Key result
Adaptive artificial neural network model classifies heartbeat morphology in MIT-BIH database traces.
Population
Traces from the MIT-BIH arrhythmia database (multichannel ECG signals)
Design
Other
Authors
Loading...
May aid automated ECG analysis in research; leaves open prospective clinical validation before any practice change.
A novel adaptive artificial neural network model can dynamically self-organize to classify heartbeat morphologies on multichannel ECG signals.
Barro et al. (1998) studied Arrhythmia. Adaptive artificial neural network model was evaluated on Morphological classification of heartbeats. An adaptive artificial neural network model was developed and evaluated for the morphological classification of heartbeats using traces from the MIT-BIH arrhythmia database.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: