2 OpenViBE Designer 3.1.0 (0x00000b2d, 0x00006d61) Feature aggregator (0x00682417, 0x453635f9) (0x544a003e, 0x6dcba5f6) Input stream 1 (0x17341935, 0x152ff448) Feature vector stream (0x1fa7a38f, 0x54edbe0b) 352 (0x207c9054, 0x3c841b63) 320 (0x4e7b798a, 0x183beafb) (0xb5d15cc9, 0x6c8c28fb) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002bb807) (0xc80ce8af, 0xf699f813) 1 (0xcfad85b0, 0x7c6d841c) 1 (0xfba64161, 0x65304e21) (0x00000d41, 0x000013b7) Feature aggregator (0x00682417, 0x453635f9) (0x544a003e, 0x6dcba5f6) Input stream 1 (0x17341935, 0x152ff448) Feature vector stream (0x1fa7a38f, 0x54edbe0b) 352 (0x207c9054, 0x3c841b63) 544 (0x4e7b798a, 0x183beafb) (0xb5d15cc9, 0x6c8c28fb) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002b7d6e) (0xc80ce8af, 0xf699f813) 1 (0xcfad85b0, 0x7c6d841c) 1 (0xfba64161, 0x65304e21) (0x00001f83, 0x00004e32) Generic stream reader (0x6468099f, 0x0370095a) (0x403488e7, 0x565d70b6) Output stream 1 (0x5ba36127, 0x195feae1) Output stream 2 (0x6f752dd0, 0x082a321e) Output stream 3 (0x330306dd, 0x74a95f98) Filename C:/Users/Tobi_/Documents/ProjektarbeitBCI/OpenVibe/p300-speller-xDAWN/signals/p300-train-[2016.04.20-14.58.03].ov false (0x17ee7c08, 0x94c14893) (0x1fa7a38f, 0x54edbe0b) -160 (0x207c9054, 0x3c841b63) 400 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0xf37b8e7a, 0x1bc33e4e) (0x8d21ff41, 0xdf6afe7e) ${Player_ScenarioDirectory}/cfg/stream-reader.cfg (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x008e34c7) (0x00002c8b, 0x000001d5) Player Controller (0x5f426dce, 0x08456e13) (0x6f752dd0, 0x082a321e) Stimulations (0x2c132d6e, 0x44ab0d97) Stimulation name OVTK_StimulationId_Label_00 OVTK_StimulationId_TrainCompleted false (0xcc14d8d6, 0xf27ecb73) Action to perform Pause Stop false (0x1fa7a38f, 0x54edbe0b) 512 (0x207c9054, 0x3c841b63) 432 (0x4e7b798a, 0x183beafb) (0x568d148e, 0x650792b3) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x00301c7f) (0xc73e83ec, 0xf855c5bc) false (0xce18836a, 0x9c0eb403) 2 (0xcfad85b0, 0x7c6d841c) 1 (0x00002f94, 0x00000341) Non Target Selection (0x426163d1, 0x324237b0) (0x5ba36127, 0x195feae1) Input signal (0x6f752dd0, 0x082a321e) Input stimulations (0x5ba36127, 0x195feae1) Epoched signal (0x512a166f, 0x5c3ef83f) Epoch duration (in sec) 1 0.600000 false (0x512a166f, 0x5c3ef83f) Epoch offset (in sec) 0.5 0.000000 false (0x2c132d6e, 0x44ab0d97) Stimulation to epoch from OVTK_GDF_VEP OVTK_StimulationId_NonTarget false (0x1fa7a38f, 0x54edbe0b) 224 (0x207c9054, 0x3c841b63) 544 (0x4e7b798a, 0x183beafb) (0xa79941ae, 0x80708445) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002bbddf) (0x00003e14, 0x00000027) Signal Decimation (0x012f4bea, 0x3be37c66) (0x5ba36127, 0x195feae1) Input signal (0x5ba36127, 0x195feae1) Output signal (0x007deef9, 