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Material Detail

Feasibility and Pragmatics of Classifying Working Memory Load with an Electroencephalograph

Feasibility and Pragmatics of Classifying Working Memory Load with an Electroencephalograph

This video was recorded at The 26th Annual CHI Conference on Human Factors in Computing Systems. We demonstrate high accuracies classifying working memory load using an electroencephalograph (EEG), even with little temporallag, not much training data, and a small number of EEG channels.
Keywords:
videolectures, ocwc, oec
Disciplines:
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More about this material

Material Type:
Presentation
Date Added to MERLOT:
February 8, 2015
Date Modified in MERLOT:
March 12, 2017
Author:
Submitter:
The Open Education Consortium
Primary Audience:
College General Ed, College Lower Division, College Upper Division
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States

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