[Eeglablist] Artifact removal using ADJUST plugin (Rabnawaz khan)

Rabnawaz khan 13mseerabnawaz at seecs.edu.pk
Mon May 8 18:22:39 PDT 2017

Dear Marco,

Hoping all is well, I would like to get a bit more in my previous query.
there are two condition, one is number of channel (which is fix in my case,
14 channels) the second is time duration of data(which I can increase). can
you suggest minimum duration of EEG recordings with 14 channels to properly
apply ADJUST and get good results.

Best Regards,


On Wed, May 3, 2017 at 11:48 AM, Rabnawaz khan <13mseerabnawaz at seecs.edu.pk>

> Dear Armand and Marco,
> Thank you so much for your valuable comments. Actually my task is to work
> out for Alpha absolute power values for this data. for that reason i wanted
> to use automatic artifact removal in my pre-processing phase, but i was
> surprised after getting un-expecting values for alpha absolute power from
> my data.
> considering the scenario, there is much noise present in the data. So
> working by visual inspection and rejecting the the noisy portion from my
> data now its seems better as I get expected values for alpha band of EEG.
> Thanks
> Best Regards,
> Rabnawaz
> On Tue, May 2, 2017 at 3:05 PM, Marco Buiatti <marco.buiatti at gmail.com>
> wrote:
>> Dear Rabnawaz,
>> Armand is right, 180 seconds are definitely not enough to obtain a good
>> ICA decomposition, and 14 channels are too few for ADJUST working properly.
>> The reason for this is that ADJUST is based on spatial features which are
>> not correctly computed for montages below 32 channels.
>> A final, general consideration: the term "automatic" refers to the fact
>> that no parameter tuning is needed, not that it works magically (neither
>> ADJUST nor any other automatic method pretends to be 100% reliable). When
>> using automatic methods, you should always review the results to
>> double-check their efficacy.
>> All the best,
>> Marco Buiatti (main ADJUST developer)
>> On 29 April 2017 at 13:16, Armand Mensen <research.mensen at gmail.com>
>> wrote:
>>> Hi Rabnawaz,
>>> So with only 14 channels and 180 seconds of recording, its going to be
>>> very difficult for you to "clean" your data.
>>> For ICA: While there is no set rule for just how many channels or length
>>> of recording will result in a good separation of independent components...
>>> considered that the maximum number of independent components you are able
>>> to find is equal to the rank of your dataset (in your case 14 channels).
>>> Thus it seems highly unlikely that ICA will find a single component that
>>> captures the spurious (as you descrive it) artefact without also captures
>>> some genuine neural activity with it.
>>> In terms of time, the longer your recording the better the ICA algorithm
>>> can separate truly independent sources. 180 seconds is very little
>>> information to go on for the ICA learning. The quality of the resulting
>>> independent components will also depend on what sort of sources are in your
>>> data. An active component that is consistent throughout the 180 seconds of
>>> your recording is more likely to be captures than a few random artefacts
>>> etc.
>>> There are complete books and 100s of papers written about ICA, and so I
>>> cannot describe all the pitfalls in this email, and I would suggest having
>>> a good look through the literature before blindly applying a tool like
>>> ADJUST and hoping for the best.
>>> My best advice is that you attempt with different filtering settings to
>>> eliminate the artefacts you find in your data. If your filters intrude in
>>> your frequencies of interest, then I would suggest rejecting those samples
>>> in your data with artefacts and working with the remaining time that is
>>> artefact free (although with only 180 seconds, you don't have much to work
>>> with).
>>> Good luck!
>>> Armand
>>> On 29 April 2017 at 07:13, Rabnawaz khan <13mseerabnawaz at seecs.edu.pk>
>>> wrote:
>>>> Dear Mensen,
>>>> Thank you for your response.
>>>> After plotting my data using EEGlab plot (scroll plot option), I can
