Live demonstration: Database-driven artifact detection method for EEG systems with few channels (DAD)

The equipment that I intend to bring are the following: laptop, poster presentation, and a mobile BCI device. I intend to prepare a poster presentation explaining the work demonstrated in the paper, such that conference participants can interactively learn about the topics in the paper. The poster will outline the steps of the algorithm, along with how to choose the database. After a brief discussion of the algorithm using the poster, a laptop will be used to demonstrate how to load new data into the algorithm in order to remove artifacts and tag parts of the data that may contain behavioral information. Figure 1 shows a screenshot of the interactive program that will demonstrate the algorithm and show output information that the user should expect. The curves that will be displayed in the figures from top to bottom will show the following: the newly loaded dataset, the output of the standard method such that areas of detected artifact will be highlighted, the output of the DAD method such that areas of detected artifact will be highlighted, the output of the DAD method such that areas of detected behaviors (based on the artifacts) will be highlighted. The GUI (Graphical User Interface) program will be demonstrated using two datasets; data shown in the paper that was collected using our BMI device and a public dataset from the The University of California at San Diego (http://sccn.ucsd.edu/~arno/fam2data/publicly available EEG data.html). In addition, it will be shown that the DAD GUI will automatically save the artifact-free dataset and a text file documenting the types of artifacts and behaviors found. The BCI device will but used to visually illustrate how artifacts can occur and contaminate the EEG signal, thus further motivating the need for artifact removal methods.