2 OpenViBE Designer 3.0.0 (0x001f9ac9, 0x8d7740bc) (0x330306dd, 0x74a95f98) Data ${Path_Data}/scenarios/signals/bci-motor-imagery.ov ${Path_Data}/scenarios/signals/bci-motor-imagery.ov (0x0011d622, 0x7d4c80a8) (0x79a9edeb, 0x245d83fc) Directory ${Player_ScenarioDirectory}/ ${Player_ScenarioDirectory} (0x005d306a, 0x9f30dd54) (0x330306dd, 0x74a95f98) Model Filename Classification-Riemann-Classic-Training-Model.xml Riemann-Training-Model.xml (0x00618c72, 0xe530a4c0) (0x330306dd, 0x74a95f98) Mean Mean-Riemann.csv Mean-Riemann.csv (0x0064fe21, 0x6acf20ec) (0x2c132d6e, 0x44ab0d97) Stimulation Class 1 OVTK_GDF_Left OVTK_GDF_Left (0x0017cd5f, 0xae3155d8) (0x2c132d6e, 0x44ab0d97) Stimulation Class 2 OVTK_GDF_Right OVTK_GDF_Right (0x00006ead, 0x71386450) (0x007deef9, 0x2f3e95c6) Log Level Information Information (0x00000d0c, 0x00002cdb) Confusion Matrix (0x1ab625da, 0x3b2502ce) (0x6f752dd0, 0x082a321e) Targets (0x6f752dd0, 0x082a321e) Classification results

(0x544a003e, 0x6dcba5f6) Confusion Matrix

(0x2cdb2f0b, 0x12f231ea) Percentages true true false (0x2cdb2f0b, 0x12f231ea) Sums false false false (0x2c132d6e, 0x44ab0d97) Class 1 OVTK_StimulationId_Label_00 $var{Stimulation Class 1} false (0x2c132d6e, 0x44ab0d97) Class 2 OVTK_StimulationId_Label_01 $var{Stimulation Class 2} false (0x1fa7a38f, 0x54edbe0b) 656 (0x207c9054, 0x3c841b63) 736 (0x4e7b798a, 0x183beafb) (0x05cf579a, 0x80d8b480) (0x61d11811, 0x71e65362) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x00de8e03) (0xc73e83ec, 0xf855c5bc) false (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 4 (0xcfad85b0, 0x7c6d841c) 2 (0x00001838, 0x00000242) Confusion Matrix (0x54f0796d, 0x3ede2cc0) (0x544a003e, 0x6dcba5f6) Matrix (0x3d3c7c7f, 0xef0e7129) Color gradient 0:2,36,58; 50:100,100,100; 100:83,17,20 0:2,36,58; 50:100,100,100; 100:83,17,20 false (0x007deef9, 0x2f3e95c6) Steps 100 100 false (0x2cdb2f0b, 0x12f231ea) Symetric min/max false false false (0x2cdb2f0b, 0x12f231ea) Real time min/max false false false (0x1fa7a38f, 0x54edbe0b) 720 (0x207c9054, 0x3c841b63) 736 (0x4e7b798a, 0x183beafb) (0x4ff49bdb, 0x9dcf6788) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x006eaeb9) (0xc73e83ec, 0xf855c5bc) false (0xce18836a, 0x9c0eb403) 4 (0xcfad85b0, 0x7c6d841c) 1 (0x0000241d, 0x0000786c) LWF (0x9a93af80, 0x6449c826) (0x5ba36127, 0x195feae1) Input Signal

