Why the study?
Manual ECG analysis for early diagnosis of AF and CHF is complex due to varied signal characteristics, warranting an accurate automated classification system.
Does a 1-D CNN accurately classify ECG signals into normal sinus rhythm, atrial fibrillation, and congestive heart failure?
Population
5600 ECG signal segments from 56 subjects with AF, CHF, and NSR
Comparison
1-D CNN ECG signal classification across AF, CHF, and NSR
Design
Model development and validation study using leave-one-out cross-validation
Authors
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Proposed ECG classification system may aid early AF/CHF detection; leaves open need for prospective validation before clinical use.
Does a 1-D CNN accurately classify ECG signals into normal sinus rhythm, atrial fibrillation, and congestive heart failure?
A 1-D CNN algorithm can highly accurately classify raw ECG signals into normal sinus rhythm, atrial fibrillation, and congestive heart failure without extensive preprocessing.
Fuadah et al. (2022) studied this question.
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