0x2f3e95c6) Decimation factor 8 4 false (0x1fa7a38f, 0x54edbe0b) 16 (0x207c9054, 0x3c841b63) 288 (0x4e7b798a, 0x183beafb) (0x5082af41, 0xd0fbf4cb) (0x8d21ff41, 0xdf6afe7e) ${Player_ScenarioDirectory}/cfg/p300-signal-decimation.cfg (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002c5bfc) (0x0000486f, 0x000075f4) Temporal filter (0xb4f9d042, 0x9d79f2e5) (0x5ba36127, 0x195feae1) Input signal (0x5ba36127, 0x195feae1) Filtered signal (0x2f2c606c, 0x8512ed68) Filter method Butterworth Butterworth false (0xfa20178e, 0x4cba62e9) Filter type Low pass Band pass false (0x007deef9, 0x2f3e95c6) Filter order 4 4 false (0x512a166f, 0x5c3ef83f) Low cut frequency (Hz) 29 1.000000 false (0x512a166f, 0x5c3ef83f) High cut frequency (Hz) 40 20.000000 false (0x512a166f, 0x5c3ef83f) Pass band ripple (dB) 0.5 0.500000 false (0x1fa7a38f, 0x54edbe0b) -32 (0x207c9054, 0x3c841b63) 288 (0x4e7b798a, 0x183beafb) (0x27a4ceec, 0x876d6384) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002b9aae) (0x000063a5, 0x0000197c) Target Selection (0x426163d1, 0x324237b0) (0x5ba36127, 0x195feae1) Input signal (0x6f752dd0, 0x082a321e) Input stimulations (0x5ba36127, 0x195feae1) Epoched signal (0x512a166f, 0x5c3ef83f) Epoch duration (in sec) 1 0.600000 false (0x512a166f, 0x5c3ef83f) Epoch offset (in sec) 0.5 0.000000 false (0x2c132d6e, 0x44ab0d97) Stimulation to epoch from OVTK_GDF_VEP OVTK_StimulationId_Target false (0x1fa7a38f, 0x54edbe0b) 224 (0x207c9054, 0x3c841b63) 320 (0x4e7b798a, 0x183beafb) (0xa79941ae, 0x80708445) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002b4e91) (0x000078d0, 0x000029bc) Epoch average (0x21283d9f, 0xe76ff640) (0x5ba36127, 0x195feae1) Input epochs (0x5ba36127, 0x195feae1) Averaged epochs (0x6530bdb1, 0xd057bbfe) Averaging type Epoch block average Epoch block average false (0x007deef9, 0x2f3e95c6) Epoch count 4 1 false (0x1fa7a38f, 0x54edbe0b) 288 (0x207c9054, 0x3c841b63) 320 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0xb73cee83, 0xf7215d60) (0x527ad68d, 0x16d746a0) (0x8d21ff41, 0xdf6afe7e) ${Player_ScenarioDirectory}/cfg/p300-epoch-average.cfg (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002b5470) (0x000078f9, 0x000063eb) xDAWN Spatial Filter (0xdd332c6c, 0x195b4fd4) (0x5ba36127, 0x195feae1) Input Signal (0x5ba36127, 0x195feae1) Output Signal (0x79a9edeb, 0x245d83fc) Spatial Filter Coefficients 1;0;0;0;0;1;0;0;0;0;1;0;0;0;0;1 9.970221e-001 -3.729500e-002 -1.177390e-002 2.814447e-002 -3.772446e-003 3.371324e-002 -5.480030e-003 8.893039e-003 -1.565213e-002 -9.956694e-003 -2.347757e-002 -2.312669e-003 -1.847227e-002 -7.550644e-004 -8.423513e-003 3.243223e-002 2.079848e-002 5.079737e-001 -2.835127e-002 8.259231e-002 -3.621803e-001 -2.004259e-001 -2.432480e-001 -1.861558e-001 -3.798139e-001 9.614762e-002 