This commit is contained in:
2021-10-14 13:47:35 +02:00
commit 6625a8dfaa
4026 changed files with 844291 additions and 0 deletions
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<Text>&lt;u&gt;&lt;b&gt;&lt;big&gt;Overview&lt;/big&gt;&lt;/b&gt;&lt;/u&gt;
This scenario can be used in order
to check the quality of the signals
before starting an experiment.
One should &lt;u&gt;definitely&lt;/u&gt;
check the quality of the signals
and ensure that :
- &lt;b&gt;eye blinks&lt;/b&gt; are visible
- &lt;b&gt;jaw clenching&lt;/b&gt; are visible
- &lt;b&gt;alpha waves&lt;/b&gt; are visible when closing eyes</Text>
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<Text>The &lt;i&gt;Temporal Filter&lt;/i&gt;
box transform the signal
so you can see what is actually
used online.</Text>
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<Text>&lt;u&gt;&lt;b&gt;Note:&lt;/b&gt;&lt;/u&gt; It is always a good idea to
monitor the signals during an experiment</Text>
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<Text>&lt;u&gt;&lt;b&gt;&lt;big&gt;Overview&lt;/big&gt;&lt;/b&gt;&lt;/u&gt;
This scenario can be used as a first
step to collect some training data. Those
data will later be used to train a classifier
for online use.
When you start this scenario, just wait 40
seconds before it starts the instruction sequence.
You will then be presented left / right arrows to
let you imagine left / right hand movements.
There will be 20 arrows of each side.
&lt;small&gt;&lt;i&gt;&lt;b&gt;note:&lt;/b&gt; the recorded files go to the
folder where the scenario xml is located
(&lt;span color="darkblue"&gt;${Player_ScenarioDirectory}/&lt;/span&gt;).&lt;/i&gt;&lt;/small&gt;</Text>
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<Text>The Graz Visualization box will send the timeline
markers directly to Acquisition Server using the
TCP Tagging plugin. The server will then attach them
appropriately to the EEG stream.</Text>
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<Value>1007</Value>
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<Comment>
<Identifier>(0x000008e3, 0x00002907)</Identifier>
<Text>&lt;b&gt;--::&lt;/b&gt; Remember to &lt;b&gt;change the file&lt;/b&gt;
to the one you recorded before!</Text>
<Attributes>
<Attribute>
<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
<Value>1232.000000</Value>
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<Value>-336.000000</Value>
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<Comment>
<Identifier>(0x00003594, 0x000016a6)</Identifier>
<Text>&lt;u&gt;&lt;b&gt;&lt;big&gt;Overview&lt;/big&gt;&lt;/b&gt;&lt;/u&gt;
This scenario trains the &lt;i&gt;Common Spatial Pattern&lt;/i&gt; spatial filter
that will be used in the further steps.
The EEG signal is filtered in a large frequency band [8-30 Hz].
Then the &lt;i&gt;Stimulation based epoching&lt;/i&gt; boxes
provide examples for the &lt;i&gt;CSP Spatial Filter Trainer&lt;/i&gt; :
class 1: LEFT trials
class 2: RIGHT trials
At the end of the training process,
the CSP trainer outputs the stimulation
&lt;b&gt;OVTK_StimulationId_TrainCompleted&lt;/b&gt; on success,
telling the &lt;i&gt;Player Controller&lt;/i&gt; to pause the scenario.</Text>
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<Value>-208.000000</Value>
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</Comment>
<Comment>
<Identifier>(0x00007e47, 0x000066f8)</Identifier>
<Text>You can browse each box' documentation by selecting the box and pressing &lt;b&gt;F1&lt;/b&gt;</Text>
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<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
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<Metadata>
<Entry>
<Identifier>(0x0000775c, 0x000078ff)</Identifier>
<Type>(0x3bcce5d2, 0x43f2d968)</Type>
<Data>[{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"height":400,"identifier":"(0x00001209, 0x000052ed)","index":0,"name":"Default window","parentIdentifier":"(0xffffffff, 0xffffffff)","type":1,"width":400},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"identifier":"(0x00002598, 0x00002e05)","index":0,"name":"Default tab","parentIdentifier":"(0x00001209, 0x000052ed)","type":2},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":0,"identifier":"(0x0000121e, 0x000031a2)","index":0,"name":"Empty","parentIdentifier":"(0x00002598, 0x00002e05)","type":0}]</Data>
