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Author: Melinda, Na Li, Erick Purwanto, Muliyadi, Yunidar, Syahrul
Publisher: Syiah Kuala University Press
ISBN: 6232649982
Category : Medical
Languages : en
Pages : 198
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Book Description
This book is a reference book for several studies related to the themes of EEG Signal Processing, Feature Extraction, and Deep Learning. This research was carried out comprehensively using EEG data from autism sufferers. Then a signal signal is carried out by applying several feature extraction methods. Next, we continued the classification process using deep learning methods to get accurate results and differentiate waveforms in autism sufferers from ordinary people. This book is intended for Electrical Engineering, Telecommunications, Electronics Engineering, Control Engineering, Computer Engineering, and other related fields of science. It is still possible to choose empirical formulas/equations. Then, this book has summarized several results from previous research that have been published in international journals related to EEG signal processing and the application of Deep Learning.
Author: Melinda, Na Li, Erick Purwanto, Muliyadi, Yunidar, Syahrul
Publisher: Syiah Kuala University Press
ISBN: 6232649982
Category : Medical
Languages : en
Pages : 198
Get Book Here
Book Description
This book is a reference book for several studies related to the themes of EEG Signal Processing, Feature Extraction, and Deep Learning. This research was carried out comprehensively using EEG data from autism sufferers. Then a signal signal is carried out by applying several feature extraction methods. Next, we continued the classification process using deep learning methods to get accurate results and differentiate waveforms in autism sufferers from ordinary people. This book is intended for Electrical Engineering, Telecommunications, Electronics Engineering, Control Engineering, Computer Engineering, and other related fields of science. It is still possible to choose empirical formulas/equations. Then, this book has summarized several results from previous research that have been published in international journals related to EEG signal processing and the application of Deep Learning.
Author: Wai Yie Leong
Publisher: Healthcare Technologies
ISBN: 9781785613708
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
Electroencephalography (EEG) is an electrophysiological monitoring method used to record the brain activity in brain-computer interface (BCI) systems. It records the electrical activity of the brain, is typically non-invasive with electrodes placed along the scalp, requires relatively simple and inexpensive equipment, and is easier to use than other methods. EEG-based BCI methods provide modest speed and accuracy which is why multichannel systems and proper signal processing methods are used for feature extraction, feature selection and feature classification to discriminate among several mental tasks. This edited book presents state of the art aspects of EEG signal processing methods, with an emphasis on advanced strategies, case studies, clinical practices and applications such as EEG for meditation, auditory selective attention, sleep apnoea; person authentication; handedness detection, Parkinson's disease, motor imagery, smart air travel support and brain signal classification.
Author: Li Hu
Publisher: Springer Nature
ISBN: 9811391130
Category : Medical
Languages : en
Pages : 435
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Book Description
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.
Author: Marcin Wozniak
Publisher: Frontiers Media SA
ISBN: 2889715787
Category : Science
Languages : en
Pages : 103
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Book Description
Author: Mostafa Ezziyyani
Publisher: Springer Nature
ISBN: 3031523857
Category :
Languages : en
Pages : 458
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Book Description
Author: Sudipta Roy
Publisher: Springer Nature
ISBN: 9811605386
Category : Technology & Engineering
Languages : en
Pages : 317
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Book Description
This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.
Author: Bouchemal, Nardjes
Publisher: IGI Global
ISBN: 1522570721
Category : Medical
Languages : en
Pages : 402
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Book Description
With the growing use of new technologies and artificial intelligence (AI) applications, intelligent systems can be used to manage large amounts of existing data in healthcare domains. Having more intelligent methods for accessing data allows medical professionals to more efficiently identify the best medical practices and more concrete solutions for diagnosing and treating a multitude of rare diseases. Intelligent Systems for Healthcare Management and Delivery provides relevant and advanced methodological, technological, and scientific approaches related to the application of sophisticated exploitation of AI, as well as providing insight into the technologies and intelligent applications that have received growing attention in recent years such as medical imaging, EMR systems, and drug development assistance. This publication fosters a scientific debate for new healthcare intelligent systems and sophisticated approaches for enhanced healthcare services and is ideally designed for medical professionals, hospital staff, rehabilitation specialists, medical educators, and researchers.
Author: Jyotismita Chaki
Publisher: CRC Press
ISBN: 1000872181
Category : Computers
Languages : en
Pages : 268
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Book Description
This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data preprocessing including scaling, correction, trimming, and normalization is also included. Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders. Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative, neurodevelopmental, and psychiatric disorders. Helps build, train, and deploy different types of deep architectures for diagnosis. Explores data preprocessing techniques involved in diagnosis. Includes real-time case studies and examples. This book is aimed at graduate students and researchers in biomedical imaging and machine learning.
Author: Saeed Mian Qaisar
Publisher: Springer Nature
ISBN: 3031232399
Category : Computers
Languages : en
Pages : 385
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Book Description
This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problem statement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors’ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems.
Author: Siuly Siuly
Publisher: Springer
ISBN: 331947653X
Category : Technology & Engineering
Languages : en
Pages : 257
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Book Description
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
