A Reliable Method to Estimate the Bispectral Index Value Using a Single Frontal EEG Channel for Intra and Inter Subject Variability

Mohammad Shahbakhti, Matin Beiramvand, Roza Krycinska, Erfan Nasiri, Wei Chen, Jordi Solé-Casals, Michal Wierzchon, Anna Broniec-Wójcik, Piotr Augustyniak, Vaidotas Marozas

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

1 Citation (Scopus)

Abstract

Objective: Monitoring the depth of anesthesia (DoA) plays an important role for administering the drug injection during a surgery, i.e., preventing undesired awareness and inordinate anesthetic depth. Although the bispectral index (BIS) monitor is the golden standard system for the DoA monitoring, it is still not affordable for the developing countries. Alternatively, a low-cost electroencephalogram (EEG) headband can be used. The objective of this paper is to present a new algorithm for estimating the BIS values using a single frontal EEG channel. Method: In the first step, the EEG signal is filtered for the elimination of artifacts and is split into its sub-bands. In the second step, several linear and nonlinear features are extracted from each sub-band and fed to a random forest regression model in order to estimate the BIS. The performance of the proposed algorithm is assessed using EEG data recorded from twenty-four subjects during the general anesthesia and is validated in terms of correlation coefficient (CC) and absolute error (AE) between the reference and estimated BIS values. Results: The proposed algorithm achieved the mean CC of 0.83 and AE of 6.5 for intra subject variability and mean CC of 0.87 and AE of 5.5 for inter subject variability. Significance: Given the similar results for both intra and inter subject variability, the proposed algorithm has the potential to be used in the real-world scenario.
Original languageEnglish
Title of host publication2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 - Conference Proceedings
PublisherIEEE
ISBN (Electronic)978-1-6654-9384-0
DOIs
Publication statusPublished - 2023
Publication typeA4 Article in conference proceedings
EventIEEE International Symposium on Medical Measurements and Applications - Jeju, Korea, Republic of
Duration: 14 Jun 202316 Jun 2023

Conference

ConferenceIEEE International Symposium on Medical Measurements and Applications
Abbreviated titleMeMeA
Country/TerritoryKorea, Republic of
CityJeju
Period14/06/2316/06/23

Publication forum classification

  • Publication forum level 1

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