ANALISIS PERBANDINGAN METODE DUAL-TREE DISCRETE WAVELET TRANSFORM DAN MOVING AVERAGE PADA DENOISING SINYAL PHONOCARDIOGRAM
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Institusion
Institut Teknologi Telkom Purwokerto
Author
TUAH JIHAN, MANULLANG
Subject
T Technology (General)
Datestamp
2021-04-26 03:23:34
Abstract :
Diagnosis of heart health conditions using electrocardiogram is common but high funding and the use of tools that require special expertise limits the spread as a diagnostic tool. The use of phonocardiogram (PCG) based devices can overcome this problem but the presence of noise coincides temporally with heart sound information limiting the development of PCG-based devices. This research conducts signal processing to eliminate noise contained in PCG signals using the Moving Average (MA) and Dual-Tree Discrete Wavelet Transform (DTDWT) methods. The test variations are the Moving Average type in the Moving Average Method, and the thresholding type in the Dual-Tree Discrete Wavelet Transform method. The results of the study show that the Dual-Tree Discrete Wavelet Transform Method is a better method compared to Moving Average to eliminate noise due to its ability to divide the signal into several subband frequencies. Keywords : Electrocardiogram, Phonocardiogram, Dual-tree Discrete Wavelet Transform, Moving Average, Mean-squared error, Signal-to-noise ratio, Root meansquared error
Diagnosis of heart health conditions using electrocardiogram is common but high funding and the use of tools that require special expertise limits the spread as a diagnostic tool. The use of phonocardiogram (PCG) based devices can overcome this problem but the presence of noise coincides temporally with heart sound information limiting the development of PCG-based devices. This research conducts signal processing to eliminate noise contained in PCG signals using the Moving Average (MA) and Dual-Tree Discrete Wavelet Transform (DTDWT) methods. The test variations are the Moving Average type in the Moving Average Method, and the thresholding type in the Dual-Tree Discrete Wavelet Transform method. The results of the study show that the Dual-Tree Discrete Wavelet Transform Method is a better method compared to Moving Average to eliminate noise due to its ability to divide the signal into several subband frequencies. Keywords : Electrocardiogram, Phonocardiogram, Dual-tree Discrete Wavelet Transform, Moving Average, Mean-squared error, Signal-to-noise ratio, Root meansquared error
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