L.A. Shimchenko – Student, Department “Medical and Technical Information Technologies”, 

Bauman Moscow State Technical University

E-mail: linashimchenko@gmail.com 

A.N. Dmitriev – Assistant, Department “Medical and Technical Information Technologies”, 

Bauman Moscow State Technical University 

E-mail: dmitalexnic@gmail.com

In clinical practice, in the study of visual evoked potentials (VEP), in order to make a diagnosis, it is necessary to focus not only on the amplitude and latency, but also on the signal shape, which is assessed only visually. Therefore, the development of an algorithm for quantifying the waveform is an urgent task. This algorithm will help to identify the components of the VEP signal.

Objective – Development and selection of the parameters of an algorithm that allows to quantify the shape of the VEP signal.

The most suitable wavelet for quantifying the VEP signal shape was shown by cmorwavf (the imaginary part of the complex Morlet wavelet). When evaluating each of the signal components, it was shown that the peaks N145 and P100 were identified. Therefore, the presented algorithm makes it possible to identify individual components of the VEP and quantify the similarity of the VEP signal with the selected comparison template. When we use flash-stimulation, the VEP components are not so stable, which doesn’t allow identification using the considered templates.

The developed algorithm will make it possible to quantitatively evaluate the signal shape, which will help in clinical practice in the diagnosis of multiple sclerosis. The results obtained indicate the possibility of using this algorithm for visual evoked potentials based on reversible chess pattern method.

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