(0x544a003e, 0x6dcba5f6) Output Covariance Matrix

(0x5261636b, 0x45535449) Estimator Covariance Ledoit and Wolf false (0x2cdb2f0b, 0x12f231ea) Center Data true true false (0xa88b3667, 0x0871638c) Log Level Information $var{Log Level} false (0x1fa7a38f, 0x54edbe0b) 528 (0x207c9054, 0x3c841b63) 880 (0x4e7b798a, 0x183beafb) (0xa227af77, 0xcd1af363) (0x666fffff, 0x666fffff) (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 3 (0xcfad85b0, 0x7c6d841c) 1 (0x00002816, 0x00002fc6) Matrix Classifier Processor (0x918f6952, 0xb22ddf0d) (0x6f752dd0, 0x082a321e) Expected Label (0x544a003e, 0x6dcba5f6) Input Matrix

(0x6f752dd0, 0x082a321e) Label

(0x544a003e, 0x6dcba5f6) Distance

(0x544a003e, 0x6dcba5f6) Probability

(0x330306dd, 0x74a95f98) Filename to load classifier model ${Player_ScenarioDirectory}/input-classifier.xml $var{Directory}/$var{Model Filename} false (0x330306dd, 0x74a95f98) Filename to save classifier model ${Player_ScenarioDirectory}/output-classifier.xml ${Player_ScenarioDirectory}/output-classifier.xml false (0x5261636b, 0x41646170) Adaptation No None false (0xa88b3667, 0x0871638c) Log Level Information Information false (0x1fa7a38f, 0x54edbe0b) 592 (0x207c9054, 0x3c841b63) 880 (0x4e7b798a, 0x183beafb) (0xb85fcd48, 0x1d5e5748) (0x666fffff, 0x666fffff) (0xc80ce8af, 0xf699f813) 3 (0xce18836a, 0x9c0eb403) 4 (0xcfad85b0, 0x7c6d841c) 2 (0x00006be7, 0x0000270b) Graz visualization (0x00dd290d, 0x5f142820) (0x6f752dd0, 0x082a321e) Stimulations (0x544a003e, 0x6dcba5f6) Amplitude

(0x544a003e, 0x6dcba5f6) Confusion Matrix

(0x2cdb2f0b, 0x12f231ea) Show instruction true true false (0x2cdb2f0b, 0x12f231ea) Show feedback false true false (0x2cdb2f0b, 0x12f231ea) Delay feedback false false false (0x2cdb2f0b, 0x12f231ea) Show accuracy false true false (0x007deef9, 0x2f3e95c6) Predictions to integrate 5 5 false (0x2cdb2f0b, 0x12f231ea) Positive feedback only false false false (0x1fa7a38f, 0x54edbe0b) 688 (0x207c9054, 0x3c841b63) 880 (0x4e7b798a, 0x183beafb) (0x602ceb3f, 0xd3bc74aa) (0xc73e83ec, 0xf855c5bc) false (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 6 (0xcfad85b0, 0x7c6d841c) 2 (0x11a6038b, 0x7157c283) Generic stream reader (0x6468099f, 0x0370095a)

(0x403488e7, 0x565d70b6) Output stream 1

(0x5ba36127, 0x195feae1) Output stream 2

(0x6f752dd0, 0x082a321e) Output stream 3

(0x330306dd, 0x74a95f98) Filename $var{Data} false (0x17ee7c08, 0x94c14893) (0x1fa7a38f, 0x54edbe0b) 224 (0x207c9054, 0x3c841b63) 880 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0xf37b8e7a, 0x1bc33e4e) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x005e1c11) (0x1396fde6, 0x1c649749) Identity (0x5dffe431, 0x35215c50) (0x6f752dd0, 0x082a321e) Input stream 1

(0x6f752dd0, 0x082a321e) Output stream 1

(0x17ee7c08, 0x94c14893) (0x1fa7a38f, 0x54edbe0b) 592 (0x207c9054, 0x3c841b63) 736 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0xa8ffe2a3, 0x27038f03) (0x527ad68d, 0x16d746a0) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x0017fc7a) (0xfba64161, 0x65304e21) (0x1396fde6, 0x1c64974a) Identity (0x5dffe431, 0x35215c50) (0x6f752dd0, 0x082a321e) Input stream 1

