TUH_EEG: In this project, we are developing the largest EEG corpus ever to be publicly released. The corpus consists of over 20,000 EEGs dating back to 2002. In addition to the raw signal data, metadata about the subjects is available, including medical conditions and treatments. Physician interpretations of the data are also included making this an invaluable resource for machine learning experiments.

TUH EEG Abnormal EEG Corpus : This is a subset of the TUH EEG Corpus that can be used for automatic detection of abnormal EEGs.

TUH EEG Epilepsy: This is a subset of the TUH EEG Corpus that contains 100 subjects with and without epilepsy.

TUH EEG Seizure: This is the first official release of a subset of the TUH EEG Corpus that has been manually annotated for seizure events.

Computational Resources

Neuronix: The Neuronix high performance computing cluster allows us to conduct BigData machine learning research consisting of 128 cores, 21TB NFS, 1TB RAM, and a central NFS server. The system is being used to develop AutoEEG™ on a large corpus of over 28,000 EEGs as part of a commercialization effort.


Gitlab: This is the repository that contains the Neural Engineering Data Consortium's foundation classes and general software.