Frequency Band Variations Predict EEG Single-Trial Classification Performance in Disorder of Consciousness Patients
| Autor: | Helge Ritter, Inga Steppacher, Johanna Kissler, Andrea Finke |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Consciousness
Computer science Frequency band media_common.quotation_subject Feature extraction 02 engineering and technology Electroencephalography 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering medicine Humans media_common Measure (data warehouse) medicine.diagnostic_test business.industry Dimensionality reduction Pattern recognition Class (biology) Mental state Consciousness Disorders 020201 artificial intelligence & image processing Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | Single-trial classification of EEG data from Disorder of Consciousness patients (DoC) has proved particularly challenging. We present an approach that establishes a measure to relate the performance of single-trial classification of DoC patient EEG data with relational frequency bands and thus with their mental state. We evaluate our approach on 31 patient data sets from two studies, showing that our measure indicates for different data sets a particular likelihood for misclassifying either target or non-target class samples. |
| Databáze: | OpenAIRE |
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