Download or read book Analysis and Classification of EEG Signals for Brain computer Interfaces Data acquisition methods for human brain activity written by Szczepan Paszkiel and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Analysis and Classification of EEG Signals for Brain Computer Interfaces written by Szczepan Paszkiel and published by Springer Nature. This book was released on 2019-08-31 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Brain Computer Interface written by Narayan Panigrahi and published by CRC Press. This book was released on 2022-07-29 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain Computer Interface: EEG Signal Processing discusses electroencephalogram (EEG) signal processing using effective methodology and algorithms. This book provides a basic introduction to EEG and a classification of different components present in EEG. It also helps the reader to understand the scope of processing EEG signals and their associated applications. Further, it covers specific aspects such as epilepsy detection; exploitation of P300 for various applications; design of an EEG acquisition system; and detection of saccade, fix, and blink from EEG and EOG data. Key Features: Explains the basis of brain computer interface and how it can be established using different EEG signal characteristics Covers the detailed classification of different types of EEG signals with respect to their physical characteristics Explains detection and diagnosis of epileptic seizures from the EEG data of a subject Reviews the design and development of a low-cost and robust EEG acquisition system Provides mathematical analysis of EEGs, including MATLAB® codes for students to experiment with EEG data This book is aimed at graduate students and researchers in biomedical, electrical, electronics, communication engineering, healthcare, and cyber physical systems.

Download or read book EEG Based Brain Computer Interfaces written by Dipali Bansal and published by Academic Press. This book was released on 2019-03-14 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: EEG-Based Brain-Computer Interface: Cognitive Analysis and Control Applications provides a technical approach to using brain signals for control applications, along with the EEG-related advances in BCI. The research and techniques in this book discuss time and frequency domain analysis on deliberate eye-blinking data as the basis for EEG-triggering control applications. In addition, the book provides experimental scenarios and features algorithms for acquiring real-time EEG signals using commercially available units that interface with MATLAB software for acquisition and control. Details techniques for multiple types of analysis (including ERP, scalp map, sub-band power and independent component) to acquire data from deliberate eye-blinking Demonstrates how to use EEGs to develop more intuitive BCIs in real-time scenarios Includes algorithms and scenarios that interface with MATLAB software for interactive use

Download or read book Brain Computer Interface Systems written by Reza Fazel-Rezai and published by BoD – Books on Demand. This book was released on 2013-06-05 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain-Computer Interface (BCI) systems allow communication based on a direct electronic interface which conveys messages and commands directly from the human brain to a computer. In the recent years, attention to this new area of research and the number of publications discussing different paradigms, methods, signal processing algorithms, and applications have been increased dramatically. The objective of this book is to discuss recent progress and future prospects of BCI systems. The topics discussed in this book are: important issues concerning end-users; approaches to interconnect a BCI system with one or more applications; several advanced signal processing methods (i.e., adaptive network fuzzy inference systems, Bayesian sequential learning, fractal features and neural networks, autoregressive models of wavelet bases, hidden Markov models, equivalent current dipole source localization, and independent component analysis); review of hybrid and wireless techniques used in BCI systems; and applications of BCI systems in epilepsy treatment and emotion detections.

Download or read book EEG Signal Analysis and Classification written by Siuly Siuly and published by Springer. This book was released on 2017-01-03 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book EEG ERP Analysis written by Kamel Nidal and published by CRC Press. This book was released on 2014-10-23 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and other monitoring systems used in preventive diagnostic procedures incorporate innovative features for brain monitoring functions such as real-time automated signal processing techniques and sophisticated amplifiers. Highlighting the US, Europe, Australia, New Zealand, Japan, Korea, China, and many other areas, EEG/ERP Analysis: Methods and Applications examines how researchers from various disciplines have started to work in the field of brain science, and explains the different techniques used for processing EEG/ERP data. Engineers can learn more about the clinical applications, while clinicians and biomedical scientists can familiarize themselves with the technical aspects and theoretical approaches. This book explores the recent advances involved in EEG/ERP analysis for brain monitoring, details successful EEG and ERP applications, and presents the neurological aspects in a simplified way so that those with an engineering background can better design clinical instruments. It consists of 13 chapters and includes the advanced techniques used for signal enhancement, source localization, data fusion, classification, and quantitative EEG. In addition, some of the chapters are contributed by neurologists and neurosurgeons providing the clinical aspects of EEG/ERP analysis. Covers a wide range of EEG/ERP applications with state-of-the-art techniques for denoising, analysis, and classification Examines new applications related to 3D display devices Includes MATLAB® codes EEG/ERP Analysis: Methods and Applications is a resource for biomedical and neuroscience scientists who are working on neural signal processing and interpretation, and biomedical engineers who are working on EEG/ERP signal analysis methods and developing clinical instrumentation. It can also assist neurosurgeons, psychiatrists, and postgraduate students doing research in neural engineering, as well as electronic engineers in neural signal processing and instrumentation.