(0x6f752dd0, 0x082a321e) Output stream 1

(0x17ee7c08, 0x94c14893) (0x1fa7a38f, 0x54edbe0b) 272 (0x207c9054, 0x3c841b63) 736 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0xa8ffe2a3, 0x27038f03) (0x527ad68d, 0x16d746a0) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x0017fc7a) (0xfba64161, 0x65304e21) (0x2b88852d, 0x43d7a772) Reference Channel (0x444721ad, 0x78342cf5) (0x5ba36127, 0x195feae1) Input signal

(0x5ba36127, 0x195feae1) Output signal

(0x79a9edeb, 0x245d83fc) Channel Ref_Nose Nz false (0x666f25e9, 0x3e5738d6) Channel Matching Method Smart Smart false (0x1fa7a38f, 0x54edbe0b) 288 (0x207c9054, 0x3c841b63) 880 (0x4e7b798a, 0x183beafb) (0x7e39891d, 0x32cf5be7) (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 2 (0xcfad85b0, 0x7c6d841c) 1 (0x5045ebd9, 0x67325c0b) Player Controller (0x5f426dce, 0x08456e13) (0x6f752dd0, 0x082a321e) Stimulations (0x2c132d6e, 0x44ab0d97) Stimulation name OVTK_StimulationId_Label_00 OVTK_StimulationId_EndOfFile false (0xcc14d8d6, 0xf27ecb73) Action to perform Pause Pause false (0x1fa7a38f, 0x54edbe0b) 368 (0x207c9054, 0x3c841b63) 672 (0x4e7b798a, 0x183beafb) (0x568d148e, 0x650792b3) (0xce18836a, 0x9c0eb403) 2 (0xcfad85b0, 0x7c6d841c) 1 (0x5194b6cb, 0x7e001786) Channel Selector (0x361722e8, 0x311574e8) (0x5ba36127, 0x195feae1) Input signal

(0x5ba36127, 0x195feae1) Output signal

(0x79a9edeb, 0x245d83fc) Channel List - C3;C4;FC3;FC4;C5;C1;C2;C6;CP3;CP4 false (0x3bcf9e67, 0x0c23994d) Action Select Select false (0x666f25e9, 0x3e5738d6) Channel Matching Method Smart Smart false (0x1fa7a38f, 0x54edbe0b) 336 (0x207c9054, 0x3c841b63) 880 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0x277826e1, 0xa30a3bd0) (0x527ad68d, 0x16d746a0) (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 3 (0xcfad85b0, 0x7c6d841c) 1 (0x558c587f, 0x223f3b66) 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 8.000000 false (0x512a166f, 0x5c3ef83f) High cut frequency (Hz) 40 24.000000 false (0x512a166f, 0x5c3ef83f) Pass band ripple (dB) 0.5 0.500000 false (0x1fa7a38f, 0x54edbe0b) 400 (0x207c9054, 0x3c841b63) 880 (0x4e7b798a, 0x183beafb) (0x27a4ceec, 0x876d6384) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x001a79f8) (0x71322e63, 0x41ba161a) Time based epoching (0x00777fa0, 0x5dc3f560) (0x5ba36127, 0x195feae1) Input signal

