Calculation of Quantitative Parameters of Clinical EEG Signals by Adopting Visual Reading Methods

Amila Sofiah, Hasballah Zakaria

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Electroencephalography (EEG) is a technique that can measure the state of the brain's bioelectric activity. In the clinical setting, EEG recording is followed by visual readings by clinicians for qualification. Visual analysis in conscious EEG records include the assessment of background rhythms and graphoelement. This visual reading is good to recognize artifacts. Unfortunately, it has several drawbacks, including its reliability among the assessors is quite low because it depends on the capabilities and experience of the interpreter. Also, if the EEG spatial resolution increases, it takes quite a long time to read. In this study, we developed an algorithm to calculate EEG signal parameters based on visual readings performed by clinicians. Quantitative parameters were calculated in the form of porterior dominant rhythm (PDR) existence, PDR frequency, PDR frequency asymmetry, PDR amplitude, PDR amplitude asymmetry, anterior-posterior gradient, beta amplitude, beta amplitude asymmetry, theta existence, and delta existence. The computation time needed to analyze all 16 channel EEG signals were about 115 seconds. To reduce the computation time, 5 minutes EEG records were manually selected from a complete records. The computation time reduced to 27 seconds without significant different on the quantitative parameters.

Original languageEnglish
Title of host publicationISESD 2018 - International Symposium on Electronics and Smart Devices
Subtitle of host publicationSmart Devices for Big Data Analytic and Machine Learning
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538666708
DOIs
Publication statusPublished - 7 Jan 2019
Externally publishedYes
Event2018 International Symposium on Electronics and Smart Devices: Smart Devices for Big Data Analytic and Machine Learning, ISESD 2018 - Bandung, Indonesia
Duration: 23 Oct 201824 Oct 2018

Publication series

NameISESD 2018 - International Symposium on Electronics and Smart Devices: Smart Devices for Big Data Analytic and Machine Learning

Conference

Conference2018 International Symposium on Electronics and Smart Devices: Smart Devices for Big Data Analytic and Machine Learning, ISESD 2018
Country/TerritoryIndonesia
CityBandung
Period23/10/1824/10/18

Keywords

  • Electroencephalography (EEG)
  • PDR
  • qEEG
  • signal processing

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