Fetal ECG denoising using Adaptive Thresholding and Extended kalman filter With Dynamic Time Warping
| Autor: | Likkitha R, R.R. Thirrunavukkarasu, Madhumathi S, Kaviya V C |
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| Rok vydání: | 2020 |
| Předmět: |
Dynamic time warping
020205 medical informatics Noise measurement business.industry Computer science Noise reduction 020206 networking & telecommunications Pattern recognition 02 engineering and technology Filter (signal processing) Kalman filter Thresholding Adaptive filter Extended Kalman filter Signal-to-noise ratio 0202 electrical engineering electronic engineering information engineering Artificial intelligence business |
| Zdroj: | 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). |
| DOI: | 10.1109/icaccs48705.2020.9074342 |
| Popis: | The mother and fetal ECG signals are affected with various external noises and internal noises. In order to remove these noises in this paper we developed an efficient ECG denoising method using Adaptive Threshold Filter(ATF), Extended Kalman Filter(EKF) and Dynamic time wrapping(DTW) algorithm. By combining the advantages of this method the noises can be efficiently removed. Input test signal is taken from MIT BIH arrhythmia database. This method involves four steps, the first step is adaptive threshold filter for denoising of mother ECG signal, the second step involves extraction of fetal signal from mother signal and the next step is highest peak correction of mother and fetal ECG and the last step is decomposition of denoised mother and fetal ECG using Dynamic Time Wrapping algorithm. The two performance metrices called signal to noise ratio (SNR) and the another one is mean square error (MSE) measures the efficacy of the proposed technique. |
| Databáze: | OpenAIRE |
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