Earticle

초록

영어

Electrocardiogram (ECG) is a vital biomedical signal for diagnosing heart diseases, but now it has many other applications like stress recognition, biometric recognition, etc. But ECG signal gets noisy from various sources like as muscle noise, electrode artifacts, baseline drift noise and respiration. As wavelet transforms shows a good performance in denoising the ECG signal however, the selection of appropriate mother wavelet functions and number of wavelet decomposition level is still an issue to remove the various kinds of noises from the input signal. It is essential to denoise the ECG signal to get appropriate features of ECG signal.This research work analyze and compare the removal of noise and distortion in ECG signal using five wavelets (Daubechies, Coiflet, Haar, Biorthogonal and Symmlet) with four thresholding rules (SURE, Hybrid, Universal and Minimax) and various decomposition levels of Undecimated Wavelet Transform (UWT) and Discrete Wavelet Transform (DWT).

목차

Abstract
 1. Introduction
 2. System Implementation
 3. Results and Simulation
  3.1. Analysis of ECG noise removal in terms of S/I ratio :
  3.2. Analysis of ECG Noise Removal in Terms of Mean Square Error :
  3.3. Analysis of ECG noise removal in terms of Variance :
  3.4. Analysis of ECG noise removal in terms of PSD:
  3.5. ECG Morphology after Noise removal
 4. Conclusion
 References

키워드

저자

• Supriya Goel [ School of Information and Communication Technology Gautam Buddha University, India ]
• Pradeep Tomar [ School of Information and Communication Technology Gautam Buddha University, India ]
• Gurjit Kaur [ School of Information and Communication Technology Gautam Buddha University, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605