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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Grubov, Vadim Frolov, Nikita Pitsik, Elena Badarin, Artem Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

Experimental design for recording of EEG and fNIRS during performance of real and imaginary movement was proposed. Set of experiments was conducted in accordance with this design and obtained EEG and fNIRS dataset was analyzed. Analysis allowed to introduce certain features in time- frequency domain that can be used to separate real motor activity from imaginary. © 2019 IEEE.

关键词： Frequency domain analysis

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The activity of the brain cortical network during solving tasks

The activity of the brain cortical network during solving ta...

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Artem Badarin Vadim Grubov Vladimir Maksimenko Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728172866

ISBN: (纸本)9781728172873

In this paper, we analyze the functional connectivity between changes in the concentration of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin, recorded by various leads of fNIRS from the frontal and parietal cortex. The obtained coefficients characterizing the functional connectivity between a pair of leads were presented in the form of a matrix. We analyzed the changes in functional connectivity during the performance of the subject of simple cognitive tasks associated with spatial perception.

关键词： Photonics Correlation Task analysis Neuroscience Optics Robots Brain

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Recurrence plot structure of motor-related human EEG 3

Recurrence plot structure of motor-related human EEG

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Pitsik, Elena Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

In present paper we consider structure of recurrence plot (RP) of human motor-related electroencephalography (EEG) signal recorded in somatosensory cortex and filtered in mu-band (8-13 Hz). We show that in averaged EEG signal background activity is mostly characterized by the diagonal lines, while motor task execution is associated with increase of recurrence points density and the emergence of vertical and horizontal lines. We also demonstrate that these features of RP structure also observed in single EEG trials. © 2019 IEEE.

关键词： Electroencephalography

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Approaches for the Improvement of Motor-Related Patterns Classification in EEG Signals 3

Approaches for the Improvement of Motor-Related Patterns Cla...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kurkin, Semen Maksimenko, Vladimir Pitsik, Elena Neuroscience and Cognitive Techology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

We apply artificial neural network (ANN) for recognition and classification of electroencephalographic (EEG) patterns associated with motor imagery for untrained subjects. Classification accuracy is optimized by reducing complexity of input experimental data. For multichannel EEG recorded by the set of 31 electrodes, we select an appropriate type of ANN which reaches 80±10% accuracy for single trial classification. We analyze the time-frequency structure of EEG signals and find that motor-related features associated with left- and right-leg motor imagery, are more pronounced in the mu (8-13 Hz) and delta (1-5 Hz) brainwaves. Based on the obtained results, we propose the optimization approach by pre-processing the EEG signals with a low-pass filter with different cutoffs. We demonstrate that the filtration of high-frequency spectral components significantly enhances the classification performance: up to 90±5% using 8 electrodes only. © 2019 IEEE.

关键词： Neural networks

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Noise amplification precedes extreme epileptic events on human EEG

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Physical Review E 2021年第2期103卷 022310-022310页

作者： Oleg E. Karpov Vadim V. Grubov Vladimir A. Maksimenko Nikita Utaschev Viachaslav E. Semerikov Denis A. Andrikov Alexander E. Hramov National Medical and Surgical Center named after N. I. Pirogov Ministry of Healthcare of the Russian Federation 105203 Moscow Russia Research and Production Company “Immersmed” Moscow 105203 Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University 420500 Kazan Russia

Extreme events are rare and sudden abnormal deviations of the system's behavior from a typical state. Statistical analysis reveals that if the time series contains extreme events, its distribution has a heavy tail. In dynamical systems, extreme events often occur due to developing instability preceded by noise amplification. Here, we apply this theory to analyze generalized epileptic seizures in the human brain. First, we demonstrate that the time series of electroencephalogram (EEG) spectral power in a frequency band of 1–5 Hz obeys a heavy-tailed distribution, confirming the presence of extreme events. Second, we report that noise on EEG signals gradually increases before the seizure onset. Thus, we hypothesize that generalized epileptic seizures in humans are the extreme events emerging from instability accompanied by preictal noise amplification similar to other dynamical systems.

关键词： Epilepsy Neuronal dynamics Brain network Extreme event statistics

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LMI-Based Design of Output Robust Controller with Static Anti-Windup*

LMI-Based Design of Output Robust Controller with Static Ant...