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@@ -0,0 +1,50 @@
g_offset = nil
g_duration = nil
-- this function is called when the box is initialized
function initialize(box)
dofile(box:get_config("${Path_Data}") .. "/plugins/stimulation/lua-stimulator-stim-codes.lua")
g_offset = box:get_setting(2)
g_duration = box:get_setting(3)
end
-- this function is called when the box is uninitialized
function uninitialize(box)
end
function wait_until(box, time)
while box:get_current_time() < time do
box:sleep()
end
end
function wait_for(box, duration)
wait_until(box, box:get_current_time() + duration)
end
function process(box)
-- loops on every received stimulation for a given input
while box:keep_processing() do
for stimulation = 1, box:get_stimulation_count(1) do
-- gets the received stimulation
identifier, date, duration = box:get_stimulation(1, 1)
-- discards it
box:remove_stimulation(1, 1)
-- delay the OVTK_GDF_Left and Right
if identifier == OVTK_GDF_Left or identifier == OVTK_GDF_Right then
box:send_stimulation(1, OVTK_GDF_Correct, date+g_offset, 0)
box:send_stimulation(1, OVTK_GDF_Incorrect, date+g_offset+g_duration, 0)
end
end
box:sleep()
end
end
@@ -0,0 +1,97 @@
function initialize(box)
dofile(box:get_config("${Path_Data}") .. "/plugins/stimulation/lua-stimulator-stim-codes.lua")
number_of_trials = box:get_setting(2)
first_class = _G[box:get_setting(3)]
second_class = _G[box:get_setting(4)]
baseline_duration = box:get_setting(5)
wait_for_beep_duration = box:get_setting(6)
wait_for_cue_duration = box:get_setting(7)
display_cue_duration = box:get_setting(8)
feedback_duration = box:get_setting(9)
end_of_trial_min_duration = box:get_setting(10)
end_of_trial_max_duration = box:get_setting(11)
-- initializes random seed
math.randomseed(os.time())
-- fill the sequence table with predifined order
sequence = {}
for i = 1, number_of_trials do
table.insert(sequence, 1, first_class)
table.insert(sequence, 1, second_class)
end
-- randomize the sequence
for i = 1, number_of_trials do
a = math.random(1, number_of_trials*2)
b = math.random(1, number_of_trials*2)
swap = sequence[a]
sequence[a] = sequence[b]
sequence[b] = swap
end
end
function process(box)
local t=0
-- manages baseline
box:send_stimulation(1, OVTK_StimulationId_ExperimentStart, t, 0)
t = t + 5
box:send_stimulation(1, OVTK_StimulationId_BaselineStart, t, 0)
box:send_stimulation(1, OVTK_StimulationId_Beep, t, 0)
t = t + baseline_duration
box:send_stimulation(1, OVTK_StimulationId_BaselineStop, t, 0)
box:send_stimulation(1, OVTK_StimulationId_Beep, t, 0)
t = t + 5
-- manages trials
for i = 1, number_of_trials*2 do
-- first display cross on screen
box:send_stimulation(1, OVTK_GDF_Start_Of_Trial, t, 0)
box:send_stimulation(1, OVTK_GDF_Cross_On_Screen, t, 0)
t = t + wait_for_beep_duration
-- warn the user the cue is going to appear
box:send_stimulation(1, OVTK_StimulationId_Beep, t, 0)
t = t + wait_for_cue_duration
-- display cue
box:send_stimulation(1, sequence[i], t, 0)
t = t + display_cue_duration
-- provide feedback
box:send_stimulation(1, OVTK_GDF_Feedback_Continuous, t, 0)
t = t + feedback_duration
-- ends trial
box:send_stimulation(1, OVTK_GDF_End_Of_Trial, t, 0)
t = t + math.random(end_of_trial_min_duration, end_of_trial_max_duration)
end
-- send end for completeness
box:send_stimulation(1, OVTK_GDF_End_Of_Session, t, 0)
t = t + 5
box:send_stimulation(1, OVTK_StimulationId_Train, t, 0)
t = t + 1
-- used to cause the acquisition scenario to stop
box:send_stimulation(1, OVTK_StimulationId_ExperimentStop, t, 0)
end
@@ -0,0 +1,3 @@
The scenario will record its signals here.
@@ -0,0 +1,816 @@
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<Text>The &lt;i&gt;Temporal Filter&lt;/i&gt;
box transform the signal
so you can see what is actually
used online.</Text>
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<Text>You can browse each box' documentation by selecting the box and pressing &lt;b&gt;F1&lt;/b&gt;</Text>
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<Text>&lt;u&gt;&lt;b&gt;&lt;big&gt;Overview&lt;/big&gt;&lt;/b&gt;&lt;/u&gt;
This scenario can be used in order
to check the quality of the signals
before starting an experiment.
