Virtual Instrumentation-LabVIEW and Data Acquisition
LabVIEW is an interactive programming language and it is user friendly. It allows to build applications with easy to understand and attractive Graphical User Interface. LabVIEW has a vast built in library of functions for numerical analysis, design and visualization of data. LabVIEW provides analysis and design tools and modules for control, signal processing, system identification etc. Development of any virtual instrument requires a front panel, which is the user interface and the block diagram which defines the functionality of the program through code. While creating any VI, initially elements are placed on the front panel, and then their properties are set. Block diagram is used to implement the VI's functionality.
Data acquisition using DAQ card:
A data acquisition device is required to pre-processed electrical signal to a computer for further processing, analysis and monitoring. Several options of data acquisition devices are available: using a PCI bus, a PCI Express bus, a PXI bus, or the computer USB. National instruments has made available several data acquisition cards, which may be suitably selected based on the required application. LabVIEW provides with ready-made libraries for making interfacing facing easier. Using these libraries, programs for the data acquisition are quickly and easily made for allowing more time to be spent on the processing and analysis of the acquired signals. In this research work, M Series USB-6221 is used as data acquisition interface. Figure 2 below shows the pin out of USB-6221. The device is connected with external measurement circuit on one side and personal computer (Laptop) on the other side.
Figure 2. USB M Series 6221 terminal pin out (courtesy-ni.com)
Signal Processing tools
LabVIEW provides signal processing tools for Fast Fourier Transform (FFT) and spectral analysis. It is possible to acquire time-domain signals, measure the frequency content, make suitable analysis, provide results in the form of table, displays etc. Using plug-in DAQ devices, flexibility is configuration makes it possible to build a lower cost measurement system. Since EOG is a non-stationary signal, time frequency analysis is most suitable. Hence wavelet analysis is most suitable. The wavelet transform has its application to characterizing transient events, eliminating noise, data compression and many others. In addition that biomedical signals are very small in amplitude, they are in danger of added noise. Noise elimination and amplification is done in the hardware designed. However, after the signal reaches the computer, it can still contain noise. Another way to solve the noise problem is to use the filters provided with LabVIEW. LabVIEW offers the choice of Butterworth, Bessel, Chebyshev and digital filters. With a few adjustments these filters can be configured for almost any design that is needed.
Hardware Design -Design of the EOG amplifier
The EOG signal has a frequency range between DC and 30Hz and amplitude between 10 to 100microvolts. The hardware circuit designed should have isolation from the subject, an instrumentation amplifier, band pass filter (0.05-30Hz), amplifier, notch filter to eliminate power line frequency of 50Hz.Amplifiers increase the strength of the signal while retaining high fidelity. The bio potential amplifiers must satisfy the basic requirements [6]. These amplifiers must have high input impedance in order to minimize the loading effect, should include isolation and protection circuitry and the common mode rejection ratio should be high to minimize interference due to the common-mode signal. Isolation and protection circuit, preamplifier, driver amplifier, filters are the required parts of the hardware designed. The preamplifier stage performs the initial amplification of the EOG. This stage should have very high input impedance and a high common-mode-rejection ratio (CMRR). Driver amplifiers amplify the EOG to a level at which it can be recorded on the recorder. This stage also carries out the band pass filtering of the electrocardiograph to give the frequency characteristics of the signal. The block diagram of the complete system developed is shown in figure 3.
Figure 3. Block diagram of the overall system
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