Content adaptation neural network method cause-specific the state of users

The aim of the study is to develop recommendations for adapting educational content based on the use of a neural network method for recognizing the human autonomic nervous system degree of activity. The initial data for decision making are the vectors of cardiointervals obtained with the help of the pulse sensor. The state of the autonomic nervous system is monitored by a two-layer artificial neural network of direct propagation. The artificial neural network was trained by combining gradient and stochastic training method

Introducing a polypyrrole (ppy)-manganese ferrite (mnfe2o4) nanocomposite based microwave absorber for studying the effect of the radiation on the modification of the patient’s functional state

In the present work, we have implemented a project aimed at the development of a modular-type technical system designed to generate microwave radiation with specified properties. This article presented the electrophysiological efficiency of super-low intensity radiation in the centimeter range of wavelengths modulated by low-frequency signals similar to the EEG rhythm with cyclical variability of the duty cycl

БИОТЕХНИЧЕСКАЯ СИСТЕМА ГЕНЕРАЦИИ ЭЭГ-ПОДОБНЫХ СИГНАЛОВ

The Purpose – realization of the structure specialized biooperated module to generations EEG-like signal directed on personalization and reinforcement to efficiency of the treatment. In work are used methods of modeling, system technical analysis and constructing.The conclusion: Its were designed models of the formulas of the action, which provide presenting on electrodes for stimulation modulated current by means of signal of the pulse and breathings within the range of changeable frequencies 7–13–7 Hz or 14–26–14 Hz.Цель  –  реализация  структуры  специализированного  биоуправляемого  модуля  генерации  ЭЭГподобных  сигналов,  направленных  на  индивидуализацию  и  усиление  эффективности  лечения. В работе использованы методы моделирования, системотехнического анализа и конструирования. Разработаны модели формул воздействия, которые обеспечивают подачу на стимулирующие электроды модулированных токов посредством сигналов пульса и дыхания в диапазоне плавающей частоты 7–13–7 Гц или 14–26–14 Гц

РАЗРАБОТКА МОДЕЛЕЙ ОПТИМИЗАЦИИ В БИОТЕХНИЧЕСКОЙ СИСТЕМЕ ИГРОВОГО АВТОМОБИЛЬНОГО ТРЕНИНГА

The Purpose – its were developed multiparametric models and algorithms of the optimization playing training biooperated. In work are used methods of the system analysis, modeling, system technical analysis and constructing, mathematical statistics, methods of the computer analysis heart rate variability by means of sensor of the pulse and breathings.The Conclusion: its were designed two models of strategy playing, one – with installation on avoid of the failures and the second – on achievement of the success. The algorithms of the success and efficiency were formed for period of the termination of the biooperated play. Цель – разработка мультипараметрических моделей и алгоритмов оптимизации игрового биоуправляемого тренинга. В работе использованы методы системного анализа, моделирования, методы системотехнического анализа и конструирования, математической статистики, методы компьютерного ритмотестирования с помощью датчиков пульса и дыхания.Разработаны две модели игровой стратегии, одна – с установкой на избегание неудачи и вторая – на достижение успеха. Сформированы алгоритмы успешности и эффективности проведенного биоуправляемого автомобильного тренинга

An action of superlow power extremely high-frequency radiation on some microbes in vitro, human erythrocytes, and the functional status of a person

This paper is devoted to the analysis of advanced scientific research about the role of superlow intensity extremely high frequency effects on biological objects, including peopl

DEVELOPMENT OF THE MODELS TO OPTIMIZATION IN SYSTEM BIOTEHNICAL OF THE PLAYING CAR TRAINING

The Purpose – its were developed multiparametric models and algorithms of the optimization playing training biooperated. In work are used methods of the system analysis, modeling, system technical analysis and constructing, mathematical statistics, methods of the computer analysis heart rate variability by means of sensor of the pulse and breathings.The Conclusion: its were designed two models of strategy playing, one – with installation on avoid of the failures and the second – on achievement of the success. The algorithms of the success and efficiency were formed for period of the termination of the biooperated play

BIOTECHNICAL SYSTEM TO GENERATIONS EEG LIKE SIGNAL

The Purpose – realization of the structure specialized biooperated module to generations EEG-like signal directed on personalization and reinforcement to efficiency of the treatment. In work are used methods of modeling, system technical analysis and constructing.The conclusion: Its were designed models of the formulas of the action, which provide presenting on electrodes for stimulation modulated current by means of signal of the pulse and breathings within the range of changeable frequencies 7–13–7 Hz or 14–26–14 Hz

A COMPARATIVE ANALYSIS OF THE RESULTS OF CONVENTIONAL AND COMBINED METHODS OF TRAINING DIRECT PROPAGATION NEURAL NETWORK IN HEALTHY PERSONS TO DETECTING THE DEGREE OF ACTIVITY OF AN AUTONOMOUS NERVOUS SYSTEM

The article deals with a comparative analysis of the efficiency of an artificial neural network (ANN) trained with the help of algorithm back propagation, and of that trained by combining a back propagation algorithm and a variant of Cauchy stochastic training, in detecting the degree of activity of an autonomous nervous system. For the purposes realization of the project has been developed a biotechnical system, including technical device for input electrophysiological information in mode on-line. To evaluate the clinical effectiveness of the classification, records of interpulse intervals in 139 healthy students of Belgorod State University have been analyzed. All of them were part of the same age and social group from 17 to 24 years old. In practice, the ANN training algorithm using the back error propagation method enabled a correct recognition of 96.0% of the samples. The analysis of the clinical effectiveness of combining the back error propagation algorithm with Cauchy stochastic training showed that 100% samples were detected correctly both: as in training statistical samples so and in examination sampling. Classification errors amounted to 0 %. Keywords: interpulse intervals; electrophysiological information input block; neurocomputing; neural network classification algorithm; method backward propagation algorithm; Cauchy stochastic training; combined methods of training