3.407766e-001 -2.158597e-001 3.720552e-001 7.500469e-002 -8.628774e-002 -3.182367e-002 5.923482e-002 4.124707e-001 2.083913e-001 -2.629501e-001 2.023081e-001 -2.658446e-001 4.022738e-001 -1.785569e-001 4.450742e-001 3.549239e-001 1.550204e-002 3.750389e-002 3.114249e-002 9.273764e-002 -7.093797e-002 -2.610929e-001 false (0x007deef9, 0x2f3e95c6) Number of Output Channels 4 3 false (0x007deef9, 0x2f3e95c6) Number of Input Channels 4 16 false (0x330306dd, 0x74a95f98) Filter matrix file false (0x1fa7a38f, 0x54edbe0b) 80 (0x207c9054, 0x3c841b63) 288 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0x81db9bf9, 0xf1cf4ed7) (0x527ad68d, 0x16d746a0) (0x8d21ff41, 0xdf6afe7e) ${Player_ScenarioDirectory}/cfg/p300-spatial-filter.cfg (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002b601f) (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 3 (0xcfad85b0, 0x7c6d841c) 1 (0x00007b56, 0x000033f9) Epoch average (0x21283d9f, 0xe76ff640) (0x5ba36127, 0x195feae1) Input epochs (0x5ba36127, 0x195feae1) Averaged epochs (0x6530bdb1, 0xd057bbfe) Averaging type Epoch block average Epoch block average false (0x007deef9, 0x2f3e95c6) Epoch count 4 1 false (0x1fa7a38f, 0x54edbe0b) 288 (0x207c9054, 0x3c841b63) 544 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0xb73cee83, 0xf7215d60) (0x527ad68d, 0x16d746a0) (0x8d21ff41, 0xdf6afe7e) ${Player_ScenarioDirectory}/cfg/p300-epoch-average.cfg (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x002c2168) (0x0a5a6a4a, 0x1d92a778) Classifier trainer (0xf3dae8a8, 0x3b444154) (0x6f752dd0, 0x082a321e) Stimulations (0x17341935, 0x152ff448) Features for class 1 (0x17341935, 0x152ff448) Features for class 2 (0x6f752dd0, 0x082a321e) Train-completed Flag (0x2c132d6e, 0x44ab0d97) Train trigger OVTK_StimulationId_Train OVTK_StimulationId_ExperimentStop false (0x330306dd, 0x74a95f98) Filename to save configuration to ${Path_UserData}/my-classifier.xml ${Player_ScenarioDirectory}/cfg/p300-classifier.cfg false (0xbe9eba5c, 0xa8415d37) Multiclass strategy to apply Native Native false (0x2c132d6e, 0x44ab0d97) Class 1 label OVTK_StimulationId_Label_01 OVTK_StimulationId_Target false (0x2c132d6e, 0x44ab0d97) Class 2 label OVTK_StimulationId_Label_02 OVTK_StimulationId_NonTarget false (0xd765a736, 0xed708c65) Algorithm to use Linear Discrimimant Analysis (LDA) Linear Discrimimant Analysis (LDA) false (0x2cdb2f0b, 0x12f231ea) Use shrinkage false false false (0x512a166f, 0x5c3ef83f) Shrinkage coefficient (-1 == auto) -1.000000 -1.000000 false (0x2cdb2f0b, 0x12f231ea) Shrinkage: Force diagonal cov (DDA) false false false (0x007deef9, 0x2f3e95c6) Number of partitions for k-fold cross-validation test 10 5 false (0x2cdb2f0b, 0x12f231ea) Balance classes false false false (0x1fa7a38f, 0x54edbe0b) 448 (0x207c9054, 0x3c841b63) 432 (0x4e7b798a, 0x183beafb) (0x9de21779, 0x37776c89) (0xc73e83ec, 0xf855c5bc) false (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 6 (0xcfad85b0, 0x7c6d841c) 3 (0xfba64161, 0x65304e21) (0x00000004, 0x00007d3a) (0x000078f9, 0x000063eb) 0 (0x000063a5, 0x0000197c) 0 (0x00000a32, 0x00005cae) (0x0000486f, 0x000075f4) 0 (0x00003e14, 0x00000027) 0 (0x00000aca, 0x000037d3) (0x00003e14, 0x00000027) 0 (0x000078f9, 0x000063eb) 0 (0x00001717, 0x00003cf9) (0x000078d0, 0x000029bc) 0 (0x00000b2d, 0x00006d61) 0 (0x00001770, 0x00000ded) (0x00001f83, 0x00004e32) 2 (0x000063a5, 0x0000197c) 1 (0x0000227f, 0x00003a6f) (0x000078f9, 0x000063eb) 0 (0x00002f94, 0x00000341) 0 (0x00002599, 0x0000329b) (0x000063a5, 0x0000197c) 0 (0x000078d0, 0x000029bc) 0 (0x00004098, 0x00007e81) (0x00002f94, 0x00000341) 0 (0x00007b56, 0x000033f9) 0 (0x00004674, 0x000061af) (0x00007b56, 0x000033f9) 0 (0x00000d41, 0x000013b7) 0 (0x00005d56, 0x000065e9) (0x00001f83, 0x00004e32) 1 (0x0000486f, 0x000075f4) 0 (0x00006821, 0x00000c75) (0x00001f83, 0x00004e32) 2 (0x00002f94, 0x00000341) 1 (0x175e412c, 0x0692f4ee) (0x00000d41, 0x000013b7) 0 (0x0a5a6a4a, 0x1d92a778) 2 (0x5a67b7d8, 0x1cf07f9a) (0x00001f83, 0x00004e32) 2 (0x0a5a6a4a, 0x1d92a778) 0 (0x616495af, 0x5c020b32) (0x0a5a6a4a, 0x1d92a778) 0 (0x00002c8b, 0x000001d5) 0 (0x63fa63da, 0x0e447c5b) (0x00000b2d, 0x00006d61) 0 (0x0a5a6a4a, 0x1d92a778) 1 (0x00004785, 0x00007f9c) You can browse each box' documentation by selecting the box and pressing F1 (0x473d9a43, 0x97fc0a97) 432 (0x7234b86b, 0x2b8651a5) -240 (0x000047f3, 0x00004eaf) The preprocessing of the signal is performed here... Note: be sure that the sampling rate and sample count per buffer you use in the acquisition server are compatible with the actual signal decimation factor (0x473d9a43, 0x97fc0a97) 48 (0x7234b86b, 0x2b8651a5) 0 (0x00005277, 0x00007fbe) <big>Overview</big> This scenario should be used to train the LDA classifier. Just configure the Generic Stream Reader box to point to the last file you recorded with scenario 1-acquisition and fast forward this scenario. At the end of the training, you will have an estimation of the classifier performance printed in the console. If this performance is lower than 70%, just run a new 4-online session to have better results. Note: in order to run this scenario, the spatial filter should have been trained using 2-train-xDAWN ! (0x473d9a43, 0x97fc0a97) 848 (0x7234b86b, 0x2b8651a5) 96 (0x0000775c, 0x000078ff) (0x3bcce5d2, 0x43f2d968) [] (0x790d75b8, 0x3bb90c33) Yann Renard (0x8c1fc55b, 0x7b433dc2) (0x9f5c4075, 0x4a0d3666) LDA Classifier Trainer (0xf36a1567, 0xd13c53da) http://openvibe.inria.fr/p300-speller-xdawn/ (0xf6b2e3fa, 0x7bd43926) xDAWN P300 Speller (0xf8034a49, 0x8b3f37cc) INRIA