Missing Data Gap Imputation Methods in Electroencephalogram (EEG) Signals: A Systematic Scoping Review
This work provides novel insights into existing methods for EEG gap imputation, as it identifies current shortcomings in the literature and paves a way for a more generalizable solution to be achieved through future work.
Authors
- Kevin Y. Stein (ORCID: https://orcid.org/0000-0002-5983-008X)
- Hina Shaheen (ORCID: https://orcid.org/0000-0002-4021-6792)
- Izabella Marquez
- Rakibul Hasan (ORCID: https://orcid.org/0000-0003-2236-0245)
- Frederick Adam Zeiler (ORCID: https://orcid.org/0000-0003-1737-0510)
- Yushu Shao
- Amanjyot Singh Sainbhi (ORCID: https://orcid.org/0000-0003-3231-5683)
- Nuray Vakitbilir (ORCID: https://orcid.org/0000-0003-2764-145X)
- Tobias J. G. Bergmann (ORCID: https://orcid.org/0009-0001-1082-6485)
- Isuru Herath (ORCID: https://orcid.org/0000-0002-3762-8374)
- Noah Silvaggio (ORCID: https://orcid.org/0009-0003-3860-8134)
- Xue Nemoga‐Stout
- Jaewoong Moon
- Julia Ryznar
- Michael Movshovich (ORCID: https://orcid.org/0009-0009-5179-7105)
Institutions
- University of Cambridge (GB)
- Karolinska Institutet (SE)
- Pan Am Clinic (CA)
- Addenbrooke's Hospital (GB)
- University of Manitoba (CA)
Publication Details
- Journal
- Sensors
- Published
- 2026-04-15
- DOI
- https://doi.org/10.3390/s26082431
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Research Manitoba
- Canadian Institutes of Health Research
- Natural Sciences and Engineering Research Council of Canada