One should &lt;u&gt;definitely&lt;/u&gt;
check the quality of the signals
and ensure that :
- &lt;b&gt;eye blinks&lt;/b&gt; are visible
- &lt;b&gt;jaw clenching&lt;/b&gt; are visible
- &lt;b&gt;alpha waves&lt;/b&gt; are visible when closing eyes</Text>
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</OpenViBE-Scenario>
@@ -0,0 +1,584 @@
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</Attribute>
<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
</Attribute>
<Attribute>
<Identifier>(0xc80ce8af, 0xf699f813)</Identifier>
<Value>5</Value>
</Attribute>
<Attribute>
<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
<Value>2</Value>
</Attribute>
</Attributes>
</Box>
<Box>
<Identifier>(0x42570b5c, 0x0bba079c)</Identifier>
<Name>Graz visualization</Name>
<AlgorithmClassIdentifier>(0x00dd290d, 0x5f142820)</AlgorithmClassIdentifier>
<Inputs>
<Input>
<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
<Name>Stimulations</Name>
</Input>
<Input>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Amplitude</Name>
</Input>
</Inputs>
<Outputs>
<Output>
<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
<Name>Confusion Matrix</Name>
</Output>
</Outputs>
<Settings>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Show instruction</Name>
<DefaultValue>true</DefaultValue>
<Value>true</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Show feedback</Name>
<DefaultValue>false</DefaultValue>
<Value>true</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Delay feedback</Name>
<DefaultValue>false</DefaultValue>
<Value>false</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Show accuracy</Name>
<DefaultValue>false</DefaultValue>
<Value>false</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
<Name>Predictions to integrate</Name>
<DefaultValue>5</DefaultValue>
<Value>5</Value>
<Modifiability>false</Modifiability>
</Setting>
<Setting>
<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
<Name>Positive feedback only</Name>
<DefaultValue>false</DefaultValue>
<Value>false</Value>
<Modifiability>false</Modifiability>
</Setting>
</Settings>
<Attributes>
<Attribute>
<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
<Value>-160</Value>
</Attribute>
<Attribute>
<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
<Value>611</Value>
</Attribute>
<Attribute>
<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
<Value>(0x602ceb3f, 0xd3bc74aa)</Value>
</Attribute>
<Attribute>
<Identifier>(0xc73e83ec, 0xf855c5bc)</Identifier>
<Value>false</Value>
</Attribute>
<Attribute>
<Identifier>(0xc80ce8af, 0xf699f813)</Identifier>
<Value>1</Value>
</Attribute>
<Attribute>
<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
<Value>6</Value>
</Attribute>
<Attribute>
<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
<Value>2</Value>
</Attribute>
</Attributes>
</Box>
</Boxes>
<Links>
<Link>
<Identifier>(0x00000477, 0x000079b6)</Identifier>
<Source>
<BoxIdentifier>(0x00000de5, 0x00006f3d)</BoxIdentifier>
<BoxOutputIndex>0</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x42570b5c, 0x0bba079c)</BoxIdentifier>
<BoxInputIndex>0</BoxInputIndex>
</Target>
</Link>
<Link>
<Identifier>(0x000012ec, 0x00006d3e)</Identifier>
<Source>
<BoxIdentifier>(0x0000430f, 0x00004aa4)</BoxIdentifier>
<BoxOutputIndex>2</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x000013d3, 0x000029d9)</BoxIdentifier>
<BoxInputIndex>2</BoxInputIndex>
</Target>
</Link>
<Link>
<Identifier>(0x000017d1, 0x000042cf)</Identifier>
<Source>
<BoxIdentifier>(0x0000430f, 0x00004aa4)</BoxIdentifier>
<BoxOutputIndex>2</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x00003f97, 0x0000658d)</BoxIdentifier>
<BoxInputIndex>0</BoxInputIndex>
</Target>
</Link>
<Link>
<Identifier>(0x000020ed, 0x00002f60)</Identifier>
<Source>
<BoxIdentifier>(0x0000430f, 0x00004aa4)</BoxIdentifier>
