Deep Learning In Brain Computer Interface

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Brain-Computer Interface

Author : M.G. Sumithra
Publisher : John Wiley & Sons
ISBN 13 : 1119857201
Total Pages : 325 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Brain-Computer Interface by : M.G. Sumithra

Download or read book Brain-Computer Interface written by M.G. Sumithra and published by John Wiley & Sons. This book was released on 2023-03-14 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: BRAIN-COMPUTER INTERFACE It covers all the research prospects and recent advancements in the brain-computer interface using deep learning. The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved. Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN). Audience Researchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists.

Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications

Author : Xiang Zhang
Publisher : World Scientific
ISBN 13 : 1786349604
Total Pages : 294 pages
Book Rating : 4.7/5 (863 download)

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Book Synopsis Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications by : Xiang Zhang

Download or read book Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications written by Xiang Zhang and published by World Scientific. This book was released on 2021-09-14 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Deep Learning in Brain-Computer Interface

Author : Minkyu Ahn
Publisher : Frontiers Media SA
ISBN 13 : 2889763285
Total Pages : 147 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Deep Learning in Brain-Computer Interface by : Minkyu Ahn

Download or read book Deep Learning in Brain-Computer Interface written by Minkyu Ahn and published by Frontiers Media SA. This book was released on 2022-06-06 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Signal Processing and Machine Learning for Brain-Machine Interfaces

Author : Toshihisa Tanaka
Publisher : Institution of Engineering and Technology
ISBN 13 : 1785613987
Total Pages : 355 pages
Book Rating : 4.7/5 (856 download)

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Book Synopsis Signal Processing and Machine Learning for Brain-Machine Interfaces by : Toshihisa Tanaka

Download or read book Signal Processing and Machine Learning for Brain-Machine Interfaces written by Toshihisa Tanaka and published by Institution of Engineering and Technology. This book was released on 2018-09-13 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Signal Processing and Machine Learning for Brain-machine Interfaces

Author : Toshihisa Tanaka (Engineer)
Publisher :
ISBN 13 : 9781523119837
Total Pages : pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Signal Processing and Machine Learning for Brain-machine Interfaces by : Toshihisa Tanaka (Engineer)

Download or read book Signal Processing and Machine Learning for Brain-machine Interfaces written by Toshihisa Tanaka (Engineer) and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. In this book an international panel of experts introduce signal processing and machine learning techniques for BMI/BCI and outline their practical and future applications in neuroscience, medicine, and rehabilitation, with a focus on EEG-based BMI/BCI methods and technologies. Topics covered include discriminative learning of connectivity pattern of EEG; feature extraction from EEG recordings; EEG signal processing; transfer learning algorithms in BCI; convolutional neural networks for event-related potential detection; spatial filtering techniques for improving individual template-based SSVEP detection; feature extraction and classification algorithms for image RSVP based BCI; decoding music perception and imagination using deep learning techniques; neurofeedback games using EEG-based Brain-Computer Interface Technology; affective computing system and more.

Toward Brain-computer Interfacing

Author : Guido Dornhege
Publisher : MIT Press
ISBN 13 : 0262042444
Total Pages : 520 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Toward Brain-computer Interfacing by : Guido Dornhege

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.

Artificial Intelligence-Based Brain-Computer Interface

Author : Varun Bajaj
Publisher : Academic Press
ISBN 13 : 0323914128
Total Pages : 394 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence-Based Brain-Computer Interface by : Varun Bajaj

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

Connected Health in Smart Cities

Author : Abdulmotaleb El Saddik
Publisher : Springer Nature
ISBN 13 : 3030278441
Total Pages : 254 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Connected Health in Smart Cities by : Abdulmotaleb El Saddik

Download or read book Connected Health in Smart Cities written by Abdulmotaleb El Saddik and published by Springer Nature. This book was released on 2019-12-03 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the theoretical foundations, fundamental applications and latest advances in various aspects of connected services for health information systems. The twelve chapters highlight state-of-the-art approaches, methodologies and systems for the design, development, deployment and innovative use of multisensory systems and tools for health management in smart city ecosystems. They exploit technologies like deep learning, artificial intelligence, augmented and virtual reality, cyber physical systems and sensor networks. Presenting the latest developments, identifying remaining challenges, and outlining future research directions for sensing, computing, communications and security aspects of connected health systems, the book will mainly appeal to academic and industrial researchers in the areas of health information systems, smart cities, and augmented reality.