>>>> see some portion of my data is very noisy, most of the channels are giving
>>>> huge peaks for some duration (I am not sure how to differentiate these
>>>> noise but I can guess these are not the eye or muscle artefacts). Moreover,
>>>> I am using Emotiv EPOC headset for recordings, which is 14 channels data,
>>>> and the duration of my recordings is 180sec.
>>>> any good advice dealing with it?
>>>> thanks,
>>>> Best Regards,
>>>> Rabnawaz
>>>> On Wed, Apr 26, 2017 at 4:49 PM, Armand Mensen <
>>>> research.mensen at gmail.com> wrote:
>>>>> Dear Rabnawaz,
>>>>> A few things here to comment on.
>>>>> 1) I think you may be expecting too much from any automatic artefact
>>>>> removal (or manual ones for that matter). Which sorts of artefacts any tool
>>>>> can remove from your data may depend on a multitude of factors. For
>>>>> example, ICA is generally quite good at finding eye blinks and eye
>>>>> movements. However even there it depends on the number of channels you
>>>>> recorded, and the length of your recording time, whether those sorts of
>>>>> artefacts can be removed without taking too much good data with them. So
>>>>> what sort of artefacts are you trying to deal with? How many channels do
>>>>> you have? How long is your recording?
>>>>> 2) It is generally unwise to run multiple ICA analysis one after
>>>>> another. There are a couple of reasons for this, but the main one (I think)
>>>>> is that you are reducing the rank of your data each run. This rank
>>>>> reduction is not always so easily or accurately detectable and will lead to
>>>>> problems.
>>>>> 3) I've used ADJUST sparingly in the past, and wasn't overly
>>>>> impressed. While examining components manually does take longer than just
>>>>> running some automatic script... you will get a good feeling for the
>>>>> quality of your data as well as the sorts of strong independent sources
>>>>> that are there (whether artefactual or not). I completely see the utility
>>>>> of using the same artefact criteria and taking some of the subjective
>>>>> decision making out of using ICA to remove artefacts... however only to the
>>>>> extent that these standard criteria are really generalisable, and useful in
>>>>> the first place [apologies to any ADJUST creator or enthusiast; I'd be
>>>>> happy to be convinced otherwise].
>>>>> Good luck with your analysis!
>>>>> Armand
>>>>>> ---------- Forwarded message ----------
>>>>>> From: Rabnawaz khan <13mseerabnawaz at seecs.edu.pk>
>>>>>> To: eeglablist at sccn.ucsd.edu
>>>>>> Cc:
>>>>>> Bcc:
>>>>>> Date: Tue, 25 Apr 2017 18:34:43 +0800
>>>>>> Subject: [Eeglablist] Artifact removal using ADJUST plugin
>>>>>> Dear All,
>>>>>> I am using ADJUST plugin for artifact removal from raw data. I follow
>>>>>> the instruction listed in the ADJUST manual to process the data. after
>>>>>> running ADJUST I get the artifacted ICs in a new pop-up window, I mark
>>>>>> these ICs for rejection and then I go to tools to remove these ICs (via
>>>>>> EEGlab GUI menu>>tools>>remove components). A new dataset is created
>>>>>> (eegdata pruned with ICA ), according to ADJUST tutorial this is the clean
>>>>>> eeg data, but I see from the plots that there is still artifact present in
>>>>>> the data. When I run ICA again and then again run ADJUST I get a new pop-up
>>>>>> window in which some other ICs are identified as artifacts. I remove these
>>>>>> ICs again. But still, artifact are present in data. I repeat running
>>>>>> ADUST many time and each time I get new ICs marked as an artifact.
>>>>>> I would be happy if you guide me with this problem.
>>>>>> Best Regards,
>>>>>> Rabnawaz
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>> --
>> Marco Buiatti
>> Neonatal Neuroimaging Unit
>> Center for Mind/Brain Sciences
>> University of Trento,
>> Piazza della Manifattura 1, 38068 Rovereto (TN), Italy
>> E-mail: marco.buiatti at unitn.it
>> Phone: +39 0464-808178 <+39%200464%20808178>
>> https://sites.google.com/a/unitn.it/marcobuiatti/
>> ***********************************************
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