Clasification Of Arrhythmic ECG Data Using Machine Learning Techniques

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Population

Multi-channel ECG recordings from MIT-BIH arrhythmia database and NSR database

Authors

Discussion

ANN models may aid ECG arrhythmia detection; leaves open prospective clinical validation before any practice change.

Population

Multi-channel ECG recordings from MIT-BIH arrhythmia database and NSR database (mixture of arrhythmic and non-arrhythmic data)

Intervention

Automated Artificial Neural Network (ANN) based classification system with back propagation algorithm

Outcome

Classification accuracysurrogate

An artificial neural network model can accurately classify cardiac arrhythmias from multi-channel ECG recordings, achieving over 96% accuracy.

Vishwa et al. (2011) studied this question.

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