Ya.A. Turovskiy - Ph.D.(Med.), Associate Professor, Digital Technologies Department, Head of the Digital Medical Technologies Laboratory of Computer Science Faculty, Voronezh State University S.D.Kurgalin - Dr.Sc.(Phys.-Math.), Head of the Digital Technologies Department of Computer Science Faculty, Voronezh State University S.V.Borzunov - Ph.D.( Phys.-Math.), Associate Professor, Digital Technologies Department of Computer Science Faculty, Voronezh State University

In this paper we provide a modelling of BCI implementing on hybrid human-machine intellect, based on a bionic principle. We consider terms of replacement for some part of commands, which are given by a human being to effector devices (remote-controlled self-propelled and flying platforms, robot manipulators, graphical interfaces and operating systems, etc.) with commands given to these devices by software and hardware of BCI. The given approach modells a process of controlling various devices by a human brain, when commands formed by mind are not specified, while detailed control of muscle tone, activity of muscle fibers, muscle synchronization, maintaining posture and balance during movement are controlled by structures of the brain that are not directly related to consciousness. With regard to the NCI, this means that only a small number of commands carrying purposeful information is generated by human, and the remaining commands are formed by software and hardware elements of BCI. A model offered for describing the total time spent by BCI on creation of such hybrid chains of commands. The model takes into account the number of commands, peculiarities of ways of selection the desired command, the probability of error in detection the command with operating interface and the required accuracy of its opera-tion. Dependencies are determined for assessing the efficiency of hybridization of the interface in the form of a result - increase of the speed of the BCI at different proportion of commands generated by the software and hardware of the BCI. Demonstrated that the most significant predictors for estimation of the speed of the hybrid BCI operation are parameters of time of formation and execution of commands by human, change in error detection of a command depending on the number of branches in the tree of commands, the number of branches and the index of hybridization, which reflects the proportion of number of commands generated by the human in the total number of commands in a S-chain. It is shown that within the considered structure of BCI the modal gain in time of the interface operation can make the value of ≈ 50%. Factors affecting the absolute, measured in seconds, values of gain in the BCI operation are duration of commands formed by human, and pecularities of change in error detection of commands when the number of branches in the command structure of BCI changes. In this case, the number of available commands within the investigated range of their transmission through the BCI is not significant for the speed of the hybrid interface. At the same time, to determine the parameters of hybridization, with help of which the reduction of implementa-tion time for S-chains is the least, this figure represents a prognostic value. In assessing the relative efficiency of hybridization BCI, the time taken by a human to generate a command is not sufficiently powerful predictor in estimating the rate of speed for engineered interface. A much greater role is played here by the number of commands in the S-chains, formed both by human and the hardware and software part of BCI. The obtained results allow us to significantly enhance the ability of designing and creating a new generation of BCI that widely use current capabilities of robotics, image processing and automatic navigation, which, in its turn, sig-nificantly raises the speed of operation for the given group of interfaces and makes them easier for end users.

 

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