Brain-Computer Interfacing

Author : Rajesh P. N. Rao
Publisher : Cambridge University Press
ISBN 13 : 0521769418
Total Pages : 337 pages
Book Rating : 4.5/5 (217 download)

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Book Synopsis Brain-Computer Interfacing by : Rajesh P. N. Rao

Download or read book Brain-Computer Interfacing written by Rajesh P. N. Rao and published by Cambridge University Press. This book was released on 2013-09-30 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this a reality, opening the door to restoration and augmentation of human physical and mental capabilities. Medical applications such as cochlear implants for the deaf and neurally controlled prosthetic limbs for the paralyzed are becoming almost commonplace. Brain-computer interfaces (BCIs) are also increasingly being used in security, lie detection, alertness monitoring, telepresence, gaming, education, art, and human augmentation. This introduction to the field is designed as a textbook for upper-level undergraduate and first-year graduate courses in neural engineering or brain-computer interfacing for students from a wide range of disciplines. It can also be used for self-study and as a reference by neuroscientists, computer scientists, engineers, and medical practitioners. Key features include questions and exercises in each chapter and a supporting website.

Intelligent Computing in Bioinformatics

Author : De-Shuang Huang
Publisher : Springer
ISBN 13 : 3319093304
Total Pages : 532 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Intelligent Computing in Bioinformatics by : De-Shuang Huang

Download or read book Intelligent Computing in Bioinformatics written by De-Shuang Huang and published by Springer. This book was released on 2014-07-03 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book – in conjunction with the volumes LNCS 8588 and LNAI 8589 – constitutes the refereed proceedings of the 10th International Conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August 2014. The 58 papers of this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections such as machine learning; neural networks; image processing; computational systems biology and medical informatics; biomedical informatics theory and methods; advances on bio-inspired computing; protein and gene bioinformatics: analysis, algorithms, applications.

Improving Generalization Performance of Deep Learning for Brain-Computer Interface

Author : Sanghyun Choo
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)

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Book Synopsis Improving Generalization Performance of Deep Learning for Brain-Computer Interface by : Sanghyun Choo

Download or read book Improving Generalization Performance of Deep Learning for Brain-Computer Interface written by Sanghyun Choo and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Brain-Computer Interface

Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1839625228
Total Pages : 200 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Brain-Computer Interface by :

Download or read book Brain-Computer Interface written by and published by BoD – Books on Demand. This book was released on 2022-05-18 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain-computer interfacing (BCI) with the use of advanced artificial intelligence identification is a rapidly growing new technology that allows a silently commanding brain to manipulate devices ranging from smartphones to advanced articulated robotic arms when physical control is not possible. BCI can be viewed as a collaboration between the brain and a device via the direct passage of electrical signals from neurons to an external system. The book provides a comprehensive summary of conventional and novel methods for processing brain signals. The chapters cover a range of topics including noninvasive and invasive signal acquisition, signal processing methods, deep learning approaches, and implementation of BCI in experimental problems.

