/**
 * \page BoxAlgorithm_GrazVisualization Graz visualization
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Detailed description
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 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Description|
The Graz visualization box implements the display of the well-known 
Graz BCI paradigm,  typically used for Motor Imagery BCI experiments. 
The paradigm is described e.g. in Pfurtscheller & Neuper, 
"Motor Imagery and Direct Brain-Computer Communication", 2001.

In its most common use, the Graz visualization instructs the user to 
perform either left or right hand motor imagery by presenting left and 
right arrows, correspondingly. In order to know when to present what, 
the box must be driven with a stimulation stream that provides the 
timeline of the experiment, including trial starts, trial stops, etc.

The same box can be used both for data collection and for real-time
displays. When used real time, the box can display a directional blue
bar to illustrate the strength and direction of the prediction.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Description|
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Inputs description
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 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Inputs|
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Inputs|

 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Input1|
 The timeline of the events.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Input1|

 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Input2|
 For online use and feedback, the strength of the current activation.
 This can be for example the continuous output from a classifier. 
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Input2|
  
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Settings description
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 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Settings|
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Settings|

 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Setting1|
If true, the user will be shown the arrows.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Setting1|

 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Setting2|
If true, the current activation will be presented as feedback in form of a blue bar.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Setting2|
 
 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Setting3|
If true, feedback will be shown only after the trial. Otherwise immediately.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Setting3|
 
 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Setting4|
If true, a little matrix will display how many online trials matched the arrow direction.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Setting4|
 
 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Setting5|
How many predictions to integrate for computing the feedback bar?
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Setting5|
 
 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Setting6|
If true, the blue bar will only be displayed if its direction agrees with the arrow.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Setting6|
 
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Online visualization settings
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 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_OnlineVisualizationSettings|
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_OnlineVisualizationSettings|
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Examples description
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 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Examples|
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Examples|

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Miscellaneous description
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 * |OVP_DocBegin_BoxAlgorithm_GrazVisualization_Miscellaneous|
The timeline required by the box can be generated by a Lua stimulator. 
OpenViBE is bundled with a few motor imagery examples illustrating 
this (in folder "bci-examples/").

In order to place the markers (stimulations) to the recorded EEG stream accurately in time, 
the box connects to the Acquisition Server's TCP Tagging plugin and forwards the received 
timeline there after rendering. The subsequent scenarios and writers should then use the timeline 
from the Acquisition Server output and not directly from the timeline generating box. But 
due to the long duration of time the motor imagery is typically integrated, this paradigm 
could be less sensitive to marker alignment issues compared e.g. to P300.
 * |OVP_DocEnd_BoxAlgorithm_GrazVisualization_Miscellaneous|
 */
