<p><strong>Short answer</strong><br>
As far as I can see - no you can't. </p>

<p><strong>Background</strong><br>
In EEG systems, unipolar signals are measurements against a distant reference electrode, for example Fpz (Fig. 1). So suppose I have recorded <em>unipolar</em> EEG signals, say O1 and O2 against Fps, then I can obtain a bipolar measurement offline by subtracting O1-O2 (source: <a href="https://www.biopac.com/knowledge-base/bipolar-eeg/" rel="nofollow noreferrer">Biopac</a>). </p>

<p>However, if you start with a bipolar measurement, <em>e.g.</em> O1-O2, then you can never reduce those recordings back to O1-Fpz and O2-Fpz as the O1 and O2 signals are independent of Fpz.</p>

<p>Further, 'the' Fpz signal is non-existant, as an electrophysiological potential (and in fact <em>any</em> potential), is a potential <em>difference</em> between 2 points. There <em>is no</em> potential difference on one electrode.        </p>

<p><sub>PS. 
I am not proficient in <strong><a href="https://onlinecourses.science.psu.edu/stat505/node/49" rel="nofollow noreferrer">principal component analysis</a></strong>, but I do know that by cross-correlating various electrode-pairs a source analysis can be done. Perhaps you could somehow extract the unipolar signal from bipolar signals, but I must say that a Google Scholar search using the search terms 'principal + component + analysis + eeg + bipolar + to + unipolar' did not yield any useful hits, at least at first glance.</sub> </p>

<p><a href="https://i.sstatic.net/baslw.gif" rel="nofollow noreferrer"><img src="https://i.sstatic.net/baslw.gif" alt="enter image description here"></a><br>
<sup>Fig.1. EEG montage. source: <a href="https://www.edfplus.info/specs/edftexts.html" rel="nofollow noreferrer">Kemp <em>et al</em>., 2003</a></sup></p>

CC BY-SA 3.0
2017-11-25T21:36:03.717Z
2017-11-25T22:40:02.107Z
2017-11-25T22:40:02.107Z
AliceD
<p>I have bipolar EEG signal of Fpz-Cz of EEG sleep data which I have downloaded from physionet. I would like to have Fpz signal for my sleep study.</p>

<p>Is there any way I could convert a bipolar EEG signal to a monopolar (unipolar) EEG signal?</p>

<methodology><eeg><electrophysiology><signal-processing>
Can a bipolar EEG signal be converted to a monopolar (unipolar) one?
maia
# Can a bipolar EEG signal be converted to a monopolar (unipolar) one?

(Asked by: username_0 on 2017-11-25)

I have bipolar EEG signal of Fpz-Cz of EEG sleep data which I have downloaded from physionet. I would like to have Fpz signal for my sleep study.

Is there any way I could convert a bipolar EEG signal to a monopolar (unipolar) EEG signal?

**Tags:** methodology, eeg, electrophysiology, signal-processing


---

## 1 answers

### Answer by username_1 on 2017-11-25. Score: 1 | Accepted answer

**Short answer**  
As far as I can see - no you can't.

**Background**  
In EEG systems, unipolar signals are measurements against a distant reference electrode, for example Fpz (Fig. 1). So suppose I have recorded *unipolar* EEG signals, say O1 and O2 against Fps, then I can obtain a bipolar measurement offline by subtracting O1-O2 (source: [Biopac](https://www.biopac.com/knowledge-base/bipolar-eeg/)).

However, if you start with a bipolar measurement, *e.g.* O1-O2, then you can never reduce those recordings back to O1-Fpz and O2-Fpz as the O1 and O2 signals are independent of Fpz.

Further, 'the' Fpz signal is non-existant, as an electrophysiological potential (and in fact *any* potential), is a potential *difference* between 2 points. There *is no* potential difference on one electrode.

PS.
I am not proficient in **[principal component analysis](https://onlinecourses.science.psu.edu/stat505/node/49)**, but I do know that by cross-correlating various electrode-pairs a source analysis can be done. Perhaps you could somehow extract the unipolar signal from bipolar signals, but I must say that a Google Scholar search using the search terms 'principal + component + analysis + eeg + bipolar + to + unipolar' did not yield any useful hits, at least at first glance.

[![enter image description here](https://i.sstatic.net/baslw.gif)](https://i.sstatic.net/baslw.gif)  
Fig.1. EEG montage. source: [Kemp *et al*., 2003](https://www.edfplus.info/specs/edftexts.html)


---

