Johan -<div><br></div><div>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).</div>
<div><br></div><div>Scott Makeig<br><br><div class="gmail_quote">On Tue, Dec 1, 2009 at 9:47 AM, Johan <span dir="ltr"><<a href="mailto:johanvandermeer@gmail.com">johanvandermeer@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Hello!<br>
<br>
I, too, am looking for something that can remove artifacts from the<br>
EMG. In particular I want to remove ECG artifacts from the (surface)<br>
EMG recorded from muscles in the neck. This ECG artifact is<br>
particularly nasty when you try to calculate EMG-EMG coherence<br>
spectra. High-pass filtering alone won't cut it to succesfully remove<br>
the ECG artifact.<br>
<br>
The AAR1.3 has some functionality to remove EOG artifacts from EEG,<br>
but makes no mention what to do to/how to proceed to remove ECG from<br>
surface EMG. I do have a separately recorded ECG signal.<br>
<br>
Is there anything you could recommend?<br>
<br>
Regards,<br>
<font color="#888888"><br>
Johan van der Meer, PhD Stud.<br>
Academic Medical Centre, Amsterdam<br>
</font><div><div></div><div class="h5"><br>
<br>
<br>
<br>
<br>
On Mon, Oct 12, 2009 at 6:37 PM, Klados Manousos <<a href="mailto:mklados@gmail.com">mklados@gmail.com</a>> wrote:<br>
> Dear Jordan<br>
><br>
> Automatic Artifact Rejection (AAR) Plugin for EEGLAB is availiable in the<br>
> EEGLAB's site. As i quickly see in the paper mentioned above they use LMS<br>
> algorithm for the implementation of the adaptive filters. AAR includes LMS<br>
> algorithm so you can use it (or mode it as you like...for the cascading).<br>
> Except LMS AAR includes another 4 (i thing) regression-based algorithms for<br>
> artifact rejection. According to my analysis and my opinion (which is going<br>
> to be published soon) among the regression techinques Schlogl's algorithm<br>
> (Schlogl,2007) seem to have better performance. This aglorithm doesn't<br>
> included in the AAR but it is very easy in it implementation. I have to<br>
> mention that Schlogl algorithm uses one step for the computation of<br>
> propagation coefficients and not an iterative procedure as adatpive filters.<br>
> If you still want to use an adaptive filter included in the AAR i propose<br>
> you to use LMS. Comparison's results (Klados,2008) suggest that LMS performs<br>
> well in EEG data.<br>
><br>
><br>
> Schlogl, C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb, G. Pfurtscheller,<br>
> “A fully automated correction method of EOG artifacts in EEG recordings” ,<br>
> Clinical Neurophysiology 118 (2007) 98–104.<br>
> Ghirnikar, A. Alexander, S.T. Stable recursive least squares filtering<br>
> using an inverse QR decomposition. IEEE International Conference on<br>
> Acoustics, Speech and Signal Processing 1990 ICASSP-90, 1990; 3 : 1623-1626<br>
> M.A.Klados, C. Papadelis, C.D. Lithari and P.D. Bamidis. The Removal Of<br>
> Ocular Artifacts From EEG Signals: A Comparison of Performances For<br>
> Different Methods, J. Vander Sloten, P. Verdonck, M. Nyssen, J. Haueisen<br>
> (Eds.): ECIFMBE 2008, IFMBE Proceedings 22, pp. 1259–1263, 2008<br>
><br>
><br>
> 2009/10/8 Power elf, Jordan <<a href="mailto:J.PowerElf2@nuigalway.ie">J.PowerElf2@nuigalway.ie</a>><br>
>><br>
>> Compatibility and artifact attenuation issues<br>
>><br>
>> Dear EEGLAB members,<br>
>><br>
>> I am currently conducting an electroencephalography experiment with the<br>
>> neuroscience division of the National University of Ireland Galway. During<br>
>> the experimental design phase I encountered much discussion about the<br>
>> algorithms used to attenuate artifact interference in the EEG signal. Many<br>
>> papers seem to agree that the only means of accounting for ECG and EOG<br>
>> artifacts is to record these signals simultaneously on a different channel.<br>
>> Once the data is collected it can then be processed using filtering methods.<br>
>> These papers (such as "Artifact removal from EEG signals using adaptive<br>
>> filters in cascade") include many advanced algorithms to account for these<br>
>> artifacts once all the data has been recorded. Unfortunately the sheer scale<br>
>> of my experiment makes the manual processing of my data a prohibitive<br>
>> prospect. I was wondering if EEGlab included a facility that applied these<br>
>> adaptive filter algorithms automatically when presented with the raw eeg<br>
>> data and the EKG and EOG artifacts. I would also like to know if eeglab is<br>
>> compatible with labchart, the program i am using to record my data.<br>
>><br>
>><br>
>> Any help you could provide would be greatly appreciated,<br>
>> Jordan<br>
>><br>
>> _______________________________________________<br>
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><br>
><br>
><br>
> --<br>
> Klados A. Manousos<br>
> Graduate Student, Research Assistant<br>
> Group of Applied Neurosciences<br>
> Lab of Medical Informatics, Medical School<br>
> Aristotle University of Thessaloniki<br>
> Thessaloniki, Greece<br>
> _________________________________________________<br>
> Tel: +30-2310-999332<br>
> Website: <a href="http://lomiweb.med.auth.gr/gan/mklados" target="_blank">http://lomiweb.med.auth.gr/gan/mklados</a><br>
><br>
><br>
><br>
><br>
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<br>
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-- <br>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, <a href="http://sccn.ucsd.edu/~scott">http://sccn.ucsd.edu/~scott</a><br>
</div>