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Kinesthetic and visual modes of imaginary movement: MEG studies for BCI development 3

Kinesthetic and visual modes of imaginary movement: MEG stud...

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

作者： Hramov, Alexander E. Pisarchik, Alexander N. Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Biomedical Technology Technical University of Madrid Madrid Spain

ISBN: (纸本)9781728124704

The study of neurophysiological mechanisms responsible for motor imagery is important for the development of brain-computer interfaces (BCI). Here we analyze the results of magnetoencephalographic (MEG) experiments which confirm the existence of two types of motor imagery, kinesthetic and visual imagery, distinguished by activation and inhibition of different brain areas in motor-related alpha (8-12 Hz) and beta (15-30 HZ) frequency ranges. Kinesthetic imagery implies muscular sensation when performing an imaginary moving action that leads to event-related desynchronization (ERD) of motor-associated brain rhythms. By contrast, visual imagery refers to visualization of the corresponding action that results in event-related synchronization (ERS) of alpha/beta activity. A main difference between kinesthetic and visual modes occurs in the frontal brain area. The analysis of evoked responses shows that in all kinesthetic imagery subjects the activity in the frontal cortex is suppressed during motor imagery, while in the visual imagery subjects the frontal cortex is always active. The accuracy in classification of left- and right-arm motor imagery using artificial intelligence methods is similar for kinesthetic and visual imagery modes. The possibility to increase the accuracy for visual imagery is in demand for BCIs. © 2019 IEEE.

关键词： Brain computer interface

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Machine learning approaches for classification of imaginary movement type by MEG data for neurorehabilitation 3

Machine learning approaches for classification of imaginary ...

引用

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

作者： Kurkin, Semen Chholak, Parth Maksimenko, Vladimir Pisarchik, Alexander Neuroscience and Cognitive Techology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Biomedical Technology Technical University of Madrid Madrid Spain

ISBN: (纸本)9781728124704

The conducted magnetoencephalographic (MEG) experiments with voluntary participants confirm the existence of two types of motor imagery, kinesthetic imagery (KI) and visual imagery (VI), distinguished by activation and inhibition of different brain areas. Similar to real movement, KI implies muscular sensation when performing an imaginary moving action that leads to event-related desynchronization (ERD) of motor-associated brain rhythms. By contrast, VI refers to visualization of the corresponding action that results in event-related synchronization (ERS) of α- and β-wave activity. A notable difference between KI and VI groups occurs in the frontal brain area. The application of artificial neural networks allows us to classify MI in raising right and left arms with average accuracy of 70% for both KI and VI using appropriate filtration of input signals. © 2019 IEEE.

关键词： Neural networks

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Effect of the fatigue in the equilibrium training

Effect of the fatigue in the equilibrium training

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Saratov Fall Meeting 2021: Computational Biophysics and Nanobiophotonics

作者： Khorev, Vladimir S. Neuroscience and Cognitive Technology Lab. Center for Technologies in Robotics and Mechatronics Components Innopolis University 1 Universitetskaya Str. Innopolis 420500 Russia

ISBN: (数字)9781510653702

ISBN: (纸本)9781510653696

Maintaining an equilibrium of the human body in an upright position is crucial for the majority of motor activities. Numerous studies of physiologists, clinicians, scientific researchers show that the equilibrium function is very complex. In this work, we conducted an experiment involving equilibrium maintaining on a balance board to research different aspects of this process. The purpose of this study was to assess the dynamics of the movement of the platform movement associated with the equilibrium during the experiment and how muscle fatigue effects it. With the help of the statistical analysis we determine which muscles were affected by the fatigue more. © 2022 SPIE.

关键词： Signal analysis

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Transformation of the Theta-band Functional Connectivity during Motor Initiation under Healthy Aging 4

Transformation of the Theta-band Functional Connectivity dur...

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4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2020

作者： Frolov, Nikita Pitsik, Elena Schukovskii, Nikolaj Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Saratov State Medical University Saratov Russia

ISBN: (纸本)9781728172866

Human brain functioning is strongly affected by the factor of age, which crucially reduces a performance of the motor system. It causes a decline in reaction time, degraded ability to execute and control complex motor actions, low flexibility in learning new skills. A reduced daily activity old people combined with a cognitive and motor decline, usually result in a developed ambidexterity, i.e., the loss of a dominant limb advances. We suggest that such weakening of a dominant limb abilities and functioning on the neuronal level should be observed not only during the exact motor execution phase, but also in the motor initiation. In this paper we apply functional connectivity analysis to reveal the age-related changes in the integrative brain dynamic during the motor initiation before the dominant hand movements accompanied. Analyzing the whole-scalp electroencephalography (EEG) signals on the sensor level, we find higher theta-band coupling in the ipsilateral hemisphere. © 2020 IEEE.

关键词： Electroencephalography

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Design and control for the underwater robot with internal rotor

Design and control for the underwater robot with internal ro...

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2021 International Conference "Nonlinearity, Information and robotics", NIR 2021

作者： Klekovkin, Anton V. Karavaev, Yury L. Mamaev, Ivan S. Technical University Kalashnikov Izhevsk State Department of Mechatronic Systems Izhevsk Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781665424066

This paper describes the design of the underwater robot which is moved by rotating the internal rotor. The design of the robot is described. A finite-dimensional mathematical model describing the robot's motion is presented. The study of the derived equations of motion is carried out, the influence of the parameters of the control action on the mode of the robot motion is considered. © 2021 IEEE.

