There is no training phase, predefined coefficients are used.

In the Surface Laplacian Box -> Spatial Filter coefficients there is this (4; 0; -1; 0; -1; -1; 0; 0; -1; 0; 0; 4; 0; -1; 0; 0; -1; -1; 0; -1)

Widget. Is there any place I can get the coefficients without running the Matlab (I do not have the DSP Toolbox....).

I tried to add a 16-24 Hz bandpass filter recently, so if you need an example you can look at the link below that shows the changes I made to the widget. Note that you need access to Matlab or some ot

Packet loss is only bad if the 50 Hz noise is really high, and the srate is 125 Hz. Then the notch filter goes crazy if one packet is lost, and you see a burst because the on-line filter coefficients

In terms of removing the DC offset, all you have to be concerned with is removing components below say .5 Hz. So that can be achieved for example with a Butterworth bandpass from .5 to 45 Hz, or a hig

# 2) Calculate the coefficients, store in variables

@Paski Thanks for the link. I guess I'm trying to better understand the logic for determining the coefficients that they use. That way, I can understand how to change their values to try to improve my

Hi Hackr, see this link. There you will find the coefficients. https://www.bci2000.org/mediawiki/index.php/User_Tutorial:Configuring_Online_Feedback

In the OpenViBE classification examples, they have this spatial filter labeled LaPlacian Surface. It takes 2 coefficients for every 1 input channel as parameters. I am wondering how one goes about det

If you are in the U.S., you want to have a notch filter at 60 Hz, to cancel out mains noise. There are tutorials on the web on how to construct the filter coefficients. And also some here,

For peak detection around 60 Hz, how to change the filter coefficients? 

3. Filter coefficients can be changed.

Sorry, that was just copy and pasted from the original code. I didn't finish editing the comments. Those coefficients are for the 125Hz sampling rate. I did clone the distribution from github, but I f

@djfletch42 the ganglion was originally 256Hz, then BLE said nope, and it's 200Hz. Thanks so much for taking a crack at the filter coefficients, I will add this to the patch.

In case it's helpful, I did go through and calculate the filter coefficients for the 125Hz sampling rate. This code will incorporate the new filter coefficients into DataProcessing.pde. I used Matlab

no significant effects . Bivariate correlation coefficients were calculated to assess the relationship between electrode pairs during the simultaneous in vivo recordings, indicating a significant pos

I was just wondering why the Butterworth filter was selected for all filtering in the EEG Processing.  I imagine the maximally flat frequency response is the enviable characteristic, but wouldn't a Be

The filters and FFT in OpenBCI_GUI are also great examples. Second link above shows how the filter coefficients can be modified for your application.

will need to be much longer (ie, have many more coefficients) that an IIR filter with the same roll-off.