2010 International Conference on Electronics and Information Engineering 2010
DOI: 10.1109/iceie.2010.5559812
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ECG noise removal and QRS complex detection using UWT

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Cited by 28 publications
(15 citation statements)
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“…The research about the application of the Wavelet transform has been applied in many fields of study, such as ultrasound and biomedical field [12][13][ [17][18][19] because Wavelet can maintain the detail of the original signal as well as removing the unused part such as noise and reconstruct the signal [20]. In the previous research about developing a conversion curve from an echo signal [12][13][14][15], the method to remove the noise of the signal is not discussed in detail, it is either because the echo signal can instantly be processed or because the need for signal pre-processing is not necessary.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The research about the application of the Wavelet transform has been applied in many fields of study, such as ultrasound and biomedical field [12][13][ [17][18][19] because Wavelet can maintain the detail of the original signal as well as removing the unused part such as noise and reconstruct the signal [20]. In the previous research about developing a conversion curve from an echo signal [12][13][14][15], the method to remove the noise of the signal is not discussed in detail, it is either because the echo signal can instantly be processed or because the need for signal pre-processing is not necessary.…”
Section: Related Workmentioning
confidence: 99%
“…This noise will affect the amplitude and the shape of the signal, which will change the value of the peak-to-peak and RMS as well. In this research, the Wavelet transform is applied to overcome this problem, because Wavelet can remove the noise without losing the original profile of the signal [10][11][12][13], compared to the conventional Bandpass filter method. The Wavelet transform can also be applied to detect the peak of the signal more precisely, compared to the conventional peak detection such as curve fitting method.…”
Section: Introductionmentioning
confidence: 99%
“…One of the most widely used techniques for identifying non-repetitive and/or periodic patterns or distortions has been the wavelet transform [4][5].This technique adapts a wavelet pattern to the characteristics of the signal distortion to be identified.This has been used for identification of epileptic spikes in electroencephalography (EEG) signal [6][7][8][9], to identify emboli in the blood flow signal [10][11][12][13], to identify arrhythmias in the ECG signal [14][15][16], for identifying flaws in industrial materials (metals, concrete, etc. )in the ultrasound signal [17][18][19], and many other scenarios.…”
Section: Iirelated Workmentioning
confidence: 99%
“…Daubechies 6 (db6) [7] wavelet is suitable because its shape resembles that of ECG. For better balance between smoothness and accuracy when compared to Discrete Wavelet Transform (DWT), Undecimated Wavelet Transform (UWT) [8] of level 8 is applied. The choice of this level is because the noise removal efficiency is proportional to the increase in levels.…”
Section: Ecg Analysismentioning
confidence: 99%