Compassionate Artificial Intelligence

Author : Amit Ray
Publisher : Compassionate AI Lab (An Imprint of Inner Light Publishers)
ISBN 13 : 9382123466
Total Pages : 161 pages
Book Rating : 4.3/5 (821 download)

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Book Synopsis Compassionate Artificial Intelligence by : Amit Ray

Download or read book Compassionate Artificial Intelligence written by Amit Ray and published by Compassionate AI Lab (An Imprint of Inner Light Publishers). This book was released on 2018-10-03 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book Dr. Amit Ray describes the principles, algorithms and frameworks for incorporating compassion, kindness and empathy in machine. This is a milestone book on Artificial Intelligence. Compassionate AI address the issues for creating solutions for some of the challenges the humanity is facing today, like the need for compassionate care-giving, helping physically and mentally challenged people, reducing human pain and diseases, stopping nuclear warfare, preventing mass destruction weapons, tackling terrorism and stopping the exploitation of innocent citizens by monster governments through digital surveillance. The book also talks about compassionate AI for precision medicine, new drug discovery, education, and legal system. Dr. Ray explained the DeepCompassion algorithms, five design principles and eleven key behavioral principle of compassionate AI systems. The book also explained several compassionate AI projects. Compassionate AI is the best practical guide for AI students, researchers, entrepreneurs, business leaders looking to get true value from the adoption of compassion in machine learning technology.

Analysis of Brain Computer Interface Using Deep and Machine Learning

Author : Carlos M. Travieso-Gonzalez
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Analysis of Brain Computer Interface Using Deep and Machine Learning by : Carlos M. Travieso-Gonzalez

Download or read book Analysis of Brain Computer Interface Using Deep and Machine Learning written by Carlos M. Travieso-Gonzalez and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is becoming increasingly important topic in all sectors of society. From the optimization of processes in the industry to the detection and diagnosis of diseases in medicine. Brain-computer interfaces are introduced in this chapter. Systems capable of analyzing brain signal patterns, processing and interpreting them through machine and deep learning algorithms. In this chapter, a hybrid deep/machine learning ensemble system for brain pattern recognition is proposed. It is capable to recognize patterns and translate the decisions to BCI systems. For this, a public database (Physionet) with data of motor tasks and mental tasks is used. The development of this chapter consists of a brief summary of the state of the art, the presentation of the model together with some results and some promising conclusions.

Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing

Author : Yizhang Jiang
Publisher : Frontiers Media SA
ISBN 13 : 2889714683
Total Pages : 239 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing by : Yizhang Jiang

Download or read book Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing written by Yizhang Jiang and published by Frontiers Media SA. This book was released on 2021-10-13 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Brain and Behavior Computing

Author : Mridu Sahu
Publisher : CRC Press
ISBN 13 : 1000387151
Total Pages : 429 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Brain and Behavior Computing by : Mridu Sahu

Download or read book Brain and Behavior Computing written by Mridu Sahu and published by CRC Press. This book was released on 2021-06-23 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain and Behavior Computing offers insights into the functions of the human brain. This book provides an emphasis on brain and behavior computing with different modalities available such as signal processing, image processing, data sciences, statistics further it includes fundamental, mathematical model, algorithms, case studies, and future research scopes. It further illustrates brain signal sources and how the brain signal can process, manipulate, and transform in different domains allowing researchers and professionals to extract information about the physiological condition of the brain. Emphasizes real challenges in brain signal processing for a variety of applications for analysis, classification, and clustering. Discusses data sciences and its applications in brain computing visualization. Covers all the most recent tools for analysing the brain and it’s working. Describes brain modeling and all possible machine learning methods and their uses. Augments the use of data mining and machine learning to brain computer interface (BCI) devices. Includes case studies and actual simulation examples. This book is aimed at researchers, professionals, and graduate students in image processing and computer vision, biomedical engineering, signal processing, and brain and behavior computing.

Handbook of Deep Learning Applications

Author : Valentina Emilia Balas
Publisher : Springer
ISBN 13 : 9783030114787
Total Pages : 383 pages
Book Rating : 4.1/5 (147 download)

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Book Synopsis Handbook of Deep Learning Applications by : Valentina Emilia Balas

Download or read book Handbook of Deep Learning Applications written by Valentina Emilia Balas and published by Springer. This book was released on 2019-03-06 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.