Download or read book EEG Signal Processing written by Saeid Sanei and published by John Wiley & Sons. This book was released on 2013-05-28 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.

Download or read book Applications of Brain Computer Interfaces in Intelligent Technologies written by Szczepan Paszkiel and published by Springer Nature. This book was released on 2022-07-08 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Real Time BCI System Design to Control Arduino Based Speed Controllable Robot Using EEG written by Swagata Das and published by Springer. This book was released on 2018-12-08 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the basic requirements and constraints in building a brain–computer interaction system. These include the technical requirements for building the signal processing module and the acquisition module. The major aspects to be considered when designing a signal acquisition module for a brain–computer interaction system are the human brain, types and applications of brain–computer systems, and the basics of EEG (electroencephalogram) recording. The book also compares the algorithms that have been and that can be used to design the signal processing module of brain–computer interfaces, and describes the various EEG-acquisition devices available and compares their features and inadequacies. Further, it examines in detail the use of Emotiv EPOC (an EEG acquisition module developed by Emotiv) to build a complete brain–computer interaction system for driving robots using a neural network classification module.

Download or read book Computational EEG Analysis written by Chang-Hwan Im and published by Springer. This book was released on 2018-08-16 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces and reviews all of the currently available methods being used for computational electroencephalogram (EEG) analysis, from the fundamentals through to the state-of-the-art. The aim of the book is to help biomedical engineers and medical doctors who use EEG to better understand the methods and applications of computational EEG analysis from a single, well-organized resource. Following a brief introduction to the principles of EEG and acquisition techniques, the book is divided into two main sections. The first of these covers analysis methods, beginning with preprocessing, and then describing EEG spectral analysis, event-related potential analysis, source imaging and multimodal neuroimaging, and functional connectivity analysis. The following section covers application of EEG analysis to specific fields, including the diagnosis of psychiatric diseases and neurological disorders, brain-computer interfacing, and social neuroscience. Aimed at practicing medical specialists, engineers, researchers and advanced students, the book features contributions from world-renowned biomedical engineers working across a broad spectrum of computational EEG analysis techniques and EEG applications.

Download or read book Imaging Brain Function With EEG written by Walter Freeman and published by Springer Science & Business Media. This book was released on 2012-10-28 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scalp and cortex lie like pages of an open book on which the cortex enciphers vast quantities of information and knowledge. They are recorded and analyzed as temporal and spatial patterns in the electroencephalogram and electrocorticogram. This book describes basic tools and concepts needed to measure and decipher the patterns extracted from the EEG and ECoG. This book emphasizes the need for single trial analysis using new methods and paradigms, as well as large, high-density spatial arrays of electrodes for pattern sampling. The deciphered patterns reveal neural mechanisms by which brains process sensory information into precepts and concepts. It describes the brain as a thermodynamic system that uses chemical energy to construct knowledge. The results are intended for use in the search for the neural correlates of intention, attention, perception and learning; in the design of human brain-computer interfaces enabling mental control of machines; and in exploring and explaining the physicochemical foundation of biological intelligence.

