Earticle

초록

영어

Artifacts frequently corrupt biomedical signal recording and processing, therefore, removal of these artifacts from physiological signals is an essential step. The acuteness in the performance of healthcare technology has upgraded from the current hospital-centric environment towards portable ubiquitous approaches. The uncertainty in the subsequent performance of these approaches introduced a dedicated research and past few decades have witnessed considerable improvement. In this research work an enhanced empirical approach to model the artifacts of EEG signal are described. The input EEG is a single channel and is converted into multichannel using Ensemble Empirical Mode decomposition (EEMD) operations and further filtered with Independent Component Analysis and Double Density Wavelet Transform to reject any traces of artifacts left at signal. This proposed algorithm is tested with different evaluation parameters and results pronounce the eligibility of the proposed algorithm to stand on top of currently deployed algorithms because significant improvement in results.

목차

Abstract
 1. Introduction
 2. Empirical Mode Decomposition (EEMD)
 3. Independent Component Analysis (ICA)
 4. Discrete Wavelet Transform (DWT)
 5. Proposed System Model
 6. Data Acquisition
 7. Performance Evaluation Parameters
  7.1. Signal to Noise Ratio (SNR)
  7.2. POWER spectral Density (PSD)
 8. Results and Discussion
 9. Conclusion
 References

키워드

저자

• Vandana Roy [ DoEC, GGITS, Jabalpur, M.P., 482005, INDIA ]
• Shailja Shukla [ Professor and Head of DoCSE, JEC, Jabalpur, MP, 482011, 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