• Title/Summary/Keyword: Digital IIR lowpass filter

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Performance Evaluation for ECG Signal Prediction Using Digital IIR Filter and Deep Learning (디지털 IIR Filter와 Deep Learning을 이용한 ECG 신호 예측을 위한 성능 평가)

  • Uei-Joong Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.611-616
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    • 2023
  • ECG(electrocardiogram) is a test used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, the noise of the ECG signal was removed using the digital IIR Butterworth low-pass filter. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, was compared using the deep learning model of LSTM, it was confirmed that the activation function with the smallest error was the tanh() function. Also, When the performance evaluation and elapsed time were compared for LSTM and GRU models, it was confirmed that the GRU model was superior to the LSTM model.