Seizure forecasting with ultra long-term EEG signals
The feasibility of cross-patient forecasting supports the universal importance of mid-term dynamics for seizure forecasting, demonstrates promising inter-subject-applicability of the scheme on ultra long-term EEG recordings, and highlights its huge potential for clinical use.
Authors
- Ronald Tetzlaff (ORCID: https://orcid.org/0000-0001-7436-0103)
- Matthias Eberlein (ORCID: https://orcid.org/0000-0002-6188-8029)
- Hongliu Yang (ORCID: https://orcid.org/0000-0002-6021-0187)
- Georg Leonhardt (ORCID: https://orcid.org/0009-0005-5892-0525)
- Troels W. Kjær (ORCID: https://orcid.org/0000-0002-2105-6199)
- Jonas Duun‐Henriksen (ORCID: https://orcid.org/0000-0003-1558-8225)
- Jens Müller (ORCID: https://orcid.org/0000-0001-9875-3534)
- Sotirios Kalousios (ORCID: https://orcid.org/0009-0007-7072-9576)
Institutions
- Zealand University Hospital (DK)
- Oticon Medical (Denmark) (DK)
- University Hospital Carl Gustav Carus (DE)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- Clinical Neurophysiology
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1016/j.clinph.2024.09.017
- Citations
- 5
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.71
Funders
- Technische Universität Dresden
- Else Kröner-Fresenius-Stiftung
- Freistaat Sachsen
- European Regional Development Fund