(0x5ba36127, 0x195feae1) Epoched signal 1

(0x512a166f, 0x5c3ef83f) Epoch 1 duration (in sec) 1 1.000000 false (0x512a166f, 0x5c3ef83f) Epoch 1 intervals (in sec) 0.5 0.062500 false (0x17ee7c08, 0x94c14893) (0x1fa7a38f, 0x54edbe0b) 464 (0x207c9054, 0x3c841b63) 880 (0x4e7b798a, 0x183beafb) (0xc5ff41e9, 0xccc59a01) (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x00183f8d) (0x00000a31, 0x00007248) (0x1396fde6, 0x1c649749) 0 (0x00006be7, 0x0000270b) 0 (0x00001878, 0x0000796f) (0x11a6038b, 0x7157c283) 2 (0x1396fde6, 0x1c64974a) 0 (0x000022f3, 0x00007475) (0x1396fde6, 0x1c64974a) 0 (0x1396fde6, 0x1c649749) 0 (0x00002363, 0x00000391) (0x11a6038b, 0x7157c283) 1 (0x2b88852d, 0x43d7a772) 0 (0x0000426f, 0x00006d4b) (0x00000d0c, 0x00002cdb) 0 (0x00001838, 0x00000242) 0 (0x000043e3, 0x00001e1d) (0x1396fde6, 0x1c649749) 0 (0x00000d0c, 0x00002cdb) 0 (0x000051de, 0x00002a6d) (0x1396fde6, 0x1c64974a) 0 (0x5045ebd9, 0x67325c0b) 0 (0x000057f7, 0x00002085) (0x558c587f, 0x223f3b66) 0 (0x71322e63, 0x41ba161a) 0 (0x00006448, 0x000061dc) (0x00002816, 0x00002fc6) 1 (0x00006be7, 0x0000270b) 1 (0x00006847, 0x00005d1c) (0x00002816, 0x00002fc6) 0 (0x00000d0c, 0x00002cdb) 1 (0x00006cdb, 0x00004d41) (0x5194b6cb, 0x7e001786) 0 (0x558c587f, 0x223f3b66) 0 (0x00006fd9, 0x00007876) (0x71322e63, 0x41ba161a) 0 (0x0000241d, 0x0000786c) 0 (0x00007cff, 0x00003710) (0x0000241d, 0x0000786c) 0 (0x00002816, 0x00002fc6) 1 (0x1e23e99e, 0x6b3cf5e1) (0x2b88852d, 0x43d7a772) 0 (0x5194b6cb, 0x7e001786) 0 (0x000054d7, 0x00005ae3) Classifier processor (Need to run previous scenario) (0x473d9a43, 0x97fc0a97) 512 (0x7234b86b, 0x2b8651a5) 576 (0x000054d7, 0x00005ae6) Compute Covariance (0x473d9a43, 0x97fc0a97) 512 (0x7234b86b, 0x2b8651a5) 512 (0x11f491f3, 0x047d65a5) (0x3bcce5d2, 0x43f2d968) [{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"height":320,"identifier":"(0x000072ec, 0x00006065)","name":"","parentIdentifier":"(0xffffffff, 0xffffffff)","type":1,"width":695},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"identifier":"(0x00006a3f, 0x00006097)","index":0,"name":"Default tab","parentIdentifier":"(0x000072ec, 0x00006065)","type":2},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":2,"dividerPosition":336,"identifier":"(0x00004386, 0x00006f22)","index":0,"maxDividerPosition":676,"name":"Horizontal split","parentIdentifier":"(0x00006a3f, 0x00006097)","type":5},{"boxIdentifier":"(0x00006be7, 0x0000270b)","childCount":0,"identifier":"(0x00007839, 0x00001ae3)","index":0,"parentIdentifier":"(0x00004386, 0x00006f22)","type":3},{"boxIdentifier":"(0x00001838, 0x00000242)","childCount":0,"identifier":"(0x00003898, 0x0000309e)","index":1,"parentIdentifier":"(0x00004386, 0x00006f22)","type":3}] (0x079d1f09, 0x667c7871) (0x4c90d4ad, 0x7a2554ec) 320 (0x60bc58ab, 0x7a1b4d83) (0x790d75b8, 0x3bb90c33) Thibaut Monseigne (0x7a3a1558, 0xf12c63c2) (0x7b814cca, 0x271df6dd) 475 (0x84009d7c, 0x3c4e763b) (0x8c1fc55b, 0x7b433dc2) 1.0 (0x9f5c4075, 0x4a0d3666) Matrix Classification Testing Example (0xf36a1567, 0xd13c53da) (0xf6b2e3fa, 0x7bd43926) bci-examples (0xf8034a49, 0x8b3f37cc) Inria