Download or read book Control Computer Engineering and Neuroscience written by Szczepan Paszkiel and published by Springer Nature. This book was released on 2021-03-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 4th International Scientific Conference IC BCI 2021 Opole, Poland. The event was held at Opole University of Technology in Poland on 21 September 2021. Since 2014, the conference has taken place every two years at the University’s Faculty of Electrical Engineering, Automatic Control and Informatics. The conference focused on the issues relating to new trends in modern brain–computer interfaces (BCI) and control engineering, including neurobiology–neurosurgery, cognitive science–bioethics, biophysics–biochemistry, modeling–neuroinformatics, BCI technology, biomedical engineering, control and robotics, computer engineering and neurorehabilitation–biofeedback.

Download or read book Artificial Intelligence Based Brain Computer Interface written by Varun Bajaj and published by Academic Press. This book was released on 2022-02-04 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services. - Provides readers with an understanding of key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders - Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for the early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others - Includes illustrative examples on how Artificial Intelligence can be applied to the Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders

Download or read book Advanced Techniques for Classification of Multi channel EEG Signals for Brain Computer Interface written by Mohammad Rubaiyat Hasan and published by . This book was released on 2015 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electroencephalogram (EEG) signal based research is ongoing for the development of simple, user friendly, robust, efficient brain computer interfacing (BCI) devices/systems. Motor imagery related EEG signal classification is one of the main challenges in designing of a BCI system. An advanced and simple classification technique for motor imagery related BCI system has been developed. Fisher Linear Discriminant Analysis (FLDA) has a very low computational requirement, which makes it suitable for BCI system. Motor imagery based EEG dataset, collected by the world renowned BCI Group from Graz University of Technology, Austria, has been used. Initially the signal is extracted into features. The power spectral density technique has been used to extract the non-linear features over some frequency components in motor imagery based EEG signals. In training phase FLDA, Mahalanobis Discriminant Analysis (MDA), Quadratic Discriminant Analysis (QDA), Cauchy and Gaussian Radial Basis (GRB) classification techniques have been used for designing a motor imagery based BCI system. Then the optimized classifier MDA has been chosen. But in evaluation phase, FLDA performs better than MDA. This classification technique separates the extracted signals into possible classes by taking the means and variances between two classes. Then percentage of accuracy has been measured to detect the motor imagery movement. In addition, the probabilistic accuracy has been measured by using Cohen's kappa. It obtains more than 98% of accuracy and around 95% kappa in average in training phase using MDA. In evaluation state, they are 46% and 39% accuracies using FLDA and MDA respectively. For contrastive justification, some other classification techniques have also been used to compare the obtained results. Result depicts that the MDA classifier could be a preferable classification technique for both training and evaluation for detecting different motor imagery related brain states.

Download or read book Electroencephalographic Signal Processing and Classifications Techniques for Noninvasive Motor Imagery Based Brain Computer Interface written by Erfanul Alam and published by . This book was released on 2017 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author's abstract: In motor imagery (MI) based brain-computer interface (BCI), success depends on reliable processing of the noisy, non-linear, and non-stationary brain activity signals for extraction of features and effective classification of MI activity as well as translation to the corresponding intended actions. In this study, signal processing and classification techniques are presented for electroencephalogram (EEG) signals for motor imagery based brain-computer interface. EEG signals have been acquired placing the electrodes following the international 10-20 system. The acquired signals have been pre-processed removing artifacts using empirical mode decomposition (EMD) and two extended versions of EMD, ensemble empirical mode decomposition (EEMD), and multivariate empirical mode decomposition (MEMD) leading to better signal to noise ratio (SNR) and reduced mean square error (MSE) compared to independent component analysis (ICA). EEG signals have been decomposed into independent mode function (IMFs) that are further processed to extract features like sample entropy (SampEn) and band power (BP). The extracted features have been used in support vector machines to characterize and identify MI activities. EMD and its variants, EEMD, MEMD have been compared with common spatial pattern (CSP) for different MI activities. SNR values from EMD, EEMD and MEMD (4.3, 7.64, 10.62) are much better than ICA (2.1) but accuracy of MI activity identification is slightly better for ICA than EMD using BP and SampEn. Further work is outlined to include more features with larger database for better classification accuracy.

Download or read book Toward Brain computer Interfacing written by Guido Dornhege and published by MIT Press. This book was released on 2007 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a timely overview of the latest BCI research, with contributions from many of the important research groups in the field.