[Eeglablist] artifact detection in continuous data

[Mahesh Casiraghi]

Dear James,


completely agree that this is an issue: I also find the possibility to apply
the same artifact detection techniques available for segmented data  to
continuous data quite necessary, and needed to write some custom workarounds
whenever in the condition to do so, both in EEGLAB and ERPLAB. I am not
aware of common ways to systematically do that and would be very happy - and
have the feeling I am not alone in that - to see such a technique you are
proposing implemented in a shareable tool or in a simple bunch of reliable
functions!


Perhaps Arnaud is already aware (as he often is) of an already implemented
way or workaround for easily doing that.


Cheers,


Mahesh




Mahesh M. Casiraghi
PhD candidate - Cognitive Sciences
Roberto Dell'Acqua Lab, University of Padova
Pierre Jolicoeur Lab, Univesité de Montréal
mahesh.casiraghi at umontreal.ca

I have the conviction that when Physiology will be far enough advanced, the
poet, the philosopher, and the physiologist will all understand each other.
Claude Bernard




On Thu, Jun 9, 2011 at 10:53 AM, James Desjardins <jdesjardins at brocku.ca>wrote:

> Dear list members,
>
> For my purposes it is beneficial to reject artifacts in the continuous
> data rather than following segmentation. I find the artifact detection
> tools in EEGLAB extremely helpful when working with segmented data.
>
> I am considering working on a plugin that windows continuous data,
> takes advantage of some of the currently available artifact detection
> tools for segmented data, then translates the windowed rejection
> information back to time intervals in the continuous data.
>
> Are there already methods for doing this... or is this something that
> someone else is already working on?
>
>
> James Desjardins
> Technician, MA Student
> Department of Psychology, Behavioural Neuroscience
> Cognitive and Affective Neuroscience Lab
> Brock University
> 500 Glenridge Ave.
> St. Catharines, ON, Canada
> L2S 3A1
> 905-688-5550 x4676
>
>
>
>
>
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