Volume 36, Issue 2 (7-2012)
Research in Medicine 2012, 36(2): 82-88 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Barjesteh S, Navidi H R, Hassanpour-ezatti M, Gharagozli K, Aghayari H. Assessment of sensitivity and specificity of scaling exponent of quantitative electroencephalography in brain stroke detection. Research in Medicine 2012; 36 (2) :82-88
URL: http://pejouhesh.sbmu.ac.ir/article-1-1039-en.html
URL: http://pejouhesh.sbmu.ac.ir/article-1-1039-en.html
Departments of Biology, Faculty of Basic Sciences, Shahed University, Tehran, Iran , hassanpour@shahed.ac.ir
Abstract: (10740 Views)
Abstract
Background: Quantitative Electroencephalography (QEEG) is an effective modality in the study of brain functions in various conditions such as sleep, unconsciousness, seizures and hypnosis. The purpose of the study was to compare sensitivity and specificity of this new analytical procedure (QEEG) in the diagnosis of stroke.
Materials and methods: QEEG was performed on 17 healthy persons and 12 patients and two scaled exponents were extracted from EEG EEGs of stroke patients were recorded in closed eyes state and then analyzed this was compared with recordings obtained from healthy persons by multifractoral detrended fluctuation analysis method with the order (q=2.37) in Matlab software. Two factors ( ) were revealed for separating patients from healthy persons. The positive predictive value and negative predictive value of the scaling exponents obtained from the EEGs was calculated.
Results: Analysis of information derived from electroencephalogram of 29 persons, showed that the negative and positive predictive values were 100%.
Conclusion: This approach provides rapid diagnostic of stroke based on EEG without need for complex and time consuming calculations such as Fourier transform and special software. Thus, this method can be used for diagnosis of stroke on the base of EEG information and can help in medical centers when a specialist is not available.
Keywords: EEG, Stroke, Multifractal detrended fluctuation analysis, Sensitivity, Specificity.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
This Journal is licensed under a Creative Commons Attribution 4.0 International License | Research in Medicine
Designed & Developed by : Yektaweb