This study aims to build a benchmark dataset of expert-annotated EEG artifacts. Participants review EEG recordings and mark regions and channels containing artifacts or likely bad data. These annotations will be released to the community to help develop better automated artifact detection algorithms.
We are looking for researchers and practitioners with experience working with EEG data. In particular we are looking for researchers that have published or have in review at least one paper or conference abstract for which they have manually cleaned EEG data
After registering and completing a brief background questionnaire, you will be shown EEG recordings in an interactive viewer. You will mark channels and time segments that you believe contain artifacts, and indicate the type and severity of each artifact.
Participants who label all 100 datasets will recieve a co-authorship on a paper describing the study and dataset.
Please visit our Contact page and get in touch with the study team. We are happy to help.