ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals
The ChMinMaxPat-based SOXFE model demonstrates high classification accuracy and interpretability in detecting violence and stress from EEG signals. This model contributes to both feature engineering and neuroscience by enabling explainable EEG classification, underscoring the potential importance of EEG analysis in clinical and forensic applications.
Authors
- Serkan Kırık (ORCID: https://orcid.org/0000-0002-8658-2448)
- Şengül Doğan (ORCID: https://orcid.org/0000-0001-9677-5684)
- Ömer Bektaş (ORCID: https://orcid.org/0000-0002-2514-8461)
- İrem Taşçı (ORCID: https://orcid.org/0000-0001-7069-769X)
- Türker Tuncer (ORCID: https://orcid.org/0000-0002-5126-6445)
- Emrah Aydemir (ORCID: https://orcid.org/0000-0002-8380-7891)
- Rena Hajiyeva
Institutions
- Sakarya University (TR)
- Fırat University (TR)
- Ankara University (TR)
- Western Caspian University (AZ)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-11-26
- DOI
- https://doi.org/10.3390/diagnostics14232666
- Citations
- 7
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 2.40