Performance Analysis of Low-Resolution Electroencephalogram Source Localization Techniques

Authors

  • Muhammad Mubashir Iqbal Indus University
  • Chandar Kumar
  • Shubash Kumar
  • Areeb Anis Khan
  • Zain Abidi

DOI:

https://doi.org/10.33317/ssurj.411

Keywords:

EEG, Inverse Problem, sLORETA, eLORETA, Event-related potential.

Abstract

Brain source localization has attained significant fascination over the last few decades. Source localization in the human brain is a prospective complication that is derived in the multifaceted real-world complications because of the brain’s practical and biological density, other than medical precincts of assembling Electroencephalogram (EEG) from enormously various subjects. It is validated that the electromagnetic signal recorded on the top of the scalp is owing to the collective actions of neurons inside the brain. Any impulsive action of the brain, sensory stimulus, cognitive action, or the generation of motor yield possibly will offer intensification to such neuronal actions. Source- localization in the human brain implicates the localization and detection of such primary neuronal originators into the brain. Although renowned and different research in the area, the complications remnants to be a mysterious inverse problem in the brain signal processing research. The performance of EEG source localization techniques based on standardized Low-Resolution Brain Electromagnetic Tomography (sLORETA) and exact Low-Resolution Brain Electromagnetic Tomography (eLORETA) is highlighted in this research. The Event-Related Potential (ERP) records with chromatic stimulus are considered for analysis at diverse time intervals for both techniques and final results are discussed in reports of scalp map, slice view, and, cortex map and proposed the optimum techniques for EEG source localization.

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Published

2022-06-30

How to Cite

Iqbal, M. M., Chandar Kumar, Shubash Kumar, Areeb Anis Khan, & Zain Abidi. (2022). Performance Analysis of Low-Resolution Electroencephalogram Source Localization Techniques. Sir Syed University Research Journal of Engineering & Technology, 12(1), 51–56. https://doi.org/10.33317/ssurj.411