OpenViBE 1.3.0 (0x00000124, 0x0000214f) Python scripting (0x5dc4f669, 0xd3fd4d64)

(0x6f752dd0, 0x082a321e) EndStimulation

(0x007deef9, 0x2f3e95c6) Clock frequency (Hz) 64 64 false (0xb0d0db45, 0x49cbc34a) Script E:/Tilen/FAX/2. stopnja/UI/projekt-bci/free-will/scripts/python-learning.py false (0x330306dd, 0x74a95f98) InputCSVSignal E:/Tilen/FAX/2. stopnja/UI/projekt-bci/free-will/signals/record-sig-[2017.05.15-23.11.00].csv false (0x330306dd, 0x74a95f98) InputCSVStimulations E:/Tilen/FAX/2. stopnja/UI/projekt-bci/free-will/signals/record-stim-[2017.05.15-23.11.00].csv false (0x330306dd, 0x74a95f98) SaveFile false (0x007deef9, 0x2f3e95c6) WindowSize (ms) 100 100 false (0x007deef9, 0x2f3e95c6) NumOfPrevWindows 5 4 false (0x007deef9, 0x2f3e95c6) NumOfWindowsBefore 0 4 false (0x007deef9, 0x2f3e95c6) NumOfWindowsAfter 0 0 false (0x007deef9, 0x2f3e95c6) K-folds 4 10 false (0x17ee7c08, 0x94c14893) (0x1fa7a38f, 0x54edbe0b) 48.000000 (0x1fa963f5, 0x1a638cd4) 34 (0x207c9054, 0x3c841b63) 320.000000 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0x2a651510, 0xb4fad0d4) (0x527ad68d, 0x16d746a0) (0x61d11811, 0x71e65362) (0xad100179, 0xa3c984ab) 102 (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x00055fbe) (0xc73e83ec, 0xf855c5bc) false (0xce18836a, 0x9c0eb403) 2 (0xf191c1c8, 0xa0123976) (0xfba64161, 0x65304e21) (0x00000d51, 0x000039af) CSV File Reader (0x641d0717, 0x02884107)

(0x6f752dd0, 0x082a321e) Output stream

(0x330306dd, 0x74a95f98) Filename E:/Tilen/FAX/2. stopnja/UI/projekt-bci/free-will/signals/record-stim-[2017.05.15-23.11.00].csv false (0x79a9edeb, 0x245d83fc) Column separator ; ; false (0x2cdb2f0b, 0x12f231ea) Don't use the file time false false false (0x007deef9, 0x2f3e95c6) Unused parameter 32 0 false (0x1fa7a38f, 0x54edbe0b) -128.000000 (0x1fa963f5, 0x1a638cd4) 45 (0x207c9054, 0x3c841b63) 496.000000 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0x3bf57676, 0xad3aaefa) (0xad100179, 0xa3c984ab) 97 (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x0001d5c4) (0xc73e83ec, 0xf855c5bc) true (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 4 (0x000055e6, 0x00000489) Player Controller (0x5f426dce, 0x08456e13) (0x6f752dd0, 0x082a321e) Stimulations (0x2c132d6e, 0x44ab0d97) Stimulation name OVTK_StimulationId_Label_00 OVTK_StimulationId_TrialStop false (0xcc14d8d6, 0xf27ecb73) Action to perform Pause Stop false (0x1fa7a38f, 0x54edbe0b) 128.000000 (0x1fa963f5, 0x1a638cd4) 23 (0x207c9054, 0x3c841b63) 320.000000 (0x4e7b798a, 0x183beafb) (0x568d148e, 0x650792b3) (0xad100179, 0xa3c984ab) 105 (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x00284de3) (0xc73e83ec, 0xf855c5bc) false (0xce18836a, 0x9c0eb403) 2 (0xcfad85b0, 0x7c6d841c) 1 (0x00006c4c, 0x000002b3) CSV File Reader (0x641d0717, 0x02884107)

