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2020 International Conference Nonlinearity, Information and robotics, NIR 2020

作者： Grubov, Vadim Maksimenko, Vladimir Kurkin, Semen Khramova, Marina Aleksandrova, Natalya Hramov, Alexander Center for Technologies in Robotics and Mechatronics Components Innopolis University Neuroscience and Cognitive Technology Lab Russia Saratov State University Faculty of Computer Science Saratov Russia

ISBN: (纸本)9781728187631

We have analyzed EEG signals of children during cognitive load of specific type in order to estimate level of attention during this task. EEG signals were recorded in accordance with proposed design of experiment. For obtained EEG data we have analyzed behavioral characteristics as well as EEG-related characteristics. We have found that behavioural characteristic changes through the task, so may the attention level. We have also found that cognitive task completion is accompanied by appearance of spatial structure-specific distribution of wavelet energy across cortex, which partially changes during completion of the task as well. We believe that changes in attention level are tied to changes in energy distribution, so we suggest this distribution to be used as the marker for attention state estimation. © 2020 IEEE.

关键词： Electroencephalography

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Ground and non-ground separation filter for UAV Lidar point cloud

arXiv

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arXiv 2019年

作者： Prathap, Geesara Fedorenko, Roman Klimchik, Alexandr Center for Technologies in Robotics and Mechatronics Components Innopolis University

This paper proposes a novel approach for separating ground plane and non-ground objects on Lidar 3D point cloud as a filter. It is specially designed for real-time applications on unmanned aerial vehicles and works on sparse Lidar point clouds without preliminary mapping. We use this filter as a crucial component of fast obstacle avoidance system for agriculture drone operating at low altitude. As the first step, a point cloud is transformed into a depth image and then places with high density nearest to the vehicle (local maxima) are identified. Then we merge original depth image with identified locations after maximizing intensities of pixels in which local maxima were found. Next step is to calculate range angle image which represents angles between two consecutive laser beams based on improved depth image. Once a range angle image is constructed, smoothing is applied to reduce the noise. Finally, we find out connected components in the improved depth image while incorporating smoothed range angle image. This allows separating the non-ground objects. The rest of the locations of depth image belong to the ground plane. The filter has been tested on a simulated environment as well as an actual drone and provides real-time performance. We make our source code and dataset available online2. Copyright © 2019, The Authors. All rights reserved.

关键词： Optical radar

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Stabilization of a spherical robot rolling on an oscillating underlying surface

Stabilization of a spherical robot rolling on an oscillating...

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2020 International Conference Nonlinearity, Information and robotics, NIR 2020

作者： Karavaev, Yury Kilin, Alexander Klekovkin, Anton Pivovarova, Elena Kalaschnikov Izhevsk State Technical University Department of Mechatronics Systems Izhevsk Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia Udmurt State University Department of Theoretical Physics Izhevsk Russia

ISBN: (纸本)9781728187631

This paper is devoted to investigations of a spherical robot rolling on an oscillating underlying surface. The model of spherical robot of combined type is considered. Based on analysis of equations of motion taking into account the oscillation of the underlying surface, a control algorithm for stabilization of the spherical robot is proposed. The influences of oscillations in horizontal and vertical directions are evaluated. The design of the spherical robot and its control system for fabrication of a prototype are described. © 2020 IEEE.

关键词： Feedback

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Biomarkers of brain activity for the performance evaluation in the process of solving cognitive tasks 5

Biomarkers of brain activity for the performance evaluation ...

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Badarin, Artem Smirnov, Nikita Kurkin, Semen Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia

ISBN: (纸本)9781665442824

In this paper, we analyze the brain activity during the execution by the subject of simple cognitive tasks associated with visual attention and symbol perception. We obtain biomarkers of brain activity in the process of solving cognitive tasks. These biomarkers make it possible to relate the quality and speed of execution of the tasks offered to the subject with the brain’s activity of the cortical network. We use a combination of time-frequency and statistical analysis to calculate activity characteristics. The results obtained can be used to develop neural interfaces for training attention and adjusting the learning process. © 2021 IEEE

关键词： Biomarkers

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How Long short-term memory artificial neural network, synthetic data, and fine-tuning improve the classification of raw EEG data 6

How Long short-term memory artificial neural network, synthe...

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6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022

作者： Nasybullin, Albert Maksimenko, Vladimir Kurkin, Semen Innopolis University Laboratory of Data Analysis and Bioinformatics Center for Artificial Intelligence Innopolis Russia Innopolis University Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (数字)9781665461740

ISBN: (纸本)9781665461740

In this paper, we discuss a Machine Learning pipeline for the classification of EEG data. We propose a combination of synthetic data generation, long short-term memory artificial neural network (LSTM), and fine-tuning to solve classification problems for experiments with implicit visual stimuli, such as the Necker cube with different levels of ambiguity. The developed approach increased the quality of the classification model of raw EEG data. © 2022 IEEE.

