New method for analysing sensitivity distributions of electroencephalography measurements
| Autor: | Outi Väisänen, Jaakko Malmivuo, Juho Väisänen, Jari Hyttinen |
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| Rok vydání: | 2007 |
| Předmět: |
Models
Anatomic Future studies medicine.diagnostic_test business.industry Biomedical Engineering Pattern recognition Electroencephalography Signal Processing Computer-Assisted Sensitivity and Specificity Computer Science Applications Correlation Signal-to-noise ratio (imaging) Region of interest Head model Electronic engineering medicine Humans Sensitivity (control systems) Artificial intelligence Evoked potential business Electrodes Mathematics |
| Zdroj: | Medicalbiological engineeringcomputing. 46(2) |
| ISSN: | 0140-0118 |
| Popis: | In this paper, we introduce a new modelling related parameter called region of interest sensitivity ratio (ROISR), which describes how well the sensitivity of an electroencephalography (EEG) measurement is concentrated within the region of interest (ROI), i.e. how specific the measurement is to the sources in ROI. We demonstrate the use of the concept by analysing the sensitivity distributions of bipolar EEG measurement. We studied the effects of interelectrode distance of a bipolar EEG lead on the ROISR with cortical and non-cortical ROIs. The sensitivity distributions of EEG leads were calculated analytically by applying a three-layer spherical head model. We suggest that the developed parameter has correlation to the signal-to-noise ratio (SNR) of a measurement, and thus we studied the correlation between ROISR and SNR with 254-channel visual evoked potential (VEP) measurements of two testees. Theoretical simulations indicate that source orientation and location have major impact on the specificity and therefore they should be taken into account when the optimal bipolar electrode configuration is selected. The results also imply that the new ROISR method bears a strong correlation to the SNR of measurement and can thus be applied in the future studies to efficiently evaluate and optimize EEG measurement setups. |
| Databáze: | OpenAIRE |
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