Wavelet-based performance in denoising ECG signal
Electrocardiogram (ECG) is a powerful tool which allows for diagnosing heart condition. Nowadays, wearable ECG recording devices are used in continuous monitoring and to provide health related information. However, these systems suffer from motion artifacts which remains an unsolved problem. In this...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
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Association for Computing Machinery
2016
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| Summary: | Electrocardiogram (ECG) is a powerful tool which allows for diagnosing heart condition. Nowadays, wearable ECG recording devices are used in continuous monitoring and to provide health related information. However, these systems suffer from motion artifacts which remains an unsolved problem. In this paper, two wavelet-based techniques are presented and applied for ECG denoising with an evaluation of their performances. These methods are: wavelet shrinkage denoisingand multi-resolution thresholding using stationary wavelet transformation (SWT).An improved multi-resolution thresholding technique is proposed. This technique combines between the two former methods. Benchmark datasets and simulated noises were used to evaluate thedenoising techniques. The results shows that the current methods still cannot cope with motions artifacts, even the proposed technique improves only the smoothness of the ECG signal. |
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