Earticle

초록

영어

Presence of artifacts in electroencephalographs (EEG) is major hurdles for the precise analysis of spectral behavior. For suppression of ocular artifact in EEG this paper proposes a component based Independent Component Analysis (ICA) model. It involves the generating a set of individual components of given signal followed by rejection of unwanted artifacts. Further this paper presents a novel method with combination of ICA, information sharing and double density wavelet transform to reject the artifacts from the signal. The Independent Component Analysis (ICA) here is used to segment artifact peaks in the signal. Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result. The Wavelet ICA suppression not only removes artifacts but also preserves the spectral and coherence properties of brain signals.

목차

Abstract
 1. Introduction
 2. ICA based Method
 3. Double Density DWT
 4. Proposed Method
 5. Experimental Setup
 6. Result Analysis
 7. Conclusion
 References

키워드

저자

• Vandana Roy [ Department of Electronics & Communication, GGITS, Jabalpur, M.P., 482005, India ]
• Shailja Shukla [ Professor and Head of Department of Computer Science Engineering, 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