Analysis of Butterworth and Chebyshev Filters for ECG Denoising Using Wavelets

Rastogi, Nidhi; Mehra, Rajesh

doi:10.9790/2834-0663744

Cited by 22 publications

(11 citation statements)

References 13 publications

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“…They are used for distinct frequencies of band from one to another also has steeper roll-off. The main feature is they have good speed [6].…”

Section: Filter Approximation Methodsmentioning

confidence: 99%

Effect of Distributed Elements Filters on Transmission Lines

Dhatrak¹

2017

International Journal of Advanced Research in Computer and Comm

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Electrical Energy is the life stream of progress for any nation and it is all the more vital in a developing country like India. The energy in electrical form is most widely used since it can be converted into any other form efficiently. A power System Network consists of variety of apparatus for generation, transmission and distribution spread over a large area serving to number of Industrial & Commercial consumers. When the power system is polluted with harmonics due to non linear load, unbalance prevailing between phases and bad voltage profile the quality of power supply becomes very inferior which hampers the power apparatus of both the utilities and the customers. Filters have gained a great attention owing to their applications as a solution to above issues. To make it distortion and ripple free filters are used at receiving end. These filtered signals may be used for further processing. This work is an attempt to simulate various filters such as Butterworth and Chebyshev Type I and Type II using MATLAB/SIMULINK. For flat band response Butterworth filter is used. Error probability will be less in Chebyshev filter.

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“…They are used for distinct frequencies of band from one to another also has steeper roll-off. The main feature is they have good speed [6].…”

Section: Filter Approximation Methodsmentioning

confidence: 99%

Effect of Distributed Elements Filters on Transmission Lines

Dhatrak¹

2017

International Journal of Advanced Research in Computer and Comm

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“…In this work, the Butterworth filter is used to obtain the required signals of the user body, since they are easy to handle at many real time applications [ 21 , 22 ]. Then, these obtained signals are used on the artificial neural network.…”

Section: Preliminariesmentioning

confidence: 99%

Design and Implementation of a Prosthesis System Controlled by Electromyographic Signals Means, Characterized with Artificial Neural Networks

et al. 2022

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Around the world many people loss a body member for many reasons, where advances of technology may be useful to help these people to improve the quality of their lives. Then, designing a technologically advanced prosthesis with natural movements is worthy for scientific, commercial, and social reasons. Thus, research of manufacturing, designing, and signal processing may lead up to a low-cost affordable prosthesis. This manuscript presents a low-cost design proposal for an electromyographic electronic system, which is characterized by a neural network based process. Moreover, a hand-type prosthesis is presented and controlled by using the processed electromyographic signals for a required particular use. For this purpose, the user performs several movements by using the healthy-hand to get some electromyographic signals. After that, the obtained signals are processed in a neural network based controller. Once an usable behavior is obtained, an exact replica of controlled motions are adapted for the other hand by using the designed prosthesis. The characterization process of bioelectrical signals was performed by training twenty characteristics obtained from the original raw signal in contrast with other papers in which seven characteristics have been tested on average. The proposed model reached a 95.2% computer test accuracy and 93% accuracy in a real environment experiment. The platform was tested via online and offline, where the best response was obtained in the online execution time.

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“…Dalam bidang medis, filter SG terbukti bermanfaat. Peneliti [13], [14] menyatakan bahwa penggunaan filter SG secara signifikan meningkatkan nilai SIR pada sinyal electrocardiogram (ECG). Performa filter SG juga menghasilkan distorsi yang lebih rendah dibandingkan dengan proses denoising wavelet konvensional.…”

Section: Gambar 1 Sinyal Yang Difilter Dengan Filter Sgunclassified

Simulasi Perbandingan Filter Savitzky Golay dan Filter Low Pass Butterworth pada Orde Ketiga Sebagai Pembatal Kebisingan

2021

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Nowadays, the Information and Communication Technology (ICT) is rapidly developed. It also trigs the development of other research field such as social science research. But in the development of it, there are a continues problem that has been discovered over 30 years, noise. Over the years, many ways have been created for example Savitzky – Golay (SG) and Low Pass (LP) Butterworth filter. In order to use SG filter, two parameters which are the order and the window length should be determined by trial and error. On the other hand, LP Butterworth filter also needs two parameters to be operated which are the order and the cut off frequency. This research focuses on comparing the performance of third order LP Butterworth filter and third order SG filter by finding the gap between filtered signal and the original signal through the simulation by using MATLAB. This research is supported by the journals and books references. Also, the data of this research is presented by the table and graph. According to this research, founded that both filters have a significant impact to smoothing the noisy signal. compare to LP Butterworth filter, SG filter has better performance. It is proven by SG filter only has 5% gap to the original signal where LP Butterworth filter has a slightly bigger gap, 8.82%.

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Analysis of Butterworth and Chebyshev Filters for ECG Denoising Using Wavelets

Cited by 22 publications

References 13 publications

Effect of Distributed Elements Filters on Transmission Lines

Effect of Distributed Elements Filters on Transmission Lines

Design and Implementation of a Prosthesis System Controlled by Electromyographic Signals Means, Characterized with Artificial Neural Networks

Simulasi Perbandingan Filter Savitzky Golay dan Filter Low Pass Butterworth pada Orde Ketiga Sebagai Pembatal Kebisingan

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