Analysis And Classification Of Eeg Signals For Brain Computer Interfaces
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Analysis And Classification Of Eeg Signals For Brain Computer Interfaces
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Author : Szczepan Paszkiel
language : en
Publisher: Springer Nature
Release Date : 2019-08-31
Analysis And Classification Of Eeg Signals For Brain Computer Interfaces written by Szczepan Paszkiel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-31 with Technology & Engineering categories.
This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology. In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.
Analysis And Classification Of Eeg Signals For Brain Computer Interfaces Data Acquisition Methods For Human Brain Activity
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Author : Szczepan Paszkiel
language : en
Publisher:
Release Date : 2020
Analysis And Classification Of Eeg Signals For Brain Computer Interfaces Data Acquisition Methods For Human Brain Activity written by Szczepan Paszkiel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Brain-computer interfaces categories.
This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain-computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore-Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology. In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain-computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain-computer technology and virtual reality technology.
Eeg Signal Analysis And Classification
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Author : Siuly Siuly
language : en
Publisher: Springer
Release Date : 2017-01-03
Eeg Signal Analysis And Classification written by Siuly Siuly and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-03 with Technology & Engineering categories.
This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems. The proposed methods enable the extraction of this vital information from EEG signals in order to accurately detect abnormalities revealed by the EEG. New methods will relieve the time-consuming and error-prone practices that are currently in use. Common signal processing methodologies include wavelet transformation and Fourier transformation, but these methods are not capable of managing the size of EEG data. Addressing the issue, this book examines new EEG signal analysis approaches with a combination of statistical techniques (e.g. random sampling, optimum allocation) and machine learning methods. The developed methods provide better results than the existing methods. The book also offers applications of the developed methodologies that have been tested on several real-time benchmark databases. This book concludes with thoughts on the future of the field and anticipated research challenges. It gives new direction to the field of analysis and classification of EEG signals through these more efficient methodologies. Researchers and experts will benefit from its suggested improvements to the current computer-aided based diagnostic systems for the precise analysis and management of EEG signals. /div
Deep Learning For Eeg Based Brain Computer Interfaces Representations Algorithms And Applications
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Author : Xiang Zhang
language : en
Publisher: World Scientific
Release Date : 2021-09-14
Deep Learning For Eeg Based Brain Computer Interfaces Representations Algorithms And Applications written by Xiang Zhang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-14 with Computers categories.
Deep Learning for EEG-Based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms and applications. BCI bridges humanity's neural world and the physical world by decoding an individuals' brain signals into commands recognizable by computer devices.This book presents a highly comprehensive summary of commonly-used brain signals; a systematic introduction of around 12 subcategories of deep learning models; a mind-expanding summary of 200+ state-of-the-art studies adopting deep learning in BCI areas; an overview of a number of BCI applications and how deep learning contributes, along with 31 public BCI data sets. The authors also introduce a set of novel deep learning algorithms aimed at current BCI challenges such as robust representation learning, cross-scenario classification, and semi-supervised learning. Various real-world deep learning-based BCI applications are proposed and some prototypes are presented. The work contained within proposes effective and efficient models which will provide inspiration for people in academia and industry who work on BCI.Related Link(s)
Analysis And Classification Of Eeg Signals Using Probabilistic Models For Brain Computer Interfaces
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Author : Silvia Chiappa
language : en
Publisher:
Release Date : 2006
Analysis And Classification Of Eeg Signals Using Probabilistic Models For Brain Computer Interfaces written by Silvia Chiappa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Eeg Signal Processing And Feature Extraction
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Author : Li Hu
language : en
Publisher: Springer Nature
Release Date : 2019-10-12
Eeg Signal Processing And Feature Extraction written by Li Hu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-12 with Medical categories.
This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.
Signal Processing And Machine Learning For Brain Machine Interfaces
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Author : Toshihisa Tanaka
language : en
Publisher: Institution of Engineering and Technology
Release Date : 2018-09-13
Signal Processing And Machine Learning For Brain Machine Interfaces written by Toshihisa Tanaka and has been published by Institution of Engineering and Technology this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-13 with Technology & Engineering categories.
Brain-machine interfacing or brain-computer interfacing (BMI/BCI) is an emerging and challenging technology used in engineering and neuroscience. The ultimate goal is to provide a pathway from the brain to the external world via mapping, assisting, augmenting or repairing human cognitive or sensory-motor functions.
Applications Of Brain Computer Interfaces In Intelligent Technologies
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Author : Szczepan Paszkiel
language : en
Publisher: Springer Nature
Release Date : 2022-07-08
Applications Of Brain Computer Interfaces In Intelligent Technologies written by Szczepan Paszkiel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-08 with Technology & Engineering categories.
The BCI technology finds newer and newer implementations. Year by year, the number of publications in this field grows exponentially. This book attempts to describe the implementation of the brain-computer technology based on both STM32 and Arduino microcontrollers. In addition, the application of BCI technology in the field of intelligent houses, robotic lines as well as in the field of bionic prostheses was presented. One of the chapters of the monograph also discusses the issue of fMRI in the context of the possibility of analyzing images made as part of fMRI through solutions based on machine learning. A practical implementation of the TensorFlow framework was presented. The fMRI technique is also often implemented in BCI solutions. The conducted literature studies show that the technology of BCI is undoubtedly a technology of the future. However, there is a need for continuous development of biomedical signal processing methods in order to obtain the most efficient implementations in the case of non-invasive implementation of BCI technology based on EEG. The further development of BCI technology has a huge impact on the techniques of rehabilitation of people with disabilities. Nowadays, wheelchairs are being constructed, thanks to which a disabled person is physically able to direct his position in a certain direction and at a certain speed. Thanks to BCI, it is also possible to create an individual speech synthesizer, with the help of which a paralyzed person will be able to communicate with the outside world. New limb prostheses that will replace the lost locomotor system in almost one hundred percent are still being developed. Some prostheses are connected to the human nervous system, thanks to which they are able to send feedback to our brain about the shape, hardness and temperature of the object held in the artificial limb.
Brain Computer Interfaces For Perception Learning And Motor Control
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Author : Saugat Bhattacharyya
language : en
Publisher: Frontiers Media SA
Release Date : 2021-12-21
Brain Computer Interfaces For Perception Learning And Motor Control written by Saugat Bhattacharyya and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-21 with Science categories.
Brain Computer Interfaces
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2014-11-01
Brain Computer Interfaces written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-01 with Technology & Engineering categories.
The success of a BCI system depends as much on the system itself as on the user’s ability to produce distinctive EEG activity. BCI systems can be divided into two groups according to the placement of the electrodes used to detect and measure neurons firing in the brain. These groups are: invasive systems, electrodes are inserted directly into the cortex are used for single cell or multi unit recording, and electrocorticography (EcoG), electrodes are placed on the surface of the cortex (or dura); noninvasive systems, they are placed on the scalp and use electroencephalography (EEG) or magnetoencephalography (MEG) to detect neuron activity. The book is basically divided into three parts. The first part of the book covers the basic concepts and overviews of Brain Computer Interface. The second part describes new theoretical developments of BCI systems. The third part covers views on real applications of BCI systems.