Earticle

초록

영어

Electrocardiogram and Respiratory signal are correlated to each other. In this paper respiration rate has been estimated from ECG. We purpose a novel combination of Ensemble Empirical Mode Decomposition (EEMD) and Canonical Correlation Analysis (CCA) in order to remove the artifacts and we have estimated the respiratory rate from the denoised ECG by creating the envelope of the denoised signal. The canonical components corresponding to the artifacts were removed on the basis of correlation coefficient of denoised signal and ground truth signal. The MIT- Polysomonographic and Apnea-ECG databases of physionet bank were used to acquire the ECG signals. Real time Baseline wander noise from MIT-NSTDB was added to each record and the respiratory rate determined was compared with the corresponding respiratory signals. The average snr improvement in case of denoising using EEMD-CCA is 20.8989db. The average BPM error in respiration rate derived from ECG denoised from EEMD is ±2.7 BPM.

목차

Abstract
 1. Introduction
 2. Methods
  2.1 Ensemble Empirical Mode Decomposition
  2.2 Canonical Correlation Analysis
  2.3 EEMD-CCA
  2.4 Algorithm
 3. Simulation and Results
 4. Conclusion
 References

키워드

저자

• Vineet Kumarand [ Department of Electronics and Communication Engineering Lovely Professional University, Phagwara , Punjab ]
• Gurpreet Singh [ Department of Electronics and Communication Engineering Lovely Professional University, Phagwara , Punjab ]

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