基于卡尔曼滤波器的 ECG 噪声去除的 MLP 神经网络。
An MLP neural network for ECG noise removal based on Kalman filter.
机构信息
Multimedia University, Cyberjaya, Malaysia.
出版信息
Adv Exp Med Biol. 2010;680:109-16. doi: 10.1007/978-1-4419-5913-3_13.
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.
本文研究了人工神经网络 (ANN) 在心电图 (ECG) 信号噪声去除中的应用。首先，从 Physikalisch-Technische Bundesanstalt (PTB) 数据库中选择了 100 个 ECG 信号，并应用卡尔曼滤波器去除其低通噪声。然后，配置了一个基于去噪 ECG 信号的合适数据集，并将其用于多层感知器 (MLP) 神经网络进行训练。最后，讨论了结果和经验，并展示了改变 MLP 训练不同参数的效果。
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