Species-independent pipeline for quantitative analysis of electroencephalogram with application in classification of traumatic brain injury in mice and humans

Manoj Vishwanath, Carolyn Jones, Miranda M. Lim, Hung Cao

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Electroencephalogram (EEG) is an electrophysiological recording of the brain potentials whose analysis has been crucial in the study of various neurological conditions. However, due to the non-stationarity and noisy nature of EEG, it is extremely difficult to extract meaningful information. In this chapter, we introduce a standard pipeline consisting of an amalgamation of advanced signal processing and machine learning techniques that can be used to analyze EEG signals irrespective of the organism it was collected from. The working of the proposed standard EEG analysis pipeline is demonstrated in the detection of traumatic brain injury (TBI) in mouse and human sleep EEG.

Original languageEnglish (US)
Title of host publicationCutting-edge Technologies in Biological Sensing and Analysis
PublisherRiver Publishers
Pages239-269
Number of pages31
ISBN (Electronic)9788770225854
ISBN (Print)9788770223799
StatePublished - Sep 27 2023

Keywords

  • Electroencephalogram
  • Machine learning
  • Mice
  • Sleep
  • Standard pipeline
  • Traumatic brain injury

ASJC Scopus subject areas

  • General Computer Science
  • General Economics, Econometrics and Finance
  • General Business, Management and Accounting

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