[Eeglablist] [EGI] Importing segmented NetStation files

[Tarik S Bel-Bahar]

Hello Laurie,

Yes that should be easy to do from the GUI, where I believe there is an
option under File > Import Data> From Multiple seg. EGI .RAW files
This is an important function and should work well. However, I usually use
continuous import as the main import from Netstation.

Alternatively, or if you have not tried the following:

...Export the files as segmented (with trials) .raw files, and eeglab
should detect them as epochs.
 if it is read as continuous by eeglab, just re-epoch on the segment marker
that should come in via NS (you might have to tweak the settings on NS
export)

...you may need to first resave the NS files as continuous files, with
appropriate markers, and then do the step mentioned above.

...check out the mmf import tool from EGI support, I think it's also
available as an eeglab plugin. It may already be implemented in eeglab, or
may need to be imported or used separately in matlab.

...alternatively, if you're matlab saavy and using a recent NS, you could
access the signal bin file in the NS file package of the segmented NS data
you're working with, and build up an eeglab file that way.

..Note that you should force a specific set of channel labels once import
is done to make sure the correct locations are applied to the trodes.


On Mon, Feb 6, 2017 at 3:22 PM, Laurie Bayet <lauriebayet at gmail.com> wrote:

> Hi,
>
> I'm trying to import a large amount of NetStation data files that have
> already been segmented in NetStation (using the "Waveform tools" GUI).
>
> The raw continuous files still exist, so technically those could still be
> exported as continuous simple binary files with segmentation markup.
>
> However, being able to directly import the already segmented files would
> be quite the time saver and would ensure consistency with other existing
> analyses that have been using these files in Netstation.
>
> Is there any way to import segmented NetStation files to EEGLAB/Matlab?
>
> Thank you.
> All the best,
> Laurie
>
>
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