Advances in Computational Biology pp 109-116 | Cite as
An MLP Neural Network for ECG Noise Removal Based on Kalman Filter
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Abstract
In this paper, application of Artificial Neural Network (ANN) for electrocardiogram (ECG) signal noise removal has been investigated. First, 100 number of ECG signals are selected from Physikalisch-Technische Bundesanstalt (PTB) database and Kalman filter is applied to remove their low pass noise. Then a suitable dataset based on denoised ECG signal is configured and used to a Multilayer Perceptron (MLP) neural network to be trained. Finally, results and experiences are discussed and the effect of changing different parameters for MLP training is shown.
Keywords
Kalman filter Noise removal MLP training Dataset PerformanceReferences
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