<BoxOutputIndex>1</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x000013d3, 0x000029d9)</BoxIdentifier>
<BoxInputIndex>1</BoxInputIndex>
</Target>
</Link>
<Link>
<Identifier>(0x00006ce5, 0x00005a2d)</Identifier>
<Source>
<BoxIdentifier>(0x0000430f, 0x00004aa4)</BoxIdentifier>
<BoxOutputIndex>0</BoxOutputIndex>
</Source>
<Target>
<BoxIdentifier>(0x000013d3, 0x000029d9)</BoxIdentifier>
<BoxInputIndex>0</BoxInputIndex>
</Target>
</Link>
</Links>
<Comments>
<Comment>
<Identifier>(0x00003459, 0x0000263e)</Identifier>
<Text>&lt;u&gt;&lt;b&gt;Note:&lt;/b&gt;&lt;/u&gt; It is always a good idea to
monitor the signals during an experiment</Text>
<Attributes>
<Attribute>
<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
<Value>976</Value>
</Attribute>
<Attribute>
<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
<Value>32</Value>
</Attribute>
</Attributes>
</Comment>
<Comment>
<Identifier>(0x00003f81, 0x00006bfa)</Identifier>
<Text>The Graz Visualization box will send the timeline
markers directly to Acquisition Server using the
TCP Tagging plugin. The server will then attach them
appropriately to the EEG stream.</Text>
<Attributes>
<Attribute>
<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
<Value>288.000000</Value>
</Attribute>
<Attribute>
<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
<Value>-128.000000</Value>
</Attribute>
</Attributes>
</Comment>
<Comment>
<Identifier>(0x000045c5, 0x00003961)</Identifier>
<Text>&lt;u&gt;&lt;b&gt;&lt;big&gt;Overview&lt;/big&gt;&lt;/b&gt;&lt;/u&gt;
This scenario can be used as a first
step to collect some training data. This
data will later be used to train a classifier
for online use.
When you start this scenario, just wait 30
seconds before it starts the instruction sequence.
You will then be presented left / right arrows to
let you imagine left / right hand movements.
There will be 20 arrows of each side.
&lt;small&gt;&lt;i&gt;&lt;b&gt;note:&lt;/b&gt; the recorded files go to the
folder where the scenario xml is located
(&lt;span color="darkblue"&gt;${Player_ScenarioDirectory}/&lt;/span&gt;).&lt;/i&gt;&lt;/small&gt;</Text>
<Attributes>
<Attribute>
<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
<Value>976</Value>
</Attribute>
<Attribute>
<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
<Value>-176</Value>
</Attribute>
</Attributes>
</Comment>
<Comment>
<Identifier>(0x0000520b, 0x000068f6)</Identifier>
<Text>You can browse each box' documentation by selecting the box and pressing &lt;b&gt;F1&lt;/b&gt;</Text>
<Attributes>
<Attribute>
<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
<Value>544</Value>
</Attribute>
<Attribute>
<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
<Value>-288</Value>
</Attribute>
</Attributes>
</Comment>
</Comments>
<Metadata>
<Entry>
<Identifier>(0x0000775c, 0x000078ff)</Identifier>
<Type>(0x3bcce5d2, 0x43f2d968)</Type>
<Data>[{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"height":505,"identifier":"(0x00006479, 0x00004325)","name":"Default window","parentIdentifier":"(0xffffffff, 0xffffffff)","type":1,"width":608},{"boxIdentifier":"(0x42570b5c, 0x0bba079c)","childCount":0,"identifier":"(0x1dfd166f, 0x4da413ec)","parentIdentifier":"(0xffffffff, 0xffffffff)","type":3},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"identifier":"(0x00000940, 0x00007014)","index":0,"name":"Default tab","parentIdentifier":"(0x00006479, 0x00004325)","type":2},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":0,"identifier":"(0x000053b1, 0x0000293b)","index":0,"name":"Empty","parentIdentifier":"(0x00000940, 0x00007014)","type":0}]</Data>
</Entry>
</Metadata>
<Attributes>
<Attribute>
<Identifier>(0x790d75b8, 0x3bb90c33)</Identifier>
<Value>Yann Renard / Fabien Lotte</Value>
</Attribute>
<Attribute>
