| Summary: | Specific features of oculomotor signal and availability of high-end measurement equipment, as well as using modern IT techniques and tools creates the possibility of automatic processing of this type of data and extensive use of developed algorithms. Analysis of such data is a tedious and complex process so computer processing of the oculomotor signal makes the process less time-consuming, more precise and effective. The article discusses data filtering and removing noise, detection of saccades and fixations and determination of characteristic oculomotor parameters and then analysis using neural networks (unidirectional, two-layer neural network with backpropagation learning method and Kohonen’s self-organising network) and application supporting the analysis process. The proposed test method allows registration of a view path followed by its automatic analysis to obtain objective parameters characterising the movement of the eyeball. The motor apparatus of the eyeball, due to its high sensitivity to changes in the body, can serve as a measure of general health.
|
|---|
