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

Content Provider	IEEE Xplore Digital Library
Author	Abdur-Rahim, J. Ogawa, T. Hirayama, J.-I. Ishii, S.
Copyright Year	2014
Description	Author affiliation: Dept. of Dynamic Brain Imaging, Adv. Telecommun. Res. Inst. Int. (ATR), Kyoto, Japan (Abdur-Rahim, J.; Ogawa, T.; Hirayama, J.-I.; Ishii, S.)
Abstract	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.
Starting Page	180
Ending Page	180
File Size	657516
Page Count	1
File Format	PDF
ISBN	9781479923465
DOI	10.1109/BioCAS.2014.6981683
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-22
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain Imaging Educational institutions Electroencephalography Telecommunications Standards Graphical user interfaces
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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

Live demonstration: A high-speed-pass asynchronous motion detection sensor

Rule-based detection for reverse engineering user interfaces

Parallel man-machine training in development of EEG-based cursor control

EEG band powers for characterizing user engagement in P300-BCI

EEG-based detection technique of moving picture image

A New Blind Source Separation Method to Remove Artifact in EEG Signals

Two player EEG-based neurofeedback ball game for attention enhancement

Selection and removal of artifacts in EEG based on independent components

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

Similar Documents

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

Live demonstration: A high-speed-pass asynchronous motion detection sensor

Rule-based detection for reverse engineering user interfaces

Parallel man-machine training in development of EEG-based cursor control

EEG band powers for characterizing user engagement in P300-BCI

EEG-based detection technique of moving picture image

A New Blind Source Separation Method to Remove Artifact in EEG Signals

Two player EEG-based neurofeedback ball game for attention enhancement

Selection and removal of artifacts in EEG based on independent components

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