Vol 1, No 3 (2016)

Articles
II INTERNATIONAL RESEARCH AND PRACTICE CONFERENCE “BRAIN-MACHINE INTERFACE: SCIENCE AND PRACTICE. SAMARA - 2016”: NEW ORGANIZATIONAL APPROACHES IN NEUROSCIENCES, RESULTS OF FUNDAMENTAL AND APPLIED RESEARCHES, FORMATION OF RUSSIAN AND INTERNATIONAL RESEARCH GROUPS
Kolsanov A.V., Avdeeva E.V.
Abstract
An overview article based on the proceedings of the II International research and practice conference “Brain-machine interface: science and practice. Samara - 2016”. Principal directions of discussions in specific research areas are represented: neurophysiology and mathematic modeling, neural networks and neurocommunication, neurocomputer interfaces, neurorehabilitation technologies, virtual reality in medical and social rehabilitation. The paper also presents decisions taken upon cooperation of participants in the sphere of scientific and technological cooperation and integration of domestic and foreign innovations into the global process of the development of neurotechnologies.
Science and Innovations in Medicine. 2016;1(3):6-11
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BRAIN-COMPUTER INTERFACE FOR THE AUGMENTATION OF BRAIN FUNCTIONS
Lebedev M.A.
Abstract
Brain-computer interface (BCI) connects the nervous system departments with external devices for the purpose of recovery of motor and sensory functions of patients with neurological lesions. Over the past half-century BCI have gone from initial ideas to the high-tech modern incarnations. This development contributed significantly to the invasive techniques of multichannel registration activity of neuronal ensembles. Modern BCI are able to manage mechanical prosthetic arms and legs. Furthermore, BCI can provide sensory feedback, allowing the user to feel the movement of the prosthesis and its interaction with external objects. Latest BCI connect multiple users to the brain network. In this review, these achievements are dealt with a focus on invasive BCI.
Science and Innovations in Medicine. 2016;1(3):11-27
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RECOGNITION OF COGNITIVE POTENTIALS TO THE TARGET STIMULI IN THE BRAIN-COMPUTER INTERFACE ON THE BASIS OF THE ENSEMBLE OF CLASSIFIERS
Kirjanov D.A., Kaplan A.Y.
Abstract
Background. A number of studies have been done on detection of human visual attention focus by means of P300 brain-computer interfaces (BCI). However, the performance of interfaces on P300 is still low, since this technique requires the repeated presentation of target and non-target stimuli. There are some indications that it is appropriate to use ensembles of classifiers to improve the accuracy of recognition of multidimensional objects. The goal of the present study was to verify the feasibility of application of ensembles of classifiers to speed up the work of the BCI P300. Methods. The study involved 22 subjects, whose task was to closely monitor the highlights of target objects on the computer screen, presented as 8 triangles located in a circle (angle of 7.7 degrees). Single classifiers and ensembles of classifiers based on linear discriminant of Fisher were used to detect the target responses in the EEG. Results. The use of the ensemble of classifiers provided almost the same accuracy of algorithmic choice of target reactions, EEG in 78-80%, as compared with the use of single classifiers, but with two times smaller number of repetitions of the test stimuli and, therefore, faster detection of the target reactions of the EEG. Conclusions. This work implies that the P300 BCI with the participation of the ensemble of classifiers can be used to build high-speed communication systems for both the stroke patients and healthy people in special circumstances for additional alarm at the inability to use speech.
Science and Innovations in Medicine. 2016;1(3):28-32
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SENSORIMOTOR POTENTIATION OF MOTOR IMAGINATION AS CNS PLASTICITY ACTIVATOR
Korovina E.S., Glazkova E.N., Shirolapov I.V., Kuznetsova O.G., Khanbikov N.R., Gornyakova I.S.
Abstract
Aim - to find out the neurophysiological correlatives of motor imagery after the simulation of the motor pattern. Materials and methods. Monopolar EEG was recorded using EEG recording system Neuron - Spectrum - 4 / VPM at 7 right-handed volunteers aged 18-19 years. EEG was recorded according to the system 10-5 in the projection of the sensorimotor cortex of the left hemisphere during the imagination of two movements in the right hand (flexing the fingers, elbow flexion) before and after 30 seconds of simulation of movement patterns using the rehabilitation device Power Plate. Results. After the simulation of the motor pattern, the imagination of the two types of movement correlated with desynchronization of alpha-, beta- EEG rhythms, increasing the number of leads with the reaction of desynchronization (p<0,01) and reliable differentiation of changes in the power of sensorimotor EEG rhythms at dualtrack imaginary movements, and the accelerated learning of motor imagination. Conclusion. Sensorimotor potentiation helps to find out the neurophysiological correlatives of motor imagery.
