Fronto-Temporal Analysis of EEG Signals of Patients with Depression: Characterisation, Nonlinear Dynamics and Surrogate Analysis
The recent advances in signal processing techniques have enabled the analysis of biosignals from brain so as to enhance the predictive capability of mental states. Biosignal analysis has been successfully used to characterise EEG signals of unipolar depression patients. Methods of characterisation o...
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2020
|
| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/73902 |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares: Fronto-Temporal Analysis of EEG Signals of Patients with Depression: Characterisation, Nonlinear Dynamics and Surrogate Analysis
- Fronto-parietal and fronto-temporal EEG coherence as predictive neuromarkers of transcutaneous auricular vagus nerve stimulation response in treatment-resistant schizophrenia: A machine learning study
- Characterising Alzheimer's Disease with EEG-based Energy Landscape Analysis
- Wavelet Transform for the Analysis of EEG Signals in Patients with Oral Communications Problems
- EEG Analysis during Music Perception
- Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition
- Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures