<font size="4">Dear Jordan<br><br>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. </font> <br>
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<ul><li><font size="4"><span style="font-family: "Times New Roman","serif";" lang="EN-US"><span style=""><span style="font-family: "Times New Roman"; font-style: normal; font-variant: normal; font-weight: normal; font-size: 7pt; line-height: normal; font-size-adjust: none; font-stretch: normal;"></span></span></span><span style="font-family: "Times New Roman","serif";" lang="EN-US">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.</span></font></li><li><meta http-equiv="Content-Type" content="text/html; charset=utf-8"><meta name="ProgId" content="Word.Document"><meta name="Generator" content="Microsoft Word 12"><meta name="Originator" content="Microsoft Word 12"><link rel="File-List" href="file:///C:%5CDOCUME%7E1%5C4F20%7E1%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_filelist.xml"><link rel="themeData" href="file:///C:%5CDOCUME%7E1%5C4F20%7E1%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_themedata.thmx"><link rel="colorSchemeMapping" href="file:///C:%5CDOCUME%7E1%5C4F20%7E1%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_colorschememapping.xml"><style>
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{page:Section</style><font size="4"><span style="font-size: 12pt; font-family: "Times New Roman","serif"; color: black;" lang="EN-US">Ghirnikar,
A.<span style=""> </span>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</span></font></li><li><meta http-equiv="Content-Type" content="text/html; charset=utf-8"><meta name="ProgId" content="Word.Document"><meta name="Generator" content="Microsoft Word 12"><meta name="Originator" content="Microsoft Word 12"><link rel="File-List" href="file:///C:%5CDOCUME%7E1%5C4F20%7E1%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_filelist.xml"><link rel="themeData" href="file:///C:%5CDOCUME%7E1%5C4F20%7E1%5CLOCALS%7E1%5CTemp%5Cmsohtmlclip1%5C01%5Cclip_themedata.thmx"><style>
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</style><font size="4"><span style="font-family: "Times New Roman","serif";" lang="EN-US">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</span></font><span style="font-family: "Times New Roman","serif";" lang="EN-US"></span>
</li></ul>
<br><br><br><div class="gmail_quote">2009/10/8 Power elf, Jordan <span dir="ltr"><<a href="mailto:J.PowerElf2@nuigalway.ie">J.PowerElf2@nuigalway.ie</a>></span><br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<div>
<div style="direction: ltr; font-family: Tahoma; color: rgb(0, 0, 0); font-size: 13px;">
<font size="1" color="black" face="Tahoma"><span style="font-size: 13px;" dir="ltr"><font size="2"><span style="font-weight: bold;">Compatibility and artifact attenuation issues</span><br>
<span style="font-family: Tahoma;"><span style="font-family: Tahoma;"><br>
</span></span>Dear EEGLAB members,<br>
<span style="font-family: Tahoma;"><br>
</span>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. </font><font size="2">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.<br>
<span style="font-family: Tahoma;"><br>
<br>
<span style="font-family: Tahoma;">Any help you could provide would be greatly appreciated,<br>
<span style="font-family: Tahoma;">Jordan</span><br>
</span></span></font></span></font></div>
</div>
<br>_______________________________________________<br>
Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html" target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>
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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">http://lomiweb.med.auth.gr/gan/mklados</a><br><br><br><br>