Analysis of Eeg Data Using Different Techniques of Digital Signal Processing

Mohd. Maroof Siddiqui¹, Mohd. Suhaib Kidwai², Geetika Srivastava^3*, K. K. Singh⁴ and Piyush Charan⁵

¹College of Engineering, Dhofar University, Sultanate of Oman

²Integral University, India

³RMLA University, India

⁴Amity University, India

⁵M.R. University, India

Corresponding Author E-mail: gsrivastava@rmlau.ac.in

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.

Keywords: EEG Signals; Low-Pass Filter; Power Spectrum Density;  Sleep Disorder

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