dio Engineering University. E-mail: belka-gjs@yandex.ru S.A. Gaulle Ph.D. (Eng.), Associate Professor, Department of Information-Measuring and Biomedical Engineering, Ryazan State Radio Engineering University. E-mail: likvon@list.ru E.A. Zakharova Post-graduate Student, Department of Information-Measuring and Biomedical Engineering, Ryazan State Ra-dio Engineering University E-mail: white_ange@mail.r

The field of magnetic resonance imaging and magnetic therapy is developed rapidly today. But the use of diagnostic equipment together with magnetic equipments is complicated by the fact that the magnetic field, is an obstacle when measuring bioelectric signals. The situation is complicated by the fact that noise has complex structure and high intensity. Thus electrocardiosignal (ECS), which allows to estimatethe patient\'s condition at the time of magnetic therapy, is almost unavailable. Reducing the noise in the receive signals may be possible if its channel penetration has been identifying. The article marked two approaches for solving this problem. Both paths are based on a priori known configuration of the magnetic field in a therapeuticequipment, predetermined by current-time dependencies for each inductor. The first approach is based on obtaining an estimate of the useful signal as an adaptive filtering error, where the input of the adaptive filter is priori known signal of sum equipment inductorscurrent, as the target - the sum of signal noise and the ECS. The second approach is based on the strategy, known as the estimation of receding horizon. The article details the first approach. The structure of the hardware of the electrocardiograph, invariant to the complex jamming environment is described and programming model for complex noise filtering, distorting ECS during the magnetic therapy session is built.

 

1. Vinogradov A.L., Globin V.I., Gol S.A.,Savelev V.JU., Ustinov K.S. Tekhnicheskoe obespechenie issledovanijj vlijanija geomagnitnogo polja na bioobekty // Biomedicinskaja radioehlektronika. 2008. № 7. S. 67-73.
2. Glazunova JU.S., Gol S.A., Zakharova E.A. Adaptivnaja filtracija ehlektrokardiosignala v realnom vremeni pri magnitoterapevticheskom vozdejjstvii  na  pacienta // Vestnik Rjazanskogo gosudarstvennogo radiotekhnicheskogo universiteta. 2014. № 4. S. 26-31.
3. Medvedev V.S., Potemkin V.G. Nejjronnye seti. MATLAB 6. M.: DIALOG-MIFI. 2002. 496 s.
4. Barns Dzh.EHlektronnoe konstruirovanie: Metody borby s pomekhami. M.: Mir. 1990. 238 s.
5. Uidrou B., Stirnz S. Adaptivnaja obrabotka signalov. M.: Radioisvjaz. 1989. 440 s.