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Mikhail A. Kakanov Oleg I. Borisov Anton A. Pyrkin Faculty of Control Systems and Robotics St. Petersburg Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

The article discusses the development of a robust algorithm for controlling the system output in the presence of restrictions on the input signals. The nominal controller contains an integral component to compensate for the external disturbance. Undesired effects of saturation of the input signals are compensated by the static anti-windup correction sheme. An approach is proposed for adjusting the coefficient of anti-windup correction based on the tools of linear matrix inequalities. The effectiveness of the proposed approach is illustrated by the example of an autopilot system by surface vessel.

关键词： Interference Tools Linear matrix inequalities Robots

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Energy-Efficiency in Legged Robots Locomotion: Open versus Closed Chains*

Energy-Efficiency in Legged Robots Locomotion: Open versus C...

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Roman A. Zashchitin Ivan I. Borisov Olga V. Borisova Sergey A. Kolyubin ITMO University Saint Petersburg Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

Quadrupedal gallop is one of the fastest and efficient forms of locomotion that can be found in nature. Engineers in the field of robotics use it as a source of inspiration to create legged robots. The most common model to describe galloping is the spring-loaded inverted pendulum, representing the body as a mass, while legs perform a spring-like bouncing movement. There are many design choices to implement a robotic system to get desirable bouncing dynamics. This paper compares two opposite ways to design a hopping robot in terms of energy-efficiency: algorithmically with an open chain or mechanically with a closed chain. The first way takes a relatively simple serial kinematic chain and, via impedance control algorithms, perform passive dynamic interaction with the ground. The second way takes SLIP-synthesized underactuated mechanism and via simple position and velocity control perform the same passive dynamic interaction with the ground. The paper contains a detailed description of the hoppers, analysis, and simulation results.

关键词： Legged locomotion Heuristic algorithms Kinematics Energy efficiency Impedance Springs Robots

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Analysis of EEG spectral amplitudes during ambiguous information processing

Analysis of EEG spectral amplitudes during ambiguous informa...

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Alexander Kuc Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Republic of Tatarstan Russia

We analyzed the dynamics of EEG spectral amplitudes in α- and β-frequency bands during ambiguous visual stimuli processing. As a result, we described differences in the cortical activity during the processing of vis... 详细信息

ISBN: (数字)9781728172866

ISBN: (纸本)9781728172873

关键词： Electroencephalography Visualization Analysis of variance Information processing Neuroscience Wavelet analysis Time-frequency analysis

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Recurrence plot analysis of functional brain connectivity during bistable visual perception 3

Recurrence plot analysis of functional brain connectivity du...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Miftahova, Amina R. Hramov, Alexander E. Innopolis University Innopolis420500 Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis420500 Russia

ISBN: (纸本)9781728124704

To develop fully-featured brain-computer interfaces it is crucial to study the behaviour of the brain in ambiguous situations. In this study, we analyzed the EEG data recorded during the perception of the bistable image - Necker's cube with the varying intensity of the lines. The image was demonstrated to the test person for one second and the person was asked to decide whether the cube is right-oriented or left-oriented and to push the corresponding data. During these actions the brain activity was recorded using 31-channel EEG, electrodes were placed according to the 10-20 system. The analysis, which was performed with the application of joint recurrence plots, suggests the existence of the synchronization between the channels of the frontal and occipital lobes. We believe that more rigorous research could reveal statistically significant brain connections and their dependence on physiological factors. Besides, this study may be significant for the development of the self-learning adaptive control systems. © 2019 IEEE.

关键词： Brain

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Tracking Output Robust Control of Unmanned Surface Vessel with Disturbance Cancellation and Anti-Windup

Tracking Output Robust Control of Unmanned Surface Vessel wi...

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Mediterranean Conference on Control and Automation (MED)

作者： Mikhail A. Kakanov Fatimat B. Karashaeva Oleg I. Borisov Anton A. Pyrkin Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728157429

ISBN: (纸本)9781728157436

This paper shows an explicit application example of the robust output high-gain control framework augmented with the internal model and back-calculation anti-windup technique. The application in question concerns station-keeping and tracking of an unmanned surface vessel modeled as MIMO systems with cross-couplings. The framework is illustrated by a set of simulation runs under different conditions.

关键词： Observers Monitoring Task analysis Surface waves Robots Oscillators Robust control

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