVM-based algorithm achieved a detection rate of 95.43% for P waves and 96.89% for T waves, with delineation performance within the tolerance limits of the CSE library.
Why the study?
Does an SVM-based algorithm accurately detect and delineate P and T waves in 12-lead ECGs compared to manual annotations?
Does an SVM-based algorithm accurately detect and delineate P and T waves in 12-lead ECGs compared to manual annotations?
An SVM-based algorithm demonstrates high accuracy (>95%) in detecting and delineating P and T waves in 12-lead ECGs compared to manual annotations.
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May support automated ECG analysis in research; leaves open clinical adoption pending prospective validation.
Mehta et al. (2009) studied Electrocardiogram analysis. Support vector machine (SVM) algorithm vs. Manual annotations by referee cardiologists was evaluated on Detection rate of P and T waves. An SVM-based algorithm achieved a detection rate of 95.43% for P waves and 96.89% for T waves, with delineation performance within the tolerance limits of the CSE library.
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