[Eeglablist] Number of samples

Pål Gunnar Larsson pall at ous-hf.no
Tue May 27 00:25:23 PDT 2014


Hi Caroline

I would suggest that you do some analysis of your data: You could do FFT on 1s or 2s data. Calculate mean and standard deviation through the epochs. Std can tell you something about the dynamics and/or noise -> small std means little noise and lttle variability as high std means noise and/or large variability.  May be you find you will work on the averages shorter epochs.

Pål

Pål G. Larsson M.D., PhD.
Head of Clinical Neurophysiology
Department of Neurosurgery
Division of Surgery and Clinical Neuroscience

Oslo University Hospital
Po.box 4950 Nydalen
0424 Oslo
Norway
Tel:  (+47) 23074407
Mobile: (+47) 93429791
E-mail: pall at ous-hf.no<mailto:pall at ous-hf.no>
not sensitive

Fra: Robertson, Caroline [mailto:carobertson at csu.edu.au]
Sendt: 27. mai 2014 07:18
Til: Pål Gunnar Larsson; 'Samaneh Valipour'; mmiyakoshi
Kopi: eeglablist at sccn.ucsd.edu
Emne: RE: [Eeglablist] Number of samples

Hi all,

I am currently examining the EEG response to certain exercise bouts. We only have a 256Hz system and are currently using 30sec data sample window. As you discuss below this may not improve the information because of the variability of the signal... on top of which exercise clearly adds to the level of noise... I have only read in one paper that the minimal suggested sample window during exercise is 20secs of data but does anyone have any other suggestions?

Many thanks
Caroline

From: eeglablist-bounces at sccn.ucsd.edu<mailto:eeglablist-bounces at sccn.ucsd.edu> [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Pål Gunnar Larsson
Sent: Thursday, 22 May 2014 4:33 PM
To: 'Samaneh Valipour'; mmiyakoshi
Cc: eeglablist at sccn.ucsd.edu<mailto:eeglablist at sccn.ucsd.edu>
Subject: Re: [Eeglablist] Number of samples

Remember that EEG is a very dynamic signal. Hence, longer samples is not expected to give better information as the signal changes within the sample window. However, increasing the sampling rate, increases the information. According to Nyquist you will be able to reconstruct a signal if you sample faster than the double of the highest frequency in the signal. However, that is when the signal is stable (EEG is not) and the sample is infinite long. Practically you will often end up sampling 5-10 time the highest frequency in biological signals.

Pål G. Larsson M.D., PhD.
Head of Clinical Neurophysiology
Department of Neurosurgery
Division of Surgery and Clinical Neuroscience

Oslo University Hospital
Po.box 4950 Nydalen
0424 Oslo
Norway
Tel:  (+47) 23074407
Mobile: (+47) 93429791
E-mail: pall at ous-hf.no<mailto:pall at ous-hf.no>
not sensitive


Dr. philos. Pål G. Larsson
Seksjonsleder Klinisk nevrofysiologi
Nevrokirurgisk avdeling
Oslo Universitetssykehus
Postboks 4950 Nydalen
0424 Oslo

Tlf.:  23074407
Mobil: 93429791

E-mail: pall at ous-hf.no<mailto:pal.gunnar.larsson at ous-hf.no>

Denne meldingen innholder ikke sensitiv informasjon som bryter med OUS sine regler for taushetsplikt

Fra: eeglablist-bounces at sccn.ucsd.edu<mailto:eeglablist-bounces at sccn.ucsd.edu> [mailto:eeglablist-bounces at sccn.ucsd.edu] På vegne av Samaneh Valipour
Sendt: 21. mai 2014 06:58
Til: mmiyakoshi
Kopi: eeglablist at sccn.ucsd.edu<mailto:eeglablist at sccn.ucsd.edu>
Emne: Re: [Eeglablist] Number of samples

Thanks a lot Dear Makoto.

On Tue, May 20, 2014 at 10:03 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu<mailto:mmiyakoshi at ucsd.edu>> wrote:
Dear Samaneh,

Samples you mean sampling points? Yes of course. The more sampling points you have, the better (i.e. smoother and more reliable) the results are.

Makoto

2014-05-19 21:31 GMT-07:00 Samaneh Valipour <samanehvalipour61 at gmail.com<mailto:samanehvalipour61 at gmail.com>>:
Dear EEGLAB users,
I would like to be sure,whether the results of analysis of EEG using  FFT or DWT depend on the number of samples?If is so, what is best choice for number of samples?
--
With very kind regards,

Samaneh .Valipour

PhD research student: DOES_UOP_INDIA
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--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego



--
With very kind regards,

Samaneh .Valipour

PhD research student: DOES_UOP_INDIA
--------------------------------------------------------------------
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                           Pune Ganeshkhind,
                          Pune-411007 ,
                           Maharashtra, (India) *
Phone nos :*+91-20-25699841,+91-20-25691256,+91-20-25601419


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