한국임상보건과학회지 (Journal of Korean Clinical Health Science)

한국임상보건과학회 (The Korean Society of Clinical Health Science)
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웨이브렛 변환의 모함수에 따른 ERG의 잡음제거 성능 비교

Comparison of ERG Denoising Performance according to Mother Function of Wavelet Transforms

  • 서정익 (대구보건대학교 안경광학과) ;
  • 박은규 (대구보건대학교 안경광학과) ;
  • 장준영 (대구보건대학교 안경광학과)
  • 투고 : 2016.10.10
  • 심사 : 2016.10.21
  • 발행 : 2016.12.31
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초록

Purpose. Noise occurs at measuring Electoretinogram(ERG) signals as the other bio-signal measurement. It is compared the denoising performance according to the mother function of wavelet transforms. Methods. The ERG signal that generated power supply noise and white noise was used as a sampling signal. The noise of ERG signal was filtered by using haar, db7, bior mother function. The filtering performance of each mother functions was compared using Fourier transform spectrum and SNR(signal to noise ratio). Results. In the haar functioin, the result of the Fourier transform spectrum was that the power supply noise is removed and the white noise performance is not good. The SNR was 27.0404. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is good. The SNR was 35.1729. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is the bset. The SNR was 35.4445. Conclusions. The db7, bior function was good results in power supply noise and white noise filtered. The bior function is suitable for filtering noise of the ERG signal.

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참고문헌

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피인용 문헌

  1. Intelligent Deep Models Based on Scalograms of Electrocardiogram Signals for Biometrics vol.19, pp.4, 2019, https://doi.org/10.3390/s19040935
  2. Obstructive sleep apnea prediction from electrocardiogram scalograms and spectrograms using convolutional neural networks vol.42, pp.6, 2021, https://doi.org/10.1088/1361-6579/ac0a9c