The architecture of rehabilitation systems with biological feedback

Abstract

Non-invasiveness, non-toxicity, reliability, and efficiency make the systems with biological feedback (BF) the most promising for improvement. The structures of the vast majority of BF-systems have been studied and the most advanced one has been proposed. The technical essence of the BF-method lies in the computer registration of certain physiological indicators that are not available for direct human perception and their transformation into a form understandable to people. Since all systems of the human organism are directly subject to the constant influ-ence of the central nervous system, the most promising type of BF is neurobiocontrol of self-learning of your own brain. The general BCI (Brain-Computer-Interface) scheme contains an encephalograph whose inputs are connected to the patient's scalp and the outputs – to a comput-er connected to a controlled device. Using AI, BCI options are greatly expanded to include cur-sor control, auditory sensations, limb control, spelling devices, somatic sensations, and visual prostheses. The National Center for Adaptive Neurotechnologies has developed the BCI200 software system for fundamental and clinical neurophysiological studies of brain-computer in-teraction. As a result, all existing implementations and applications of BF-based systems for medical rehabilitation do not meet modern trends of creating unified, portable and safe new generation rehabilitation systems which can be used not only in medical institutions but also at home. To cardinally solve this problem, a new structure of the hardware and software complex for the implementation of the advanced BF-method of rehabilitation of people with disabilities has been suggested. The improved BF-procedure consists of three steps: entering and accumu-lating knowledge in the rehabilitation field, setting personal rehabilitation goals, and searching for a solution to these goals.