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| − | == Abstract ==
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| − | The purpose of this project is to determine the optimal spatial filtering techniques for a Brain-Computer Interface (BCI) using an Emotiv Epoc EEG headset. Each type of spatial filter is a tool used to improve the characteristics of a signal using different patterns of linear combinations of electrodes. Those combinations produce a new signal with less noise, which gives BCI patients better control over the device.
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| − | In general, the methods used are a simple ear-reference, Bipolar filters, Common Average Reference filters, and Laplacian filters. Bipolar filters combine any two electrodes. Common Average Reference filters use the mean of every electrode's voltage at a given time as their zero. Laplacian filters use several near neighbor electrodes to approximate a spatial second derivative of the signal. While the Emotiv headset offers several advantages for BCI applications, its limited number of electrodes makes generating accurate signals much more difficult, particularly for Laplacian filters. Obtaining high-quality signals given these limitations is the primary goal of this investigation.
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| | == Still to do == | | == Still to do == |
| | • Determine the effectiveness of each filter created for the Emotiv headset. | | • Determine the effectiveness of each filter created for the Emotiv headset. |
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| | • Code a script to optimize possible linear combinations of electrodes for R^2. | | • Code a script to optimize possible linear combinations of electrodes for R^2. |
Revision as of 15:52, 15 December 2011
Still to do
• Determine the effectiveness of each filter created for the Emotiv headset.
• Code a script to optimize possible linear combinations of electrodes for R^2.
