Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 11, 2026

Chronic Cranial Window Technique for Repeated Cortical Recordings During Anesthesia in Pigs
07:19

Chronic Cranial Window Technique for Repeated Cortical Recordings During Anesthesia in Pigs

Published on: June 6, 2025

Evolution of electroencephalogram signal analysis techniques during anesthesia.

Mahmoud I Al-Kadi1, Mamun Bin Ibne Reaz, Mohd Alauddin Mohd Ali

  • 1Department of Electrical, Electronic & Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi Selangor 43600, Malaysia. mahmoudalkadi67@yahoo.com

Sensors (Basel, Switzerland)
|May 21, 2013
PubMed
Summary

This review explores electroencephalograms (EEGs) for monitoring anesthesia depth. Advanced biosignal analysis of EEG data can lead to more reliable anesthesia monitoring devices.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach.

Artificial intelligence in medicine·2025
Same author

A novel classical machine learning framework for early sepsis prediction using electronic health record data from ICU patients.

Computers in biology and medicine·2024
Same author

Correction: Machine learning-based prognostic model for 30-day mortality prediction in Sepsis-3.

BMC medical informatics and decision making·2024
Same author

PPG2RespNet: a deep learning model for respirational signal synthesis and monitoring from photoplethysmography (PPG) signal.

Physical and engineering sciences in medicine·2024
Same author

Machine learning-based prognostic model for 30-day mortality prediction in Sepsis-3.

BMC medical informatics and decision making·2024
Same author

Correction: An Integrated Approach for Platoon-based Simulation and Its Feasibility Assessment.

PloS one·2024

Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Anesthesiology

Background:

  • Biosignal analysis is crucial for understanding human diseases.
  • Electroencephalograms (EEGs) provide electrical brain activity data.
  • Anesthesia level monitoring is vital to prevent awareness and overdose.

Purpose of the Study:

  • To review EEG techniques for anesthesia monitoring.
  • To present physiological background and signal processing developments.
  • To highlight noise removal methods for EEG analysis.

Main Methods:

  • Review of historical development of EEG techniques.
  • Synopsis of methodologies and algorithms for EEG signal analysis.
  • Discussion of noise reduction strategies in EEG processing.

More Related Videos

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates
05:58

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates

Published on: September 6, 2017

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy
10:23

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Published on: June 23, 2023

Related Experiment Videos

Last Updated: May 11, 2026

Chronic Cranial Window Technique for Repeated Cortical Recordings During Anesthesia in Pigs
07:19

Chronic Cranial Window Technique for Repeated Cortical Recordings During Anesthesia in Pigs

Published on: June 6, 2025

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates
05:58

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates

Published on: September 6, 2017

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy
10:23

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Published on: June 23, 2023

Main Results:

  • EEG analysis offers a pathway to monitor anesthesia depth.
  • Signal processing advancements improve EEG data utility.
  • Effective noise removal enhances EEG signal reliability.

Conclusions:

  • Further development of EEG-based methods is needed for reliable anesthesia depth detection.
  • High data rate and flexible devices are key objectives.
  • EEG analysis holds promise for improved patient safety during anesthesia.