The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지
DOI QR코드

DOI QR Code

Removing Baseline Drift from ECG Signal Using Smoothing Spline and Morphology Operation

평활화 스플라인 연산과 형태학 연산을 이용한 기저선 변동 잡음 제거

  • Back, Seung-Gwan (Kyungpook National University The Graduate School Department of Computer Information) ;
  • Choi, Chang-Hoon (Kyungpook National University Department of Computer Software) ;
  • Kim, Jeong-Hong (Kyungpook National University School of Computer Science)
  • Received : 2016.09.21
  • Accepted : 2016.12.19
  • Published : 2017.01.31
Download PDF
⟨ Previous Next ⟩

Abstract

Low frequency noise components causes the baseline drift in the ECG signals. In this paper, a morphological operation and smoothing spline technique are used for ECG signal processing in order to accomplish baseline correction. Removing the baseline drift from ECG signal using morphology operation, the feature of original signal may be distorted. To resolve this distortion problem, we applied a smoothing spline operation after morphology operation. In order to compare with existing morphology operation method for baseline correction, we apply proposed method to ECG data in MIT/BIH database. Compared to other existing method, our proposed method achieved low data distortion on the original signal.

심전도 신호에 있는 저주파 잡음 성분은 기저선 변동을 일으킨다. 본 논문에서는 기저선 변동이 있는 심전도 신호에 대하여 형태학 연산과 평활화 스플라인 연산을 사용하여 기저선 변동 잡음을 제거하였다. 형태학 연산만 이용하여 기저선 변동 잡음을 제거하는 경우, 사용한 구조요소에 따라 원 신호의 특징점 정보를 손상시킬 수 있다. 형태학 연산의 단점을 해결하기 위하여, 형태학 연산 후 평활화 스플라인 연산을 적용하였다. ECG 신호 처리를 위한 기존의 형태학 연산을 이용한 방법과 본 논문에서 제안된 방식을 MIT/BIH 데이터베이스에서 제공하는 심전도 임상 데이터에 각각 적용하여 비교하였다. 실험을 통해 본 논문에서 제안된 방식이 기존 방식보다 원신호에 대한 데이터 왜곡도가 낮음을 확인하였다.

Keywords

References

  1. K. H. Park and J. H. Kim, "Removing baseline drift in ECG signal using morphology-pair operation and median value," J. Korea Soc. Comput. and Inf., vol. 19, no. 8, pp. 107-117, Aug. 2014. https://doi.org/10.9708/jksci.2014.19.8.107
  2. K. L. Park, "Design of WAF and WIF for de-noising in the stress ECG," M.S. Thesis, The Graduate School of Yonsei University, Jun. 2005.
  3. Rafael C. Gonzalez, Richard E. Woods, and Steven L. Eddins, Digital Image Processing Using MATLAB, pp. 142-144, Prentice-Hall, Inc., 2004.
  4. G. Y. Lee, I. K. Kim, S. O. Hwang, K. H. Choi, and H. R. Yoon, "Improvement of ECG P wave detection performance using CIR (Contextual Information Rule-bass) algorithm," J. Biomed. Eng. Res., vol. 17, no. 2, pp. 235-240, 1996.
  5. J. A. Apolinario Jr., QRD-RLS Adaptive Filtering, pp. 12-23, Springer, 2009.
  6. C. H. Choi, Y. J. Kim, T. H. Kim, Y. H. Ahn, and D. R. Shin, "Analysis of QRS-wave using wavelet transform of electrocardiogram," J. Biosyst. Eng., vol. 33, no. 5, pp. 317-325, 2008. https://doi.org/10.5307/JBE.2008.33.5.317
  7. S. M. Lee, J. S. Kim, and K. H. Park, "PVC detection based on the distortion of QRS complex on ECG signal," J. KICS, vol. 40, no. 04, pp. 731-739, Apr. 2015. https://doi.org/10.7840/kics.2015.40.4.731
  8. G. M. Friesen, T. C. Jannett, M. A. Jadallah, S. L. Yates, S. R. Quint, and H. T. Nagle, "A comparison of the noise sensitivity of nine QRS detection algorithms," IEEE Trans. Biomed. Eng., vol. 37, no. 1, pp. 85-98, Jan. 1990. https://doi.org/10.1109/10.43620
  9. J. H. Kim, S. M. Lee, and K. H. Park, "Stepwise detection of the QRS complex in the ECG signal," J. KICS, vol. 41, no. 02, pp. 244-253, Feb. 2016. https://doi.org/10.7840/kics.2016.41.2.244
  10. K. S. Bae, "ECG baseline wander rejection use improved morphological filter," M.S. Thesis, The Graduate School of Yonsei University, Jun. 2005.
  11. Y. Sun, K. Chan, and S. M. Krishnan, "ECG signal conditioning by morphological filtering," Comput. Biol. and Med., vol. 32, no. 6, pp. 465-479, Nov. 2002. https://doi.org/10.1016/S0010-4825(02)00034-3
  12. Wikipedia, Smoothing spline(2016), Retrieved Aug. 3, 2016, from https://en.wikipedia.org/wiki/Smoothing_spline
  13. Simon Wood, Generalized Additive Models:An Introduction with R, pp. 142-144, Chapman and Hall/CRC, 2006.
  14. MathWorks, Smoothing splines(2015), Retrieved Aug. 4, 2016, from http://kr.mathworks.com/help/curvefit/smoothing-splines.html#bq_6ys3-13
  15. G. Moody and R. Mark, "The impact of the MIT-BIH arrhythmia database," IEEE Eng. Med. and Biol., vol. 20, no. 3, pp. 45-50, May-Jun. 2001. https://doi.org/10.1109/51.932724