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An Denoising Method based on Improved Wavelet Threshold Function
| Content Provider | Semantic Scholar |
|---|---|
| Author | Lv, Xiafu Ni, Daihui Zhao, Zhiqiang Liu, Yanjun |
| Copyright Year | 2017 |
| Abstract | The ECG signal is an important parameter for the diagnosis of heart disease. In the process of collection and transportation, ECG signals easily mixed with human body noise or the noise generated by the instrument. Therefore, the noise greatly affects the accuracy of the measurement. Wavelet threshold denoising method is widely used in denoising of ECG signal. Based on soft threshold and hard threshold denoising, an improved wavelet threshold denoising algorithm is proposed to remove ECG noise in this paper. The improved denoising algorithm can avoid the false Gibbs phenomenon and the drawbacks of excessive smoothing caused by the soft threshold and the hard threshold method. Finally, the ECG data in MIT-BIH database is used to simulate. The experimental result shows that the improved threshold denoising algorithm can effectively remove the noise in the signal, and the signal to noise ratio is higher than the soft threshold and hard threshold method. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijscience.org/download/IJS-4-1-42-48.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