Science and Innovations in Medicine. 2016;1(3):33-38
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INTEGRAL ALGORITHM OF P300 RECOGNITION IN EEG FOR BCI APPLICATION
Agapov S.N., Bulanov V.A., Zakharov A.V., Sergeeva M.S., Pyatin V.F.
Abstract
Aim - developing the integral algorithm of recognition of the evoked potential (ERP-response) to a target visual stimulus and testing of the proposed algorithm on the wireless 5-channel electroencephalograph Emotiv Insight with “dry” electrodes. Materials and methods. The objects of the study were the EEG records of five volunteers. Were used 5-channel wireless EEG headset Emotiv Insight, self-developed software «eSpeller», software environment MathWork® MATLAB R2015a. Results. It was found that the proposed integral algorithm of recognition of electrical activity of the cerebral cortex to a target visual stimulus shows the accuracy of the detection from 71.5% to 90.6% with the average value 80.1+7.2%, using EEG headset Emotiv Insight. Conclusion. The algorithm shows a high level of reliability of recognition of evoked potential to a target visual stimulus, does not require large computing power, sophisticated classification methods and machine learning. The testing of the algorithm suggests the possibility of using the electroencephalograph Emotiv Insight with "dry" electrodes in the development of BCI.
Science and Innovations in Medicine. 2016;1(3):39-44
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COMBINING METHODS OF FREQUENCY FILTERING AND NONLINEAR ANALYSIS FOR SOMNOLOGICAL STUDY OF EEG SIGNALS
Antipov O.I., Zakharov A.V.
Abstract
Aim - combined use of frequency and nonlinear analysis methods for obtaining hypnograms by analyzing electroencephalographic (EEG) signals during somnological studies. Methods. Frequency filtering methods were used for preliminary treatment of EEG signals before the following nonlinear analysis. As non-linear methods of analysis we used fractal methods of deterministic chaos, such as Hurst’s method of the normalized amplitude, approximate entropy method, calculation of the correlation integral by Grassberger and Procaccia’s method. For the possibility of applying the last two methods we used quasi phase space recovery method according to the Taken’s theorem. As a result of non-linear analysis we obtained hypnograms reflecting the transition between the stages of sleep in patients undergoing somnological examination. To assess the reliability of the results, they were compared to the hypnograms obtained by the classical method based on the rules of Rehchaffen and Keyls. Also the problems associated with the occurrence of various types of interference were considered and methods for reducing their influence on the final results were suggested. Results. We can conclude that using these methods with appropriate selection of the parameters, employing the necessary normalization of raw data, and averaging the results allow us to obtain hypnogram having a full match of defined phases of sleep for about half of the periods recorded by EEG. To obtain these results it is sufficient to use only one channel of EEG recording.
Science and Innovations in Medicine. 2016;1(3):45-50
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MECHANISMS OF INTERACTION BETWEEN THE CIRCADIAN SYSTEM, EEG RHYTHMS AND REGULATION OF VEGETATIVE PROCESSES
Romanhuk N.P., Tyurin N.L., Borisova O.V., Loginova L.N., Kirasirova L.A.
Abstract
Aim - to investigate the dynamics of EEG rhythms and vegetative responses in human on a short-term exposure of the retina to the blue light in the spectrum of maximum sensitivity of circadian photoreceptors during daytime wake. Materials and methods. EEG parameters (BP-010302 BrainАmp Standart128), blood pressure and heart rate variability (HRV) were recorded at 22 volunteer students aged 18-20 years before, after and during the 2-5 minute stimulation of circadian retinal receptors by blue light with maximum wavelength of 480 nm. Results. The stimulation of the photoreceptors of the circadian system correlates with the dynamics of the following neurovegetative processes: desynchronization in beta2- and gamma EEG rhythms, synchronization in teta2- and alpha1-frequency bands; increase in the duration of RR interval and power of low-frequency component of HRV, decrease in the percentage of high-frequency oscillation spectrum of HRV and decrease in systolic blood pressure. Termination of the stimulation of circadian system photoreceptors causes the transformation of EEG rhythms response with predominance of synchronization in low (teta1, teta 2), medium (alpha 1, alpha 2, alfa 3) and high frequency (beta 2) bands. Conclusion. The paper shows the possibility of quick correction of human vegetative background by controlling the circadian system. The human circadian clock is likely to control functional brain activity involving beta 2- and gamma-quantization.
