[Eeglablist] FW: reading xltec-produced data
Makoto Miyakoshi
mmiyakoshi at ucsd.edu
Mon Apr 4 18:53:49 PDT 2016
Dear Maria,
I would try the following:
1. load that data to Matlab
2. open empty EEGLAB structure by 'eeg_emptyset'
3. write code to copy the items from one structure to the other
4. save the .set file
5. run the above routine for all the files as either a function or .m file
However this does require a bit of Matlab coding... should not be too
difficult though.
Makoto
On Sat, Feb 13, 2016 at 11:01 AM, Maria Veretennikova <veretenn at stt.msu.edu>
wrote:
> Hi all,
>
>
>
> We are starting to research EEG.
>
>
>
> We have sets of files produced by XLTEC, each set consists of files with
> extensions:
>
> .eeg, .erd, .snc, .etc, .stc, ent.
>
>
>
> For example a typical set is a directory with these files:
>
> Data.eeg
>
> Data.erd
>
> Data_001.erd
>
> Data.erd
>
> Data_001.etc
>
> Data.etc
>
> Data.snc
>
> Data.stc
>
> Data.ent
>
>
>
> We have been looking for softwares that can read these files.
>
>
>
> We tried EEGLAB, but we don’t know which of these files is the correct one
> to import into it. And we could not import any of the files.
>
>
>
> We also tried to read these files with
> https://github.com/gpiantoni/phypno/blob/83e01b096fdb96df3c3e4babf096ffc6b351a687/phypno/ioeeg/ktlx.py
>
> It claims that the erd files are the main data files, which looks right
> because the biggest file is Data_001.erd.
>
> However, the _*read*_erd function in ktlx.py applied to Data_001.erd
> returns only 32 mostly identical numbers (including some ‘nan’s), despite
> the file being 41MB in size. On the other hand, we know that 32 is also the
> number of channels.
>
>
>
> We know Persyst can read the data, but we can’t afford it, so we are
> looking for an alternative way / software to read the data.
>
>
>
> Any help / suggestions will be greatly appreciated.
>
>
>
> Thank you very much in advance.
>
>
>
> Maria Veretennikova
>
> Michigan State University, USA
>
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--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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