Some functions in NBT require the Mathwork's Statistics Toolbox (and as NBT develops, potentially other toolboxes). If you have ideas to code NBT more efficiently (e.g., your own statistics toolbox?), then please let us know.
Our tutorials aim at showing how to use the NBT GUI to visualize, pre-process, compute biomarkers and biomarker statistics for your data. We will mainly focus on how to analyze electroencephalography (EEG) signals.
For demonstration we use a demo EEG dataset. The demo dataset contains recordings of 129 EEG channels from 16 subjects in two conditions (eyes closed (ECR1) and eyes opened (EOR1)), downsampled at 200Hz. The format of the dataset follows the NBT standard (for more info see Importing data into nbt format).
Two versions of the data are available for download. The first version contains unprocessed (Raw) data, for the second (Clean) version artifacts have been removed with semi-automatic methods. You can use the Clean version to evaluate the quality of your processing of the Raw data.
In the following tutorial we will show you how to process the Raw NBT signals. If you do not want to learn how to use NBT for artifact cleaning of EEG signals, but only want to try to compute biomarkers or biomarker statistics then download