A study on discrete wavelet-based noise removal from eeg signals

K. Asaduzzaman, Md. Mamun Ibne Reaz, F. Mohd-Yasin, K. S. Sim, M. S. Hussain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.

Original languageEnglish
Title of host publicationAdvances in Experimental Medicine and Biology
Pages593-599
Number of pages7
Volume680
DOIs
Publication statusPublished - 2010

Publication series

NameAdvances in Experimental Medicine and Biology
Volume680
ISSN (Print)00652598

Fingerprint

Electroencephalography
Noise
Wavelet Analysis
Brain
Portable equipment
Electrooculography
Orthogonal functions
Biomedical equipment
Sleep Stages
Central Nervous System Diseases
Discrete wavelet transforms
Neurology
Electromyography
Artifacts
Wavelet transforms
Field programmable gate arrays (FPGA)
Epilepsy
Healthy Volunteers
Seizures
Research Personnel

Keywords

  • De-noising
  • Discrete wavelet transform
  • EEG

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Asaduzzaman, K., Ibne Reaz, M. M., Mohd-Yasin, F., Sim, K. S., & Hussain, M. S. (2010). A study on discrete wavelet-based noise removal from eeg signals. In Advances in Experimental Medicine and Biology (Vol. 680, pp. 593-599). (Advances in Experimental Medicine and Biology; Vol. 680). https://doi.org/10.1007/978-1-4419-5913-3_65

A study on discrete wavelet-based noise removal from eeg signals. / Asaduzzaman, K.; Ibne Reaz, Md. Mamun; Mohd-Yasin, F.; Sim, K. S.; Hussain, M. S.

Advances in Experimental Medicine and Biology. Vol. 680 2010. p. 593-599 (Advances in Experimental Medicine and Biology; Vol. 680).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Asaduzzaman, K, Ibne Reaz, MM, Mohd-Yasin, F, Sim, KS & Hussain, MS 2010, A study on discrete wavelet-based noise removal from eeg signals. in Advances in Experimental Medicine and Biology. vol. 680, Advances in Experimental Medicine and Biology, vol. 680, pp. 593-599. https://doi.org/10.1007/978-1-4419-5913-3_65
Asaduzzaman K, Ibne Reaz MM, Mohd-Yasin F, Sim KS, Hussain MS. A study on discrete wavelet-based noise removal from eeg signals. In Advances in Experimental Medicine and Biology. Vol. 680. 2010. p. 593-599. (Advances in Experimental Medicine and Biology). https://doi.org/10.1007/978-1-4419-5913-3_65
Asaduzzaman, K. ; Ibne Reaz, Md. Mamun ; Mohd-Yasin, F. ; Sim, K. S. ; Hussain, M. S. / A study on discrete wavelet-based noise removal from eeg signals. Advances in Experimental Medicine and Biology. Vol. 680 2010. pp. 593-599 (Advances in Experimental Medicine and Biology).
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