CSE 599E Syllabus

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In this course, we will explore BCI research along several different dimensions including: Input Signals (invasive versus non- invasive recording techniques) Feature Extraction Methods (spectral, wavelet, etc.) Machine learning for BCI (classification, regression, filtering, tracking, etc.), BCI applications (cursor control, word speller, robotic arm control, etc.). There will be a mix of lectures, invited speakers, and discussion of research papers. Paper Discussion: Students will be expected to sign up to present papers of their choice from a selected list of papers covering the topics mentioned above. Discussion Board: Before each class involving paper discussion, all students will post to the 599E discussion board short summaries and/or a brief critical analysis of the assigned paper(s) for that class. Students may also instead opt to respond to critical analyses or questions of other students that are already posted on the board. Final Group Project: There will be a final group project that will involve additional exploration of BCI research and possibly hands-on experience with BCI data. Final project groups will consist of 1-3 students. Each group will present their results to class during the last week of classes and submit a short written report. For details, see the Group Project page.

	Department of Computer Science & Engineering University of Washington Box 352350 Seattle, WA  98195-2350 (206) 543-1695 voice, (206) 543-2969 FAX [comments to rao@cs.washington.edu]