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		<title>en&gt;TheHappiestCritic: added description section</title>
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		<updated>2012-02-14T21:32:05Z</updated>

		<summary type="html">&lt;p&gt;added description section&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;{{no footnotes|date=December 2011}}&lt;br /&gt;
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&amp;#039;&amp;#039;&amp;#039;Quantitative Electroencephalography&amp;#039;&amp;#039;&amp;#039; (&amp;#039;&amp;#039;&amp;#039;QEEG&amp;#039;&amp;#039;&amp;#039;) a field concerned with the numerical analysis of electroencephalography data and associated behavioral correlates.&lt;br /&gt;
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== Details ==&lt;br /&gt;
Techniques commonly found in digital signal analysis have been extended to the analysis of [[electroencephalography]] (EEG). These include [[Wavelet transform|Wavelet]] analysis and [[Fourier Transform|Fourier]] analysis.&lt;br /&gt;
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The analog signal, comprising the microvoltage time series of the EEG, is sampled digitally with analog to digital technology and sampling rates adequate to over-sample the signal (using the [[Harry Nyquist|Nyquist]] principle  of exceeding twice the highest frequency being detected). Modern EEG amplifiers use adequate sampling to resolve the EEG across the traditional medical band from DC to 70 or 100&amp;amp;nbsp;Hz, using sample rates of 250/256, 500/512, to over 1000 samples per second, depending on the intended application.{{Citation needed|date=May 2012}}&lt;br /&gt;
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==Fourier Analysis of EEG==&lt;br /&gt;
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The Fourier decomposes the EEG time series into a voltage by frequency spectral graph commonly called the “power spectrum”, with power being the square of the EEG magnitude, and magnitude being the integral average of the amplitude of the EEG signal, measured from(+) peak-to-(-)peak), across the time sampled, or epoch.  The epoch length determines the frequency resolution of the Fourier, with a 1 second epoch providing a 1&amp;amp;nbsp;Hz resolution (plus/minus 0.5&amp;amp;nbsp;Hz resolution), and a 4 second epoch providing ¼ Hz, or plus/minus 0.125&amp;amp;nbsp;Hz resolution.&lt;br /&gt;
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* &amp;lt;math&amp;gt;f(\xi) = \int_{-\infty}^{\infty} f(x)e^{-2 \pi ix \xi}\, dx&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
*where &amp;#039;&amp;#039;ξ =&amp;#039;&amp;#039; frequency&lt;br /&gt;
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==Wavelet Analysis of EEG==&lt;br /&gt;
A Wavelet is a time-frequency transformation that allows analysis of EEG signals in the time extension that is not possible with Fourier analysis.&lt;br /&gt;
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*&amp;lt;math&amp;gt; X(a,b) = \frac{1}{\sqrt{a}}\int_{-\infty}^{\infty}\overline{\Psi\left(\frac{t - b}{a}\right)} x(t)\, dt &amp;lt;/math&amp;gt;&lt;br /&gt;
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* where &amp;#039;&amp;#039;a = &amp;#039;&amp;#039;scaling; &amp;#039;&amp;#039;b =&amp;#039;&amp;#039; time&lt;br /&gt;
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==Uses==&lt;br /&gt;
&lt;br /&gt;
QEEG has been accepted by for clinical application in some areas, such as cerebro-vascular disorders and epilepsy, though it remains yet to be accepted in other clinical areas, such as diagnosing mild traumatic brain injury or psychiatric disorders. The use of qEEG techniques in investigations in clinical and research settings are on going.{{Citation needed|date=May 2012}}&lt;br /&gt;
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== References ==&lt;br /&gt;
{{reflist}}&lt;br /&gt;
1. Kececi H, Degirmenci Y. Quantitative EEG and cognitive evoked potentials in anemia. http://dx.doi.org/10.1016/j.neucli.2008.01.004&lt;br /&gt;
[[Category:Electroencephalography]]&lt;/div&gt;</summary>
		<author><name>en&gt;TheHappiestCritic</name></author>
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