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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Prevalence, Antimicrobial Resistance, and Resistance Gene Profiles of Extended-Spectrum β-Lactamase-Producing Escherichia coli and Klebsiella pneumoniae Isolated From Quails in Sylhet, Bangladesh.

MicrobiologyOpen·2026
Same author

Interpolation and Imputation Strategies for Missing Segments in Continuous Pressure-Flow Cerebral Bio-Signals: A Systematic Scoping Review.

Sensors (Basel, Switzerland)·2026
Same author

Comparative analysis of processed EEG indices and entropy-based metrics for assessing anesthetic depth: a scoping review - PRISMA-ScR.

BMC biomedical engineering·2026
Same author

Green synthesis and characterization of zinc chitosan nanoparticles with their anti-bacterial study against rice pathogen Xanthomonas oryzae pv. oryzae.

PloS one·2026
Same author

Assessment of Pet Owners' Knowledge on Parasitic Infection in Sylhet City Corporation, Bangladesh.

Journal of parasitology research·2026
Same author

Detection of regional disparity in cerebrovascular reactivity using a custom whole brain functional near-infrared spectroscopy based mapping system: A prospective observational study.

PLOS digital health·2026

Related Experiment Video

Updated: May 5, 2026

Author Spotlight: Capturing Infant-Caregiver Interactions Through Synchronized Multimodal Data Collection
08:08

Author Spotlight: Capturing Infant-Caregiver Interactions Through Synchronized Multimodal Data Collection

Published on: May 31, 2024

1.7K

Missing Data Gap Imputation Methods in Electroencephalogram (EEG) Signals: A Systematic Scoping Review.

Tobias Bergmann1, Michael Movshovich2, Yushu Shao3

  • 1Graduate Program in Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Sensors (Basel, Switzerland)
|May 4, 2026
PubMed
Summary
This summary is machine-generated.

This review examines electroencephalogram (EEG) signal gap imputation methods. While several techniques show promise, limited generalizability and data diversity prevent identifying a leading approach for reconstructing missing EEG data.

Keywords:
electroencephalogramgap reconstructionimputation methodologiesmissing segments

More Related Videos

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
10:22

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Published on: December 6, 2016

22.8K
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

3.5K

Related Experiment Videos

Last Updated: May 5, 2026

Author Spotlight: Capturing Infant-Caregiver Interactions Through Synchronized Multimodal Data Collection
08:08

Author Spotlight: Capturing Infant-Caregiver Interactions Through Synchronized Multimodal Data Collection

Published on: May 31, 2024

1.7K
Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
10:22

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Published on: December 6, 2016

22.8K
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

3.5K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Electroencephalogram (EEG) is crucial for understanding brain activity.
  • Missing data in EEG signals is a common problem, impacting analysis.
  • Imputation techniques are necessary to reconstruct these data gaps.

Purpose of the Study:

  • To systematically review and analyze existing methods for imputing missing data in EEG signals.
  • To identify the strengths and limitations of various EEG imputation techniques.
  • To guide future research in developing more robust and generalizable imputation solutions.

Main Methods:

  • A comprehensive literature search was conducted across five databases.
  • Systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.
  • Categorization of identified imputation methods into tensor-based, machine learning/deep learning, and model-based/classical approaches.

Main Results:

  • Sixteen articles detailing EEG gap imputation methods were included in the review.
  • Methods were classified into tensor-based, machine learning/deep learning, and model-based/classical categories.
  • Several methods demonstrated high accuracy in reconstructing 'ground truth' EEG signal gaps.

Conclusions:

  • No single imputation method is universally superior due to limited generalizability and dataset diversity.
  • Some methods' reliance on full recordings hinders real-time imputation applications.
  • Further research is needed to address limitations and investigate computational efficiency for widespread EEG data gap imputation.