ECG signal denoising using Undecimated Wavelet Transform

Raj, V. Naga Prudhvi; Venkateswarlu, T.

doi:10.1109/icectech.2011.5941808

Cited by 26 publications

(11 citation statements)

References 5 publications

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“…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. However, in some cases [14][15][16], a pre-processing is required for the echo signal in order to obtain the best quality of the signal parameters applied for developing a conversion curve.…”

Section: Related Workmentioning

confidence: 99%

“…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%

“…A 3 MHz trigger signal is sent to the transducer by a signal generator (GW Instek GFG-3015). The transducer is a 3 MHz immersion probe transceiver (ISP5- [10][11][12][13][14][15][16][17][18][19][20] which has a focused beam with the focal length of 20 mm. The transducer transmits an ultrasonic wave that propagates through the multi-layered mediums.…”

Section: System Designmentioning

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%

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The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

Prastika

Gunawan

Dewantara

et al. 2018

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Ultrasonic technology has already been applied for many applications. Most of them are mainly used for object measurement. Some techniques have been widely applied to particular measurement by utilizing a very specific component. In this research, the previous technique to develop a conversion curve to obtain the acoustic impedance of the target is adopted. Then, a 3 MHz concave shaped ultrasonic transducer for measuring liquids is proposed and a confirmation is needed to confirm if the system is correct. Therefore, several saline solutions with some known properties are used. A low voltage of 10 Volt pulse is sent to trigger the transducer. The ultrasonic wave is transmitted through the multilayered mediums, which is pure water, clear acrylic, and the target. The echo from the interface between the acrylic and the target is then received by the same transducer. Some parameters such as peak and Root Mean Square (RMS) are used to develop the conversion curve. A peak detection and comparison between the original echo and the processed one by using Wavelet transform is performed. Some analysis of the echo signal by using multiresolution and timefrequency analysis are also proposed. The result obtained from the measurement is then compared to the theoretical calculation. Based on the result, in terms of developing the conversion curve, only the RMS value of the Undecimated Wavelet Transform (UWT) which has the closest trend to the result of the calculation, with the mean percentage error of 0.65512%, which is the smallest value among all parameters.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: System Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

Prastika

Gunawan

Dewantara

et al. 2018

emitter

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“…The hierarchical scheme of arrangement of these correlations with different wavelet functions is called multi-resolution decomposition. The multi-resolution decomposition algorithm separates the signals into "approximation" and "details" at different scales [8].…”

Section: Wavelet Transformmentioning

confidence: 99%

Denoising EOG Signal using Stationary Wavelet Transform

Naga¹,

Chandralingam²,

Anjaneyulu³

et al. 2012

Measurement Science Review

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Eye movements are critical signs of the neurological disorders and they can be acquired by EOG. The EOG signal is electrical signal generated due to eye ball movements and is contaminated with brain signals and power line while recording. As the EOG signal is a non-stationary signal, it can be denoised by wavelet transformation techniques. The present work covers denoising of noisy EOG signal using Stationary Wavelet Transform (SWT), which was done with all suitable wavelets that are morphologically similar to an EOG signal by applying both Soft and Hard Thresholding methods. An EOG signal was simulated and added with noise to obtain noisy EOG signal. The wavelet analysis of the simulated noisy EOG signal reveals that the Biorthogonal 3.3 wavelet is the best wavelet to denoise by using SWT technique, wherein the yield achieved was good with Signal to Noise Ratio of 36.5882 dB and minimum Mean Square Error of 0.383313 for quality diagnosis.

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Classification of Arrhythmias from ECG Using Fractal Dimensions and Wavelet Theory

Sabrine

Aguili

2022

Advances in Information, Communication and Cybersecurity

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ECG signal denoising using Undecimated Wavelet Transform

Cited by 26 publications

References 5 publications

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

Denoising EOG Signal using Stationary Wavelet Transform

Classification of Arrhythmias from ECG Using Fractal Dimensions and Wavelet Theory

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