Science and Innovations in Medicine. 2016;1(3):51-55
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CLINICAL EXPERIENCE OF POST-STROKE REHABILITATION WITH THE USE OF HAND EXOSKELETON CONTROLLED BY BRAIN-COMPUTER INTERFACE
Frolov A.A., Mokienko O.A., Biryukova E.V., Bobrov P.D., Lukmanov R.K., Kondur A.A., Dzhalagonya I.Z.
Abstract
Aim - to evaluate the efficiency of the motor recovery rehabilitation procedure with the use of hand exoskeleton controlled by the brain-computer interface (BCI). Materials and methods. 60 post-stroke patients participated in the study. 46 patients had ischemic stroke and 14 had hemorrhagic stroke. 42 patients of the main experimental group were trained in kinesthetic motor imagery using hand exoskeleton controlled by BCI, 18 patients of the control group carried out the imitating procedure. Exoskeleton - BCI system consists of encephalograph NVX52 («Medical Computer Systems», Russia), personal computer and hand exoskeleton («Android Technique», Russia). Motor functions were estimated by neurological scales ARAT and Fugl-Meyer. Results were statistically analyzed by Mann-Whitney, Wilcoxon and x2 tests, Spearman's correlation and RM-ANOVA using Statsoft Statistica v. 6.0. Results. It is shown that post-stroke patients are able to control BCI with the same efficiency as healthy subjects, regardless of the duration, severity and localization of the disease. Ten days of BCI training significantly improved patients’ motor functions according to neurological scales ARAT and Fugl-Meyer. Improvement was mainly provided by the small movements of the hand. According to several sections of neurological scales, improvement in the main group is significantly higher than in the control group. However, according to general scores, statistically significant difference between two groups was not observed. Conclusion. It is shown that the rehabilitation procedure using hand exsoskeleton controlled by BCI significantly improves motor functions of the paretic arm regardless of the duration, severity and localization of the disease. Increase of the training duration enhances the rehabilitation efficiency.
Science and Innovations in Medicine. 2016;1(3):56-61
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USING VIRTUAL REALITY AS A METHOD OF ACCELERATED REHABILITATION AMONG THE PATIENTS AFTER STROKE
Zakharov A.V., Pyatin V.F., Kolsanov A.V., Poverennova I.E., Segreeva M.S., Khivintseva E.V., Korovina E.S., Kucepalova G.U.
Abstract
Aim - exploring the effect of displaying the motion from the first-person’s point of view in virtual reality on the recovery of motor disorders among patients in the acute period of cerebrovascular disorder. Materials and methods. 45 patients with acute cerebrovascular disorder aged 58±7 years were analyzed. Patients were randomized in two groups. The first group received either standard rehabilitation or training with virtual reality equipment. The second group received only standard rehabilitation. Training included displaying the motion from the first-person’s point of view in the virtual reality during 3-7 sessions, 15 minutes each. In this exercise a patient could see his “virtual legs”. Speed range was 2-5 km/h. Berg’s balance assessment was used to score movement function (14 questions, where max score - 56 points - means that there is no dysfunction to notice). Assessment method for comparing groups with unusual distribution (Mann-Whitney criteria) was used as statistical analysis. Results. Exercises with the virtual reality equipment show their efficiency on 15th-19th day after stroke. The most significant outcome can be achieved in 5-9 days after stroke (p=0,022). The rate of movement function recovery depends on the duration of training (p=0,001); the highest outcome can be achieved during the first 3-5 sessions. Conclusion. Additional exercises with the virtual reality equipment help to improve outcomes of movement function recovery among patients with acute cerebrovascular disorder.
Science and Innovations in Medicine. 2016;1(3):62-66
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POSTURAL DISORDERS PROGNOSIS AMONG ELDERLY PEOPLE
Khivintseva E.V., Veselova E.D., Bogomazova C.A., Marinovskaya V.B., Petrov K.A.
