[Eeglablist] Compatability and artifact identification issues

Thu Dec 3 01:20:46 PST 2009

Hello all,

Thanks to all for the help!

ICA probably doesn't do it that well for me, for I indeed have several
widely separated bipolar EMG's electrodes (and a separate ECG). I
think that for it to work, you need to have some kind of spatial
consistency as is the case in EEG.

The way I handled it now is by tinkering with the fmrib_fastr toolbox
(by Niazy, 2006) used for correcting the BCG artifact in combined
EEG-fMRI, to make it also work on normal ECG in EMG.

I added some extra interations to the QRS detection algorithm (and the
samplerate it operates on) so that ECG events are better aligned. When
the events are placed, in the ECG correction algorithm I changed the
window settings so that it better matches the ECG itself (the artifact
is not misplaced by 0.21 sec (Allen, 1998) like the ballistocardiac
artifact in EEG-fMRI and the window can therefore be smaller). I think
this somewhat matches the essence of the workflow which has been
described in Butler (2005).

After the ECG has been (somewhat) subtracted, I high-pass filter the
EMG at 30 Hz and rectify (for getting the amplitude modulation).

Regards,
Johan

On Wed, Dec 2, 2009 at 6:56 AM, Scott Makeig <smakeig at gmail.com> wrote:
> Johan -
> Yes, ICA decomposition should return 1 or more ECG component(s). Removing
> them from t he data, should remove the ECG -- unless you have widely
> separated EMG electrodes such that each of them records a separate EMG and
> ECG ( if from local ECG effects rather than volume conduction). In that
> case, a single-channel component map could account for both local ECG and
> EMG effects. Use enough data! (see the tutorial for estimates).
> Scott Makeig
>
> On Tue, Dec 1, 2009 at 9:47 AM, Johan <johanvandermeer at gmail.com> wrote:
>>
>> Hello!
>>
>> I, too, am looking for something that can remove artifacts from the
>> EMG. In particular I want to remove ECG artifacts from the (surface)
>> EMG recorded from muscles in the neck. This ECG artifact is
>> particularly nasty when you try to calculate EMG-EMG coherence
>> spectra. High-pass filtering alone won't cut it to succesfully remove
>> the ECG artifact.
>>
>> The AAR1.3 has some functionality to remove EOG artifacts from EEG,
>> but makes no mention what to do to/how to proceed to remove ECG from
>> surface EMG. I do have a separately recorded ECG signal.
>>
>> Is there anything you could recommend?
>>
>> Regards,
>>
>> Johan van der Meer, PhD Stud.
>> Academic Medical Centre, Amsterdam
>>
>>
>>
>>
>>
>> On Mon, Oct 12, 2009 at 6:37 PM, Klados Manousos <mklados at gmail.com>
>> wrote:
>> > Dear Jordan
>> >
>> > Automatic Artifact Rejection (AAR) Plugin for EEGLAB is availiable in
>> > the
>> > EEGLAB's site. As i quickly see in the paper mentioned above they use
>> > LMS
>> > algorithm for the implementation of the adaptive filters. AAR includes
>> > LMS
>> > algorithm so you can use it (or mode it as you like...for the
>> > cascading).
>> > Except LMS AAR includes another 4 (i thing) regression-based algorithms
>> > for
>> > artifact rejection. According to my analysis and my opinion (which is
>> > going
>> > to be published soon) among the regression techinques Schlogl's
>> > algorithm
>> > (Schlogl,2007) seem to have better performance. This aglorithm doesn't
>> > included in the AAR but it is very easy in it implementation. I have to
>> > mention that Schlogl algorithm uses one step for the computation of
>> > propagation coefficients and not an iterative procedure as adatpive
>> > filters.
>> > If you still want to use an adaptive filter included in the AAR i
>> > propose
>> > you to use LMS. Comparison's results (Klados,2008) suggest that LMS
>> > performs
>> > well in EEG data.
>> >
>> >
>> > Schlogl, C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb, G.
>> > Pfurtscheller,
>> > “A fully automated correction method of EOG artifacts in EEG recordings”
>> > ,
>> > Clinical Neurophysiology 118 (2007) 98–104.
>> > Ghirnikar, A.   Alexander, S.T. Stable recursive least squares filtering
>> > using an inverse QR decomposition. IEEE International Conference on
>> > Acoustics, Speech and Signal Processing 1990 ICASSP-90, 1990; 3 :
>> > 1623-1626
>> > M.A.Klados, C. Papadelis, C.D. Lithari and P.D. Bamidis. The Removal Of
>> > Ocular Artifacts From EEG Signals: A Comparison of Performances For
>> > Different Methods, J. Vander Sloten, P. Verdonck, M. Nyssen, J. Haueisen
>> > (Eds.): ECIFMBE 2008, IFMBE Proceedings 22, pp. 1259–1263, 2008
>> >
>> >
>> > 2009/10/8 Power elf, Jordan <J.PowerElf2 at nuigalway.ie>
>> >>
>> >> Compatibility and artifact attenuation issues
>> >>
>> >> Dear EEGLAB members,
>> >>
>> >> I am currently conducting an electroencephalography experiment with the
>> >> neuroscience division of the National University of Ireland Galway.
>> >> During
>> >> the experimental design phase I encountered much discussion about the
>> >> algorithms used to attenuate artifact interference in the EEG signal.
>> >> Many
>> >> papers seem to agree that the only means of accounting for ECG and EOG
>> >> artifacts is to record these signals simultaneously on a different
>> >> channel.
>> >> Once the data is collected it can then be processed using filtering
>> >> methods.
>> >> These papers (such as "Artifact removal from EEG signals using adaptive
>> >> filters in cascade") include many advanced algorithms to account for
>> >> these
>> >> artifacts once all the data has been recorded. Unfortunately the sheer
>> >> scale
>> >> of my experiment makes the manual processing of my data a prohibitive
>> >> prospect. I was wondering if EEGlab included a facility that applied
>> >> these
>> >> adaptive filter algorithms automatically when presented with the raw
>> >> eeg
>> >> data and the EKG and EOG artifacts. I would also like to know if eeglab
>> >> is
>> >> compatible with labchart, the program i am using to record my data.
>> >>
>> >>
>> >> Any help you could provide would be greatly appreciated,
>> >> Jordan
>> >>
>> >> _______________________________________________
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>> >
>> >
>> >
>> > --
>> > Klados A. Manousos
>> > Graduate Student, Research Assistant
>> > Group of Applied Neurosciences
>> > Lab of Medical Informatics, Medical School
>> > Aristotle University of Thessaloniki
>> > Thessaloniki, Greece
>> > _________________________________________________
>> > Tel: +30-2310-999332
>> > Website: http://lomiweb.med.auth.gr/gan/mklados
>> >
>> >
>> >
>> >
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>>
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>
> --
> Scott Makeig, Research Scientist and Director, Swartz Center for
> Computational Neuroscience, Institute for Neural Computation, University of
> California San Diego, La Jolla CA 92093-0961, http://sccn.ucsd.edu/~scott
>