OpenViBE forum

Thomas, Ignore the title of this topic, I am concerned about the 2nd question I asked, how to use a single branch to use for both stim types. You did not reply to my last error report, and I went in other directions and did not follow up. I think if we can get this working it might help solve the ot...

Thomas, We are still trying to make our work-around work (described in the large paragraph in my initial message of this topic), but are hampered by our ability to see what is going on in some of the boxes. In particular we cannot figure out how to display or save to a file the stimulus or feature v...

last file, seems to be limited to 3 at a time?

scenarios mentioned above

Thomas or whoever is able to respond to this topic: We are being held up implementing our neurofeedback scenario as it requires a custom Box. After initial filtering and Feature-Aggregating we need to computer a statistical measure and use it to threshold the most significant features to send on to ...

Hi Thomas, I did not see your response until tonight. Is there any way to be notified by email when there are new replies to a subject? I will have to go back and try the Time-based epoching as you suggest here and see what happens. As I recall it failed for some reason. More important now is our in...

This is the scenario we are using. The proposed Box would fit after each of the two Feature Aggregator Boxes and the SVM Classifier Box.
smok_clas_svm_train.xml attached.
-Jeff

Hello, We have been trying to create a custom box that does these things: 1. transforms the EEG data to a type of Z-score (requires all of the data in order to calculate means and stddevs over all trials) 2. selects the top P percent of the data (P entered by the user) that matches the top P percent...

had problem with this attachment, trying again
-Jeff

Hi, We have a classification scenario with two classes. we have trained it using SVM, which created the SVM model in a file. We now want to use that model during our neurofeedback sessions, and on pre-recorded data. we tried to follow the motor-imagery example, but are stuck. Here is what we have fo...

Hi Thomas,

This info is helpful, thank you. I will look into your suggestions about selecting time windows, but I suspect it may be difficult to use as I need to select "random" time frames (samples) based on statistical significance, not time sub-epochs.

-Jeff

Thomas, I have been using svm.SVC which allows these kernel choices: {‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’, ‘precomputed’} or callable, default=’rbf’. It seems odd to me that this more general implementation was not implemented already, as it includes a linear kernel as an option and gives you a lot m...

Thomas, I tried it and after it read the 3 minute file in I got this: [ INF ] Initialization took 1958 ms [ ERROR ] At time 183.984 sec <Box algorithm::(0x00006520, 0x00005569) aka SVM classifier> {Error description} : {Received fewer examples (0) than specified partition count (10)}, {Error type} :...

Hi Thomas,

I have been out of town for a few days, so just logged on and saw your reply. I will look ed the link, but this problem has temporarily been solved by exporting GDF files from Matlab.

Thanks,
-Jeff

I would like to use the sklearn classifier box, specifically with the Support Vector Machine (SVM) option. The advantage of this I had hoped to avail myself of is the ability to optimize the SVM outside of OpenViBE using the sklearn Python SVM. Looking at the parameters available in the configuratio...