Hello all,
I' m trying to run the motor-imagery-bci-1-acquisition.xml scenario and I want make the imagination of left/right hand movement without of eeg device but with prerecorded data. Any idea how can I do this? Is there any suitable data-set for this?
Thanks.
motor-imagery-bci-1-acquisition.xml
Re: motor-imagery-bci-1-acquisition.xml
HI,
The acquisition scenario is used for..... acquisition^^, you train your classifier with the next scenario : train. An example eeg file is already set in this scenario
Thibaut
The acquisition scenario is used for..... acquisition^^, you train your classifier with the next scenario : train. An example eeg file is already set in this scenario
Thibaut
Re: motor-imagery-bci-1-acquisition.xml
I have trained the classifier successfully. The .cfg file has been generated.
Also when the classifier is trained, I want to replay some recorded test data and depending of the result, print a left or right message in Unity 3d.
How can I achieve this? Is there some instructions for something like that or can someone give me these instructions?
I would appreciate any help!
Also when the classifier is trained, I want to replay some recorded test data and depending of the result, print a left or right message in Unity 3d.
How can I achieve this? Is there some instructions for something like that or can someone give me these instructions?
I would appreciate any help!
Re: motor-imagery-bci-1-acquisition.xml
HI,
I have down some hello world game with Unity
See : viewtopic.php?p=16495#p16495
viewtopic.php?p=16511#p16511
Thibaut
I have down some hello world game with Unity
See : viewtopic.php?p=16495#p16495
viewtopic.php?p=16511#p16511
Thibaut
Re: motor-imagery-bci-1-acquisition.xml
Hello,
When i run this scenario at the end i take Accuracy = 0.0?
Why is this happening and why generated confusion matrix in the acquisition phase?
RESULTS:
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Finished with partition 6 / 7 (performance : 26.5372173)
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Finished with partition 7 / 7 (performance : 31.0679613)
[ INF ] At time 430.594 sec <Box algorithm: : 0x02e67945, Ox5ea8d309) aka Classifier trainer> Cross-validation test accuracy is 31.573362% (sigma = 6.9795798)
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Cls vs cls 1 2
[ INF ] At time 430.594 sec <Box algorithm: : 0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 1: 42.1 57.9, 1080 examples
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 2: 79.0 21.0 %, 1080 examples
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer Training set accuracy is 48.379630$ (optimistic)
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Cls vs cls 1 2
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 1: 51.4 48.6 %, 1080 examples
| INF | At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 2: 54.6 45.4 $, 1080 examples
! INF ] At time 0.000 sec <Box algorithm:: (0x00000de5, 0x0000613d) aka Graz Motor Imagery BCI Stimulator> Lua script terminated
[ INF ] At time 431.273 sec <Box algorithm:: (0x42570b5c, OxObba079c) aka Graz visualization> Confusion Matrix :
000 000
000 000
Accuracy = 0.0
When i run this scenario at the end i take Accuracy = 0.0?
Why is this happening and why generated confusion matrix in the acquisition phase?
RESULTS:
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Finished with partition 6 / 7 (performance : 26.5372173)
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Finished with partition 7 / 7 (performance : 31.0679613)
[ INF ] At time 430.594 sec <Box algorithm: : 0x02e67945, Ox5ea8d309) aka Classifier trainer> Cross-validation test accuracy is 31.573362% (sigma = 6.9795798)
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Cls vs cls 1 2
[ INF ] At time 430.594 sec <Box algorithm: : 0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 1: 42.1 57.9, 1080 examples
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 2: 79.0 21.0 %, 1080 examples
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer Training set accuracy is 48.379630$ (optimistic)
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Cls vs cls 1 2
[ INF ] At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 1: 51.4 48.6 %, 1080 examples
| INF | At time 430.594 sec <Box algorithm:: (0x02e67945, Ox5ea8d309) aka Classifier trainer> Target 2: 54.6 45.4 $, 1080 examples
! INF ] At time 0.000 sec <Box algorithm:: (0x00000de5, 0x0000613d) aka Graz Motor Imagery BCI Stimulator> Lua script terminated
[ INF ] At time 431.273 sec <Box algorithm:: (0x42570b5c, OxObba079c) aka Graz visualization> Confusion Matrix :
000 000
000 000
Accuracy = 0.0
Re: motor-imagery-bci-1-acquisition.xml
Hi,
It's normal, Graz visualization Confusion matrix works with classifier processor not trainer. Launch all scenario of the folder to see the protocol.
Thibaut
It's normal, Graz visualization Confusion matrix works with classifier processor not trainer. Launch all scenario of the folder to see the protocol.
Thibaut
Re: motor-imagery-bci-1-acquisition.xml
How can I add a 3rd class of Resting state? I want to train my classifier recognizing left-right hand movement and resting state if the user don't trying to imagine anything.
Re: motor-imagery-bci-1-acquisition.xml
Hi,
Right Click on box classifier trainer, inputs->new. I have never test the behavior on 3 class for this box, so I can help you so much.^^
Thibaut
Right Click on box classifier trainer, inputs->new. I have never test the behavior on 3 class for this box, so I can help you so much.^^
Thibaut