Cargando…

An 18-subject EEG data collection using a visual-oddball task, designed for benchmarking algorithms and headset performance comparisons

This data note describes an 18-subject EEG (electroencephalogram) data collection from an experiment in which subjects performed a standard visual oddball task. Several research projects have used this data to test artifact detection, classification, transfer learning, EEG preprocessing, blink detec...

Descripción completa

Detalles Bibliográficos
Autores principales: Robbins, Kay, Su, Kyung-min, Hairston, W. David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5712810/
https://www.ncbi.nlm.nih.gov/pubmed/29226211
http://dx.doi.org/10.1016/j.dib.2017.11.032
Descripción
Sumario:This data note describes an 18-subject EEG (electroencephalogram) data collection from an experiment in which subjects performed a standard visual oddball task. Several research projects have used this data to test artifact detection, classification, transfer learning, EEG preprocessing, blink detection, and automated annotation algorithms. We are releasing the data in three formats to enable benchmarking of EEG algorithms in many areas. The data was acquired using a Biosemi Active 2 EEG headset and includes 64 channels of EEG, 4 channels of EOG (electrooculogram), and 2 mastoid reference channels.