关键词： Classification (of information)

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Effect of prehistory on the ambiguous stimuli processing in the human brain 5

Effect of prehistory on the ambiguous stimuli processing in ...

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Kuc, Alexander Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia

ISBN: (纸本)9781665442824

To model the picture of the external environment, the brain uses data coming from the sensory system. However, it is believed that the brain’s representation of the external environment is formed not only by sensory information, but also by a priori knowledge, the so-called predictions. This work considers how the previous sensory information (sensory prehistory) influences the processing of the current visual stimuli. Bistable images of the Necker cube with varying degrees of ambiguity were used as visual stimuli. We found EEG biomarkers possibly reflecting the effect of prehistory on the brain state and the ongoing stimulus processing. © 2021 IEEE

关键词： Visualization Complex networks Biomarkers Brain modeling Electroencephalography Data models Time factors

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Phase-amplitude coupling between mu- and gamma-waves to carry motor commands 3

Phase-amplitude coupling between mu- and gamma-waves to carr...

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

作者： Chholak, Parth Pisarchik, Alexander N. Kurkin, Semen A. Maksimenko, Vladimir A. Hramov, Alexander E. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

The development of brain computer interfaces, especially the ones related to controlling exoskeletons and neurorehabilitation of stroke patients, strongly relies on our understanding of motor system and its neuronal mechanism. Motor imagery (MI) has turned out to be one of the most popular experimental regimes to study this system. Kinesthetic imagery (KI) is a kind of MI which shares a large portion of its neuronal pathway with real movements, except for having an additional inhibitory mechanism to prevent movement execution. Our magnetoencephalographic (MEG) experiments with ten untrained subjects revealed that this inhibitory control implied local neuronal desynchronization. We found that the motor-related communication between the inferior parietal cortex and the prefrontal cortex was carried out using the mu-frequency range. Additionally, three gamma frequencies were also pinpointed that encode the motor command specifics. Using artificial neural networks (ANNs) we classified left- and right-hand MI which reached maximal accuracy when we included these three gamma frequencies in the input signal for ANN. We suggest that mu-activity acts as a carrier of gamma-activity between inferior and parietal areas utilising phase-amplitude coupling. © 2019 IEEE.

关键词： Neural networks

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Quasi-movements as an intermediate type of motion 5

Quasi-movements as an intermediate type of motion

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Smirnov, Nikita M. Kurkin, Semen Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia

ISBN: (纸本)9781665442824

This paper discusses the three distinct types of motor activity, namely quasi, real, and imagery. Quasi-motion is voluntary movements that are minimized to the point that finally become undetectable by objective measures. This type of motion is particular from the point of difficulty of classifying it as real or imaginary. In this paper, we are aiming to show it from the sensor- and source-level perspectives. © 2021 IEEE

关键词： Dynamics Complex networks

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Propellerless aquatic robots 23rd

Propellerless aquatic robots

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23rd International Conference on Climbing and Walking Robots and the Support technologies for Mobile Machines, CLAWAR 2020

作者： Klekovkin, Anton V. Mamaev, Ivan S. Vetchanin, Evgeny V. Tenenev, Valentin A. Karavaev, Yury L. Kalashnikov Izhevsk State Technical University Izhevsk Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Udmurt State University Izhevsk Russia

ISBN: (纸本)9781916449046

This paper is devoted to investigations of the motion of the propellerless aquatic robots. There are two models of aquatic robots under consideration that move due to rotation of internal rotors. Mathematical models to describe the motion of the robots are proposed. Experiments with different control actions for fabricated prototypes to verify mathematical models have been conducted. © CLAWAR Association Ltd.

关键词： Robots

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Synchronization in the inhibitory coupled Hodgkin-Huxley neural networks

Synchronization in the inhibitory coupled Hodgkin-Huxley neu...

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Saratov Fall Meeting 2020 - Computations and Data Analysis: From Molecular Processes to Brain Functions

作者： Andreev, Andrei V. Maksimenko, Vladimir A. Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Universitetskaya Str. 1 Innopolis420500 Russia

ISBN: (数字)9781510645332

ISBN: (纸本)9781510645325

We consider two small-world networks of Hodgkin-Huxley neurons interacting via inhibitory coupling. We found that synchronization indices (SI) in both networks oscillate periodically in time, so that time intervals of high SI alternate with time intervals of low SI. Depending on the coupling strength, the two coupled networks can be in the regime of either in-phase or anti-phase synchronization. We suppose that the inherent mechanism behind such a behavior lies in the cognitive resource redistribution between neuronal ensembles of the brain. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Synchronization

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