DOI QR코드

DOI QR Code

워핑 변환을 이용한 심전도 신호의 ST 분절 특징 값 강화

Enhancement of ST-segment Features in ECG Signals by Warping Transformation

  • 신승원 (건국대 의료생명대 의학공학부) ;
  • 김경섭 (건국대 의료생명대 의학공학부, 건국대 의공학실용기술연구소)
  • 투고 : 2010.04.26
  • 심사 : 2010.05.13
  • 발행 : 2010.06.01

초록

In this study, we propose a novel method to detect and enhance the feature of ST-segment which offers the crucial information for the diagnosis of myocardial infarction and ischemia. With this aim, PQRST features of Electrocardiogram initially are detected and subsequently ST-segment are estimated. And Dynamic Time Warping(DTW) transformation is applied recursively to minimize the difference in time between ST-segments and calculate the minimum cumulative distance that decides the degree of similarity among ST-segments. As of the results, the inherent characteristic of ST-segment can be emphasized in terms of time parameter and thus the diagnostic features of a ST-segment can be revealed further.

키워드

참고문헌

  1. J. S. Sahambi, S. N. Tandon, and R. K. P. Bhatt, "Wavelet based ST-segment analysis," Medical & Biological Engineering & Computing, 36, pp. 568-572, 1998. https://doi.org/10.1007/BF02524425
  2. B. Hunag, W. Kinsner, "ECG Frame Classification Using Dynamic Time Warping," Proceeding of the 2002 IEEE Canadian conference on Electrical & Computer Engineering, pp. 1105-1110, 2002.
  3. D. C. Reddy, "Biomedical Signal Processing: Principles and Techniques," McGraw-Hill, 2005.
  4. H. Sakoe, S Chiba, "Dynamic Programming Algorithm Optimization for Spoken Ward Recognition," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-26, no. 1, pp. 43-49, 1978.
  5. 한학용, "패턴인식 개론," 한빛미디어, 2006.
  6. G. B. Moddy, "MIT/BIH Database Distribution," http://ecg.mit.edu, July, 2005.
  7. R. M. Rangayyan, "Biomedical Signal Processing: A Case-Study Approach," Wiley-Interscience, 2002.
  8. 신승원, 김경섭, 이정환, 이강휘, 김동준, "이동형 심전도 신호의 잡음 제거 및 유사도 평가," 대한전기학회논문지D, 제57권, 3호, pp.507-513, 2008. 3.