Tutorial: EEG Data Analysis: Feature Extraction, Connectivity and Classification

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EEG Data Analysis: Feature Extraction, Connectivity and Classification

Aamir Saeed Malik

Centre for Intelligent Signal and Imaging Research (CISIR), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia

 

 

 
ABSTRACT

In the last decade, BCI technology has emerged to impact the society in terms of brain connectivity with the machines. This is due to EEG signals which play a key role. EEG signals are acquired from the human scalp non-invasively. EEG signals represent different states of the brain inferring to neural activity. Low amplitudes of EEG signals make it more vulnerable to the noise. EEG signals are amplified and filtered to remove noise and artefacts. To extract the useful information from the clean EEG data, feature extraction plays a critical role in assessing the person’s cognitive or mental states of brain. Brain connectivity is another perspective to understand the brain functional networks and regions. These features can be further used in brain computer interfacing, gaming, and neural rehabilitation purposes.

This tutorial will focus on brain signal processing using EEG data. The main focus is on feature extraction and classification.

The tutorial will cover the following topics:

  • Fundamentals of Brain Science
  • EEG pre-processing & band analysis
  • Feature Extraction
    • Time Series Analysis
    • Frequency Based Analysis
    • Time Frequency Analysis
  • Classification
  • Brain Connectivity

SPEAKER BIOGRAPHY

Aamir Saeed Malik is currently Associate Professor at Universiti Teknologi PETRONAS in Malaysia. He is associated with the Department of Electrical and Electronic Engineering and Centre for Intelligent Signal and Imaging Research. He has a B.S in Electrical Engineering from University of Engineering & Technology, Lahore, Pakistan, M.S in Nuclear Engineering from Quaid-i-Azam University, Islamabad, Pakistan, another M.S in Information & Communication and Ph.D in Information & Mechatronics from Gwangju Institute of Science & Technology, Gwangju, Korea. He has more than 15 years of research experience and has worked for IBM, Hamdard University, Government of Pakistan, Yeungnam University and Hanyang University during his career. He is fellow IET, Senior Member of IEEE and has more than 200 publications with cumulative impact factor of more than 200. He is the author of 3 books and has more than 10 patents and copyrights. His research interests include brain signal & image processing (EEG, MEG, fNIR, fMRI).