(0x5ba36127, 0x195feae1) Output stream

(0x330306dd, 0x74a95f98) Filename E:/Tilen/FAX/2. stopnja/UI/projekt-bci/free-will/signals/record-sig-[2017.05.15-23.11.00].csv false (0x79a9edeb, 0x245d83fc) Column separator ; ; false (0x2cdb2f0b, 0x12f231ea) Don't use the file time false false false (0x007deef9, 0x2f3e95c6) Samples per buffer 32 32 false (0x1fa7a38f, 0x54edbe0b) -128.000000 (0x1fa963f5, 0x1a638cd4) 45 (0x207c9054, 0x3c841b63) 384.000000 (0x30a4e5c9, 0x83502953) (0x4e7b798a, 0x183beafb) (0x3bf57676, 0xad3aaefa) (0xad100179, 0xa3c984ab) 97 (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x0007fed6) (0xc73e83ec, 0xf855c5bc) true (0xc80ce8af, 0xf699f813) 1 (0xce18836a, 0x9c0eb403) 4 (0x00006ed7, 0x000003cf) Signal display (0x0055be5f, 0x087bdd12) (0x5ba36127, 0x195feae1) Data (0x6f752dd0, 0x082a321e) Stimulations (0x6ab26b81, 0x0f8c02f3) Channel Units (0x5de046a6, 0x086340aa) Display Mode Scan Scan false (0x33a30739, 0x00d5299b) Auto vertical scale Per channel Per channel false (0x512a166f, 0x5c3ef83f) Scale refresh interval (secs) 5 5 false (0x512a166f, 0x5c3ef83f) Vertical Scale 100 100 false (0x512a166f, 0x5c3ef83f) Vertical Offset 0 0 false (0x512a166f, 0x5c3ef83f) Time Scale 10 10 false (0x2cdb2f0b, 0x12f231ea) Bottom ruler true true false (0x2cdb2f0b, 0x12f231ea) Left ruler false false false (0x2cdb2f0b, 0x12f231ea) Multiview false false false (0x1fa7a38f, 0x54edbe0b) -64.000000 (0x1fa963f5, 0x1a638cd4) 45 (0x207c9054, 0x3c841b63) 432.000000 (0x4e7b798a, 0x183beafb) (0x92c056a7, 0x2dc71aff) (0x527ad68d, 0x16d746a0) (0xad100179, 0xa3c984ab) 87 (0xc46b3d00, 0x3e0454e1) (0x00000000, 0x00024b35) (0xc73e83ec, 0xf855c5bc) true (0xce18836a, 0x9c0eb403) 9 (0xcfad85b0, 0x7c6d841c) 3 (0x00000e16, 0x00006760) (0x00006c4c, 0x000002b3) 0 (0x00006ed7, 0x000003cf) 0 (0x1b32c44c, 0x1905e0e9) -99 (0x358ae8b5, 0x0f8bacd1) 384 (0x3f0a3b27, 0x570913d2) -91 (0x6267b5c5, 0x676e3e42) 417 (0x000011ac, 0x000063f9) (0x00000d51, 0x000039af) 0 (0x00006ed7, 0x000003cf) 1 (0x1b32c44c, 0x1905e0e9) -99 (0x358ae8b5, 0x0f8bacd1) 496 (0x3f0a3b27, 0x570913d2) -91 (0x6267b5c5, 0x676e3e42) 432 (0x00004464, 0x0000753e) (0x00000124, 0x0000214f) 0 (0x000055e6, 0x00000489) 0 (0x1b32c44c, 0x1905e0e9) 71 (0x358ae8b5, 0x0f8bacd1) 320 (0x3f0a3b27, 0x570913d2) 112 (0x6267b5c5, 0x676e3e42) 320 (0x6160f9b8, 0x37b083c2) <u><b><big>Overview</big></b></u> This scenario is used to train data for the "free will experiment". See the python scripts for a deeper look into the code. Main Python script settings are: <b>Script</b> - python script for learning and other ML methods <b>InputCSVSignal</b> - captured EEG signal <b>InputCSVStimulation</b> - captured keyboard times <b>SaveFile</b> - if you want to save learning hypotesis into a (python pickle) file (e.g. ./python-out-[$core{date}-$core{time}].pkl) <b>WindowSize (ms)</b> - size of windows/chunks in milliseconds <b>NumberOfPrevWindows</b> - number of windows, to be marked as class 1 (just before the button was pressed) <b>NumberOfWindowsBefore</b> - number of windows, to be marked as class 0 (before those marked as 1) <b>NumberOfWindowsAfter</b> - number of windows, to be marked as class 0 (after those marked as 1) <b>K-folds</b> - K-fold cross validation (0x473d9a43, 0x97fc0a97) -94.000000 (0x7234b86b, 0x2b8651a5) -64.000000 (0x00003e01, 0x000020d2) 3 (0xffffffff, 0xffffffff) (0x00006ed7, 0x000003cf) 0 (0x0c60317a, 0x7480157f) Default window 1 (0xffffffff, 0xffffffff) (0xffffffff, 0xffffffff) 1 (0x4c90d4ad, 0x7a2554ec) 1 (0x7b814cca, 0x271df6dd) 1 (0x4eff2d5e, 0x057e5a93) Default tab 2 (0x0c60317a, 0x7480157f) 0 (0xffffffff, 0xffffffff) 1 (0x00b5ee2a, 0x40e0a42c) Empty 0 (0x4eff2d5e, 0x057e5a93) 0 (0xffffffff, 0xffffffff) 0 (0x790d75b8, 0x3bb90c33) Yann Renard / Fabien Lotte (0x8c1fc55b, 0x7b433dc2) (0x9f5c4075, 0x4a0d3666) Classifier Training (0xf36a1567, 0xd13c53da) (0xf6b2e3fa, 0x7bd43926) Motor Imagery (0xf8034a49, 0x8b3f37cc) INRIA