THE TITLE OF THE PAPER, IN BOLD CAPITAL LETTERS, CENTRED,

The experiments have been performed using a PCcomputer with a data acquisition board from NationalInstruments NI PCI-6110E, NI BNC-2110 adapter,an analogical oscilloscope for visualizing the signalsand a BNC cable to link the board output and theoscilloscope input (fig. 3).The EEG signal from figure 5 is obtained using thesame values for signal parameters like in the previouscase with one exception, the frequence value is 100.Fig. 3. Connection between computer andoscilloscopeThe ECG signal from next figure is obtained afterselection of signal type, by using parametersamplitude, frequency, sampling frequency withvalues 1, 1000, 44000. This signal is characteristicfor a intense physical activity. By the decrease orincrease of signal frequence it is obtained a bigger orlower heart rate.a)b)Fig. 5. EEG signalFurther, in order to obtain the VAG signal (fig. 6) theonly different parameter value is again for frequencyand is 2000.a)b)a)Fig. 4. ECG signal

knowledge in the field. This PC-based instrumentaffords visualization of biomedical signals withoutthe help of specialized medical instruments and is notnecessary the patient presence.ACKNOWLEDGEMENTThis paper was developed within framework offeredby CNCSIS grant 58GR/19.05.2006.REFERENCESFig. 6. VAG signalb)4. CONCLUSIONSIn Matlab environment using a data acquisition boardmay be achieved a virtual signal generator forbiomedical signals with GUI for their research. Theuser-friendly interactive GUI allows the easy andquick selecting of the parameters for the desiredoutput signal by the users with a low level ofJennings D., Flint A., Turton B.C.H., NokesL.D.M..(1995). Introduction to MedicalElectronics Applications, Edward Arnold, GreatBritain.Kutz M. (2003). Standard Handbook of BiomedicalEngineering and Design, McGraw-Hill, USA.Rangayyan M. R.(2002). Biomedical Signal Analysis,John Wiley & Sons, USA.