<Identifier>(0x8c1fc55b, 0x7b433dc2)</Identifier>
<Value></Value>
</Attribute>
<Attribute>
<Identifier>(0x9f5c4075, 0x4a0d3666)</Identifier>
<Value>Data Acquisition</Value>
</Attribute>
<Attribute>
<Identifier>(0xf36a1567, 0xd13c53da)</Identifier>
<Value></Value>
</Attribute>
<Attribute>
<Identifier>(0xf6b2e3fa, 0x7bd43926)</Identifier>
<Value>Motor Imagery</Value>
</Attribute>
<Attribute>
<Identifier>(0xf8034a49, 0x8b3f37cc)</Identifier>
<Value>INRIA</Value>
</Attribute>
</Attributes>
</OpenViBE-Scenario>
@@ -0,0 +1,23 @@
<OpenViBE-Classifier-Box Creator="Designer" CreatorVersion="2.0.0" FormatVersion="4">
<Strategy-Identifier class-id="(0xffffffff, 0xffffffff)">Native</Strategy-Identifier>
<Algorithm-Identifier class-id="(0x2ba17a3c, 0x1bd46d84)">Linear Discrimimant Analysis (LDA)</Algorithm-Identifier>
<Stimulations>
<Class-Stimulation class-id="0">OVTK_StimulationId_Label_01</Class-Stimulation>
<Class-Stimulation class-id="1">OVTK_StimulationId_Label_02</Class-Stimulation>
</Stimulations>
<OpenViBE-Classifier>
<LDA version="1">
<Classes>0 1 </Classes>
<Class-config-list>
<Class-config>
<Weights> 5.482270e+001 2.478968e+001</Weights>
<Bias>-66.7812</Bias>
</Class-config>
<Class-config>
<Weights> 5.275779e+001 2.744076e+001</Weights>
<Bias>-68.0094</Bias>
</Class-config>
</Class-config-list>
</LDA>
</OpenViBE-Classifier>
</OpenViBE-Classifier-Box>
@@ -0,0 +1,97 @@
function initialize(box)
dofile(box:get_config("${Path_Data}") .. "/plugins/stimulation/lua-stimulator-stim-codes.lua")
number_of_trials = box:get_setting(2)
first_class = _G[box:get_setting(3)]
second_class = _G[box:get_setting(4)]
baseline_duration = box:get_setting(5)
wait_for_beep_duration = box:get_setting(6)
wait_for_cue_duration = box:get_setting(7)
display_cue_duration = box:get_setting(8)
feedback_duration = box:get_setting(9)
end_of_trial_min_duration = box:get_setting(10)
end_of_trial_max_duration = box:get_setting(11)
-- initializes random seed
math.randomseed(os.time())
-- fill the sequence table with predifined order
sequence = {}
for i = 1, number_of_trials do
table.insert(sequence, 1, first_class)
table.insert(sequence, 1, second_class)
end
-- randomize the sequence
for i = 1, number_of_trials do
a = math.random(1, number_of_trials*2)
b = math.random(1, number_of_trials*2)
swap = sequence[a]
sequence[a] = sequence[b]
sequence[b] = swap
end
end
function process(box)
local t=0
-- manages baseline
box:send_stimulation(1, OVTK_StimulationId_ExperimentStart, t, 0)
t = t + 5
box:send_stimulation(1, OVTK_StimulationId_BaselineStart, t, 0)
box:send_stimulation(1, OVTK_StimulationId_Beep, t, 0)
t = t + baseline_duration
box:send_stimulation(1, OVTK_StimulationId_BaselineStop, t, 0)
box:send_stimulation(1, OVTK_StimulationId_Beep, t, 0)
t = t + 5
-- manages trials
for i = 1, number_of_trials*2 do
-- first display cross on screen
box:send_stimulation(1, OVTK_GDF_Start_Of_Trial, t, 0)
box:send_stimulation(1, OVTK_GDF_Cross_On_Screen, t, 0)
t = t + wait_for_beep_duration
-- warn the user the cue is going to appear
box:send_stimulation(1, OVTK_StimulationId_Beep, t, 0)
t = t + wait_for_cue_duration
-- display cue
box:send_stimulation(1, sequence[i], t, 0)
t = t + display_cue_duration
-- provide feedback
box:send_stimulation(1, OVTK_GDF_Feedback_Continuous, t, 0)
t = t + feedback_duration
-- ends trial
box:send_stimulation(1, OVTK_GDF_End_Of_Trial, t, 0)
t = t + math.random(end_of_trial_min_duration, end_of_trial_max_duration)
end
-- send end for completeness
box:send_stimulation(1, OVTK_GDF_End_Of_Session, t, 0)
t = t + 5
box:send_stimulation(1, OVTK_StimulationId_Train, t, 0)
t = t + 1
-- used to cause the acquisition scenario to stop
box:send_stimulation(1, OVTK_StimulationId_ExperimentStop, t, 0)
end
@@ -0,0 +1,3 @@
The scenario will record its signals here.