Abstract
Aim - finding out the features of postural disorders among elderly people. Materials and methods. 47 patients above the age of 90 were analyzed. There were no disorders in particular functional systems to be noticed in these patients’ neurological status, although the patients complained of problems with balance function. All the patients were neurologically examined; the anamnesis data and computer stabilometry were investigated. Control group included patients of different age groups without any balance dysfunction according to computer stabilometry data. We used logistic regression to elicit connection between clinical and instrumental factors. Only significant regressors were taken into consideration. Results. The difference between the group of long-livers and the other age groups is about the modification of universal statokinesigram indicators. The suggested mathematical model included the area of statokinesigram, the speed of changing of the pressure center, Romberg’s coefficient and spectral statokinesigram parameters. Swift of the statokinesigram frequency range towards the low frequency characterizes tension or “failure” of compensatory mechanisms providing postural functions in this age group. Sensibility of this model is 95.5%, specificity is 69.5%. Conclusion. Long-living patients can be characterized as a group with a high risk of postural disorders and falls. Obtained mathematical model can be used in the daily clinical practice to verify the risk of falls among long-livers who complain of balance dysfunction.
Science and Innovations in Medicine. 2016;1(3):67-71
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DEVELOPMENT OF EYE-TRACKING BASED SYSTEMS FOR ALTERNATIVE AND AUGMENTATIVE COMMUNICATION
Balovnev D.A., Znayko G.G.
Abstract
Rehabilitation of people with communication impairments is a socially important issue in Russia. Currently, there are no high-tech alternative and augmentative communication devices on the Russian market. On creation of such devices, a need arises for a model which structures any occurring communication impairment. The article sets out the structure of an alternative model of speech production developed on the basis of Levelt’s model of speech production. Practical application of the developed model is shown in the course of designing a high-tech platform for alternative and augmentative communication.
Science and Innovations in Medicine. 2016;1(3):72-76
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DEVELOPMENT OF THE HARDWARE AND SOFTWARE COMPLEX CONTROLLING ROBOTIC DEVICES BY MEANS OF BIOELECTRIC SIGNALS OF THE BRAIN AND MUSCLES
Gordleeva S.Y., Lobov S.A., Mironov V.I., Kastalskiy I.A., Lukoyanov M.V., Krilova N.P., Mukhina I.V., Kaplan A.Y., Kazantsev V.B.
Abstract
Aim - to develop a hardware-software complex with combined command-proportional control of robotic devices based on electromyography (EMG) and electroencephalography (EEG) signals. Materials and methods. EMG and EEG signals are recorded using our original units. The system also supports a number of commercial EEG and EMG recording systems, such as NVX52 (MCS ltd, Russia), DELSYS Trigno (Delsys Inc, USA), MYO Thalmic (Thalmic Labs, Canada). Raw signals undergo preprocessing and feature extraction. Then features are fed to classifiers. The interpretation unit controls robotic devices on the base of classified EEG- and EMG-patterns and muscle effort estimation. The number of controlled devices includes mobile robot LEGO NXT Mindstorms (LEGO, Denmark), humanoid robot NAO (Aldebaran, France) and exoskeleton Ilia Muromets (UNN, Russia). Results. We have developed and tested an interface combining command and proportional control based on EMG signals. We have determined the parameters providing optimal characteristics of classification accuracy of EMG patterns, as well as the speed and accuracy of proportional control. Also we have developed and tested a BCI interface based on motor imagined patterns. Both EMG and EEG interfaces are included into hardware and software system. The system combines outputs of the interfaces and sends commands to a robotic device. Conclusion. We have developed and approved the hardware-software system on the basis of the combined command-proportional EMG and EEG control of external robotic devices.
Science and Innovations in Medicine. 2016;1(3):77-82
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ROBOTIC SYSTEMS FOR SPECIAL AND MEDICAL INTELLIGENT ASSISTANCE
Dudorov Е.А., Bogdanov А.А., Permyakov A.F.
Abstract
Exoskeletons gradually come to all spheres of human activities - from building houses to sports, from medicine to military usage. Exoskeleton complexes are rapidly developing with the help of 3D printing, microwires, new sources of energy and computing power. Russian developers are actively participating in this process, and their results keep up with the results of their foreign competitors. So these teams have a good chance to become market leaders in exoskeleton technologies for a wide range of applications. Aim. Analysis of condition and determination of the main directions of development of robotic systems for special and medical intelligent assistance. Methods. The study involved a complex of methods of designing of robotic systems and evaluation of their mechanic characteristics and managing principles, such as method of movement modeling, method of managing robotic systems based on biologically suitable principles, method of automatic interaction between robotic device and BCI, method of remote control of robotic systems etc. All these methods helped to develop the best possible models of exoskeleton robotic systems. Conclusion. The key problems of Russian developers of robotic systems for intelligent assistance are the technological dependence on foreign suppliers and a lack of qualified personnel. The most promising directions of development are the development of lower-extremity exoskeleton and specific exoskeleton complexes.
Science and Innovations in Medicine. 2016;1(3):83-88
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