<p>A study by D’Zmura et al. (<a href="https://www.google.com.au/url?sa=t&amp;rct=j&amp;q=&amp;esrc=s&amp;source=web&amp;cd=1&amp;cad=rja&amp;uact=8&amp;ved=0CCMQFjAA&amp;url=http://cnslab.ss.uci.edu/speechattention/content/DZmuraHCIInternational2009.pdf&amp;ei=nfoTVbS-CpCC8gXOy4LgCA&amp;usg=AFQjCNEMv02n223j2Gy0U740F1WclKrY1A&amp;sig2=vJimVjXvZn1XY-zXdCf2yA&amp;bvm=bv.89217033,d.dGc" rel="nofollow noreferrer">2009</a>) in which two syllables were spoken in imagination showed that imagined speech information was present in EEG alpha, beta and theta bands. The <strong>beta band</strong> (13-18 Hz) proved most informative. The most informative electrodes were located mainly near the top of the head (<strong>vertex</strong>) where electromyographic artifacts had least influence.</p>
<p>They used various signal processing steps (standard low-pass filtering to remove 60 Hz line artifact, DC filtering, signal enveloping etc.) to clean up their signal. Please refer to the reference list for specific signal processing details.</p>
<p><sub><strong>References</strong></p>
<ul>
<li><a href="https://www.google.com.au/url?sa=t&amp;rct=j&amp;q=&amp;esrc=s&amp;source=web&amp;cd=1&amp;cad=rja&amp;uact=8&amp;ved=0CCMQFjAA&amp;url=http://cnslab.ss.uci.edu/speechattention/content/DZmuraHCIInternational2009.pdf&amp;ei=nfoTVbS-CpCC8gXOy4LgCA&amp;usg=AFQjCNEMv02n223j2Gy0U740F1WclKrY1A&amp;sig2=vJimVjXvZn1XY-zXdCf2yA&amp;bvm=bv.89217033,d.dGc" rel="nofollow noreferrer">D’Zmura et al. Lecture notes in computer science 2009;40-8. HCI International</a></li>
<li><a href="https://ieeexplore.ieee.org/document/5515807" rel="nofollow noreferrer">Brigham &amp; Kumar, iCBBE 2010</a></sub></li>
</ul>

CC BY-SA 4.0
2015-03-26T12:37:21.503Z
2022-04-27T19:13:38.840Z
2022-04-27T19:13:38.840Z
AliceD
<p>I am doing an EEG experiment about imagined speech recognition. Which frequencies will have the most relevant information? I chose the frequency band [4-40] Hz as a start, mainly because of signal processing considerations. Filtering out the remaining frequencies basically removes the DC voltage and most of the EOC artifacts. <br><br> Which frequencies should I select?
<br><br>Also which channels will contain the signal (<em>i.e.</em>, the most relevant data)?</p>

<eeg><signal-detection><speech><signal-processing>
What are proper EEG frequency bands and electrode placements for imagined speech?
Learner
# What are proper EEG frequency bands and electrode placements for imagined speech?

(Asked by: username_0 on 2015-03-25)

I am doing an EEG experiment about imagined speech recognition. Which frequencies will have the most relevant information? I chose the frequency band [4-40] Hz as a start, mainly because of signal processing considerations. Filtering out the remaining frequencies basically removes the DC voltage and most of the EOC artifacts.   
  
 Which frequencies should I select?
  
  
Also which channels will contain the signal (*i.e.*, the most relevant data)?

**Tags:** eeg, signal-detection, speech, signal-processing


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## 1 answers

### Answer by username_1 on 2015-03-26. Score: 8 | Accepted answer

A study by D’Zmura et al. ([2009](https://www.google.com.au/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0CCMQFjAA&url=http://cnslab.ss.uci.edu/speechattention/content/DZmuraHCIInternational2009.pdf&ei=nfoTVbS-CpCC8gXOy4LgCA&usg=AFQjCNEMv02n223j2Gy0U740F1WclKrY1A&sig2=vJimVjXvZn1XY-zXdCf2yA&bvm=bv.89217033,d.dGc)) in which two syllables were spoken in imagination showed that imagined speech information was present in EEG alpha, beta and theta bands. The **beta band** (13-18 Hz) proved most informative. The most informative electrodes were located mainly near the top of the head (**vertex**) where electromyographic artifacts had least influence.

They used various signal processing steps (standard low-pass filtering to remove 60 Hz line artifact, DC filtering, signal enveloping etc.) to clean up their signal. Please refer to the reference list for specific signal processing details.

**References**

* [D’Zmura et al. Lecture notes in computer science 2009;40-8. HCI International](https://www.google.com.au/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0CCMQFjAA&url=http://cnslab.ss.uci.edu/speechattention/content/DZmuraHCIInternational2009.pdf&ei=nfoTVbS-CpCC8gXOy4LgCA&usg=AFQjCNEMv02n223j2Gy0U740F1WclKrY1A&sig2=vJimVjXvZn1XY-zXdCf2yA&bvm=bv.89217033,d.dGc)
* [Brigham & Kumar, iCBBE 2010](https://ieeexplore.ieee.org/document/5515807)


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