Difference between revisions of "Setup SSVEP BCI example"
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== Editing the Processing Pipeline == | == Editing the Processing Pipeline == | ||
| − | In the following figure | + | In the following figure an edited setup of the SSVEP-BCI processing pipeline is shown in the MNE-Scan GUI environment. For this example the NoiseReduction plugin was interposed as a preprocessing step in order to increase the Signal-to-Noise ratio. However, the SSVEP-BCI plugin can also be processed with the raw data by connection it directly with the acquisition plugin. |
[[File:MNE-Scan processing pipelilne.jpeg|framed|center|SSVEP BCI processing pipeline in the MNE-Scan environment]] | [[File:MNE-Scan processing pipelilne.jpeg|framed|center|SSVEP BCI processing pipeline in the MNE-Scan environment]] | ||
Revision as of 11:50, 27 October 2016
Abstract
The SSVEP-BCI plugin beholds a Brain Computer Interface (BCI) using Steady-State-Visual-Evoked-Potentials (SSVEP). It was developed under the Master Thesis "Development of a BCI based on real-time neural source localization", in which the so called Bremen-BCI was used as a role model in order to setup classification pipeline and visualization. This tutorial describes both the setup of the processing pipeline and usage of the SSVEP-BCI plugin.
Editing the Processing Pipeline
In the following figure an edited setup of the SSVEP-BCI processing pipeline is shown in the MNE-Scan GUI environment. For this example the NoiseReduction plugin was interposed as a preprocessing step in order to increase the Signal-to-Noise ratio. However, the SSVEP-BCI plugin can also be processed with the raw data by connection it directly with the acquisition plugin.
