Analysis of Eeg Data Using Different Techniques of Digital Signal Processing

Author:

Siddiqui Mohd. Maroof1ORCID,Kidwai Mohd. Suhaib2ORCID,Srivastava Geetika3ORCID,Singh K. K.4,Charan Piyush5

Affiliation:

1. 1College of Engineering, Dhofar University, Sultanate of Oman

2. 2Integral University, India

3. 3RMLA University, India

4. 4Amity University, India

5. 5M.R. University, India

Abstract

This paper explores the application of digital signal processing (DSP) techniques in the examination of electroencephalogram (EEG) data. DSP encompasses a collection of mathematical algorithms designed to employ signals, such as EEG recordings, and finds application in diverse domains, including sleep medicine, neuroscience, and biomedical engineering. Employing DSP methods for EEG data analysis enables the extraction of pertinent insights from EEG signals, the identification of event-related patterns, and the enhancement of diagnostic and therapeutic practices across various disciplines. This article provides an overview of prevalent DSP methodologies employed in EEG signal processing, encompassing filtering, power spectral analysis, wavelet analysis, independent component analysis, and artifact removal.

Publisher

Oriental Scientific Publishing Company

Reference27 articles.

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5. 10.1183/09059180.00003213 Sforza, E., Cistulli, P. A., &Bonsignore, M. R. (2010).

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