关键词： Equations of motion

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Classification of external signal by spiking neural network of bistable Hodgkin-Huxley neurons 4

Classification of external signal by spiking neural network ...

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4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2020

作者： Andreev, Andrey Pisarchik, Alexander Innopolis University Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis Russia Center for Biomedical Technology Technical University of Madrid Madrid Spain

ISBN: (纸本)9781728172866

We propose a classifier consisting of Hodgkin-Huxley neurons based on the activation of a different number of neurons depending on the external current amplitude. We consider a network with 2 output neurons and train the classifier for 2 external current pulses with different amplitudes by adaptation of the couplings between neurons of the main network and the output neurons. © 2020 IEEE.

关键词： Neural networks

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Continuous learning with random memory for object detection in robotic applications

Continuous learning with random memory for object detection ...

引用

2021 International Conference "Nonlinearity, Information and robotics", NIR 2021

作者： Nenakhov, Ivan Mazhitov, Ruslan Artemov, Kirill Zabihifar, SeyedHassan Semochkin, Aleksandr Kolyubin, Sergey ITMO University Biomechatronics and Energy-Efficient Robotics Lab St. Petersburg Russia PJSC Sberbank Sber Robotics Laboratory Moscow Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (纸本)9781665424066

If the robot is to interact with environment designed for humans it has to be able to cope with new objects in it's surrounding, and not only to classify but also effectively localize objects in its reach based on visual sensing. We cannot predict all objects the robot will face. So it needs to learn them while operating, without an external update of software. One of the promising approaches to handle this task is using detectors based on convolution neural networks (CNN) with continuous learning setup. However, there is a well-known problem of catastrophic forgetting (CF) that negatively affects accuracy of neural networks, the main algorithms in object recognition nowadays. Moreover, we need to reach a trade off between training time (because it is unacceptable if the robot trains for hours) and good acccuracy of detection. In this paper we review some of the latest approaches in the field and adapt one of SOtA methods in classification task to detection task. Particularly, we adapt YOLOv5 to work in scenario with continuous learning by adding random memory mechanism from [1] and applying layer freezing in order to increase training speed. We benchmark the proposed method using iCubWorld Transformations dataset and report results with significantly improved metrics and inference speed. © 2021 IEEE.

关键词： Object detection

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Mathematical Modeling of Changes in Geometric Parameters of Pneumatic Muscles 3

Mathematical Modeling of Changes in Geometric Parameters of ...

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

作者： Galushko, Ilya D. Makaryants, Georgy M. Gafurov, Salimzhan A. Department of Automatic Systems of Power Plants Samara National Research University Samara Russia Center for Technologies of Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

Today, this type of actuators as pneumatic muscles has wide application. Pneumatic muscle is a one-way actuator and has such advantages as the developed force, as well as speed. Pneumatic muscles, compared to pneumatic cylinders, have a non-linear structure that needs to be correctly identified. In this paper, we study the dynamic processes of pressure change in the working cavity of a pneumatic muscle in order to build a mathematical model, which can later be used to develop control systems, where the main actuator is pneumatic muscle. As well as in order to accurately describe and predict the geometric parameters of pneumatic muscles on pressure of compressed air in the working cavity. © 2019 IEEE.

关键词： Compressed air

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Chaos and hyperchaos in a chain of coupled Rydberg atoms 3

Chaos and hyperchaos in a chain of coupled Rydberg atoms

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

作者： Balanov, Alexander Andreev, Andrey Department of Physics Loughborough University Loughborough United Kingdom Neuroscience and Cognivite Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

Partially quantum coherent arrays of artificial atoms (e.g., superconducting qubits) may be used as analogue simulators of other quantum systems, when the behaviour of the latter cannot be directly observed or modeled by classical means. Here we show that a chain of superconducting qubits can simulate the chaotic behaviour predicted in chains of Rydberg atoms. We investigate the transition from periodic to chaotic dynamics and show the increase of the number of positive Lyapunov exponents as the number of atoms grows. The possibility of an external control and suppression of hyperchaos in the chain is demonstrated. © 2019 IEEE.

关键词： Lyapunov methods

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Analysis of muscle activation patterns during equilibrium seeking activity

Analysis of muscle activation patterns during equilibrium se...

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

作者： Khorev, Vladimir S. Grubov, Vadim V. Badarin, Artem A. Kurkin, Semen A. Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University 1 Universitetskaya Str Innopolis420500 Russia

ISBN: (数字)9781510645332

ISBN: (纸本)9781510645325

The main goal of this project was to identify the patterns of muscular activity of a person in the process of his interaction with the environment, as well as to identify mechanisms that make it possible to adapt behavior in response to changing external conditions. For this, we conducted a series of experiments with subjects placed in an unstable state. We carried out statistical analysis for the received signals of muscle activity. Based on the results of the analysis of behavioral characteristics, we revealed positive dynamics when subjects were reaching a state of balance and a pattern associated with training. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Signal analysis

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