Difference between revisions of "Application Group"
From ESE497 Wiki
Jump to navigationJump to searchMWronkiewicz (talk | contribs) (Created page with ''''Project and Motivation''' Our group is currently focused on refining techniques for gathering strong and clear data with our electroencephalograph (EEG) headset to control br…') |
MWronkiewicz (talk | contribs) |
||
| (2 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
'''Project and Motivation''' | '''Project and Motivation''' | ||
| − | Our group is currently focused on refining techniques for gathering strong and clear data with our electroencephalograph (EEG) headset to control brain computer interfaces (BCI). Once this problem | + | Our group is currently focused on refining techniques for gathering strong and clear data with our electroencephalograph (EEG) headset to control brain computer interfaces (BCI). Once this problem is resolved, the improved data will make projects such as 2D control, spatial filtering, and artifact identification/removal more targeted and reliable. Overall, this translates to faster analysis and more meaningful results. |
| − | is resolved, the improved data will make projects such as 2D control, spatial filtering, and artifact | + | |
| − | identification/removal more targeted and reliable, | + | The most recent hypotheses tested includes comparing: |
| − | |||
*signals generated from motor imagery (imagining movement) versus actual motor movement | *signals generated from motor imagery (imagining movement) versus actual motor movement | ||
*signals generated from a person’s dominant side versus their weak side | *signals generated from a person’s dominant side versus their weak side | ||
| − | *signals generated from a repeated movement versus a single held movement | + | *signals generated from a repeated movement versus a single held movement |
Latest revision as of 16:17, 14 November 2011
Project and Motivation
Our group is currently focused on refining techniques for gathering strong and clear data with our electroencephalograph (EEG) headset to control brain computer interfaces (BCI). Once this problem is resolved, the improved data will make projects such as 2D control, spatial filtering, and artifact identification/removal more targeted and reliable. Overall, this translates to faster analysis and more meaningful results.
The most recent hypotheses tested includes comparing:
- signals generated from motor imagery (imagining movement) versus actual motor movement
- signals generated from a person’s dominant side versus their weak side
- signals generated from a repeated movement versus a single held movement
