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Features of real and imaginary human motor activity with EEG and fNIRS

Features of real and imaginary human motor activity with EEG...

引用

2020 International Conference Nonlinearity, Information and robotics, NIR 2020

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

ISBN: (纸本)9781728187631

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 motor imagery. © 2020 IEEE.

关键词： Electroencephalography

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Dynamic Object Grasping in Human-Robot Cooperation Based on Mixed-Reality

Dynamic Object Grasping in Human-Robot Cooperation Based on ...

引用

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

作者： Demian, Albert Ostanin, Mikhail Klimchik, Alexandr Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia Innopolis University Robotics and Computer Vision Institute Innopolis Russia

ISBN: (纸本)9781665424066

Static Object grasping is a challenging task that has been studied for decades. The difficulty of the task comes back to the reason that a grasping attempt can have many solutions or due to the uncertainty about the targeted object's features and characteristics. This makes the fact about dynamic object grasping with un-modeled dynamics even more challenging. In this paper, an approach for dynamic object grasping is presented. The approach considers human-robot handover operation where the robot should be able to track human's holding-object hand and plan a successful grasp of the object in hand. The system was implemented with the help of Mixed-Reality using HoloLens glasses for human's hand tracking. A serial manipulator was used to execute the operation mounted with end-effector-mounted camera to perform computer vision operations for grasp planning and correction. The main task is robot at random configuration can be able to find hand-holding object and plan grasp on object in hand. The implemented system shows success and was able to perform most of the grasping tasks successfully. © 2021 IEEE.

关键词： Mixed reality

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Upper limb exoskeleton for neurorehabilitation with control via brain-computer interface 6

Upper limb exoskeleton for neurorehabilitation with control ...

引用

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

作者： Antipov, Vladimir 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

This paper describes the results of developing control methods for an active exoskeleton for rehabilitation of human upper limb motor activity. The experimental setup, real-time software implementation of the control system, and also the developed software environment for stimulation of the subject during the neurophysiological experiment are described. The research object of the above system is the processes of activation of brain areas in terms of analysis of bioelectrical electroencephalographic signals registered during a motor activity, suitable for use in the tasks of motor rehabilitation. The purpose of this work is to develop a hardware-software part of the experiment to study real-time algorithms for control of the upper limb exoskeleton for rehabilitation and education tasks using 'brain-computer' interfaces. © 2022 IEEE.

关键词： Brain computer interface

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Explicit Model Predictive Control Design based on Constrained Zonotope Propagation 7

Explicit Model Predictive Control Design based on Constraine...

引用

7th Scientific School: Dynamics of Complex Networks and their Applications, DCNA 2023

作者： Jnadi, Ali Khusainov, Ramil Nedelchev, Simeon Savin, Sergei Innopolis University Institute of Robotics and Computer Vision Innopolis Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (纸本)9798350305746

Zonotopes have become a widely used tool in control design, demonstrating their effectiveness in various applications ranging from state estimation to explicit model predictive control. However, the traditional use of zonotopes is limited by a set certain geometric shapes that restrict the range of state sets that can be considered. This paper proposes a novel approach to control design using constrained zonotopes that can encode arbitrary polytopes. We present a propagation scheme and an affine approximation of the exact control law for this representation, and discuss issues related to center identification for constrained zonotopes. A fast method for detecting set membership is also proposed based on lifting the constrained zonotopes into a higher dimensional space. The proposed method extends the range of shapes that can be considered in control design and offers a promising alternative to the limitations of regular zonotopes. It has the potential for wide-ranging impact in various areas of control, providing a valuable tool for solving complex control problems. © 2023 IEEE.

关键词： Convex optimization

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Development of a digital software platform for the study of nonlinear dynamics of electronic systems 3

Development of a digital software platform for the study of ...

引用

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

作者： Badarin, Artem Neuroscience and Cognivite Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

The paper presents the results of applied research on the design and application of an integrated platform for solving applied problems of developing, studying and optimizing high-power electron-plasma devices from th... 详细信息

ISBN: (纸本)9781728124704

关键词： Simulation platform

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Multilayer perceptron reveals functional connectivity structrure in thalamo-cortical brain network 3

Multilayer perceptron reveals functional connectivity struct...

引用

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

作者： Frolov, Nikita S. Hramov, Alexander E. Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

Artificial neural networks (ANNs) are known to be a powerful tool for big data analysis. They are widely used in computer science, nonlinear dynamics, robotics, and neuroscience for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience ANNs allow recognizing specific forms of brain activity from multichannel electro- (EEG) or magnetoencephalographic (MEG) data and, therefore, widely used as a computational core in various brain-computer interfaces. Another challenging problem is the analysis of connectivity structures in big multivariate data. In neuroscience restoring the functional brain network using multichannel EEG/MEG signals uncovers mechanisms of neuronal interaction during various physiological or cognitive processes. In this report we use recent advances in the area of machine learning known as feed-forward artificial neuronal network to formulate a method for detecting functional dependence in unidirectionally and bidirectionally coupled systems without additional information about them. We apply our method for the first time to reveal functional connectivity structure in the thalamo-cortical network of epileptic brain based on a rodent electrocorticography (ECoG) data set. © 2019 IEEE.

关键词： Brain

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Classification of hand-related real and imaginary motor activity with fNIRS 4

Classification of hand-related real and imaginary motor acti...

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

作者： Hramov, Alexander Grubov, Vadim Badarin, Artem Center for Technologies in Robotics and Mechatronics Components Innopolis University Neuroscience and Cognitive Technology Lab Innopolis Russia

ISBN: (纸本)9781728172866

In the present work we studied blood oxygenation/deoxygenation spatial dynamics related to real and imaginary motor activity using functional near-infrared spectroscopy (fNIRS). We revealed biomarkers based on pronounced hemispheric lateralization of hemodynamical response in the motor cortex during motor activity. We used these markers to design a sensing method for classification of movement's type. The accuracy of real movements classification was close to 100%, while for imaginary movements it was lower but still quite high (about 90%). The proposed system can find application, for example, in neurorehabilitation after severe brain injuries, including traumas and strokes. © 2020 IEEE.

关键词： Infrared devices

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Time-frequency and recurrence quantification analysis detect limb movement execution from EEG data 3

Time-frequency and recurrence quantification analysis detect...

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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 application of recurrence quantification analysis (RQA) in detection of motor-related electroencephalograms (EEG). Particularly, we apply RQA to reveal transitions of mu-rhythm dynamics extracted from multichannel EEG recorded in motor cortex. The results show that the considering RQA measures of EEG in time-frequency domain one can effectively reveal dynamical features of motor-related brain activity. © 2019 IEEE.

关键词： Electroencephalography

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The control of the dynamics of intense electron beams coupled through a common field 3

The control of the dynamics of intense electron beams couple...

引用

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

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

ISBN: (纸本)9781728124704

This paper presents the results of a study of the nonlinear dynamics of a system with several electron beams. A review and analysis of the latest results obtained in this area. In this case, the main emphasis in this work is made on controlling the generation characteristics in such a highly nonlinear system. The main dynamic modes typical for this kind of systems are shown. © 2019 IEEE.

关键词： Electron beams

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Features of real and imaginary motor activity on EEG and fNIRS signals for neurorehabilitation 3

Features of real and imaginary motor activity on EEG and fNI...

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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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