Adaptive Processing Of Brain Signals

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Adaptive Processing Of Brain Signals

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Author : Saeid Sanei
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-28

Adaptive Processing Of Brain Signals written by Saeid Sanei and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-28 with Technology & Engineering categories.

In this book, the field of adaptive learning and processing is extended to arguably one of its most important contexts which is the understanding and analysis of brain signals. No attempt is made to comment on physiological aspects of brain activity; instead, signal processing methods are developed and used to assist clinical findings. Recent developments in detection, estimation and separation of diagnostic cues from different modality neuroimaging systems are discussed. These include constrained nonlinear signal processing techniques which incorporate sparsity, nonstationarity, multimodal data, and multiway techniques. Key features: Covers advanced and adaptive signal processing techniques for the processing of electroencephalography (EEG) and magneto-encephalography (MEG) signals, and their correlation to the corresponding functional magnetic resonance imaging (fMRI) Provides advanced tools for the detection, monitoring, separation, localising and understanding of functional, anatomical, and physiological abnormalities of the brain Puts a major emphasis on brain dynamics and how this can be evaluated for the assessment of brain activity in various states such as for brain-computer interfacing emotions and mental fatigue analysis Focuses on multimodal and multiway adaptive processing of brain signals, the new direction of brain signal research

Advances In Non Invasive Biomedical Signal Sensing And Processing With Machine Learning

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Author : Saeed Mian Qaisar
language : en
Publisher: Springer Nature
Release Date : 2023-03-01

Advances In Non Invasive Biomedical Signal Sensing And Processing With Machine Learning written by Saeed Mian Qaisar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Computers categories.

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.

Artificial Intelligence And Multimodal Signal Processing In Human Machine Interaction

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Author : Abdulhamit Subasi
language : en
Publisher: Elsevier
Release Date : 2024-09-18

Artificial Intelligence And Multimodal Signal Processing In Human Machine Interaction written by Abdulhamit Subasi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-18 with Science categories.

Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction presents an overview of an emerging field that is concerned with exploiting multiple modalities of communication in both Artificial Intelligence and Human-Machine Interaction. The book not only provides cross disciplinary research in the fields of multimodal signal acquisition and sensing, analysis, IoTs (Internet of Things), Artificial Intelligence, and system architectures, it also evaluates the role of Artificial Intelligence I in relation to the realization of contemporary Human Machine Interaction (HMI) systems.Readers are introduced to the multimodal signals and their role in the identification of the intended subjects, mental state and the realization of HMI systems are explored, and the applications of signal processing and machine/ensemble/deep learning for HMIs are assessed. A description of proposed methodologies is provided, and related works are also presented. This is a valuable resource for researchers, health professionals, postgraduate students, post doc researchers and faculty members in the fields of HMIs, Brain-Computer Interface (BCI), Prosthesis, Computer vision, and Mental state estimation, and all those who wish to broaden their knowledge in the allied field. - Covers advances in the multimodal signal processing and artificial intelligence assistive HMIs - Presents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective HMI (Human Machine Interaction) system - Presents different aspects of the multimodal signals, from the sensing to analysis using hardware/software, and making use of machine/ensemble/deep learning in the intended problem-solving

Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques

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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2019-03-16

Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Medical categories.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. - Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction - Explains how to apply machine learning techniques to EEG, ECG and EMG signals - Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

Learning Approaches In Signal Processing

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Author : Francis Ring
language : en
Publisher: CRC Press
Release Date : 2018-12-07

Learning Approaches In Signal Processing written by Francis Ring and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Computers categories.

Coupled with machine learning, the use of signal processing techniques for big data analysis, Internet of things, smart cities, security, and bio-informatics applications has witnessed explosive growth. This has been made possible via fast algorithms on data, speech, image, and video processing with advanced GPU technology. This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc. The applications include super-resolution imaging, fringe projection profilometry, human activities detection/capture, gesture recognition, spoken language processing, cooperative networks, bioinformatics, DNA, and healthcare.

Artificial Intelligence Applications For Brain Computer Interfaces

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Author : Abdulhamit Subasi
language : en
Publisher: Elsevier
Release Date : 2025-01-10

Artificial Intelligence Applications For Brain Computer Interfaces written by Abdulhamit Subasi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-10 with Science categories.

Artificial Intelligence Applications for Brain-Computer Interfaces focuses on the advancements, challenges, and prospects of future technologies involving noninvasive brain-computer interfaces (BCIs). It includes the processing and analysis of multimodal signals, integrated computation-acquisition devices, and implantable neuro techniques. This book not only provides cross-disciplinary research in BCI but also presents divergent applications on telerehabilitation, emotion recognition, neuro-rehabilitation, cognitive workload assessments, and ambient assisted living solutions. In 15 chapters, this book describes how BCIs connect the brain with external devices like computers and electronic gadgets. It analyzes the neural signals from the brain to obtain insights from the brain patterns using multiple noninvasive wearable sensors. It gives insight into how sensor outcomes are processed through machine-intelligent models to draw inferences. Each chapter starts with the importance, problem statement, and motivation. A description of the proposed methodology is provided, and related works are also presented. Each chapter can be read independently, and therefore, the book is a valuable resource for researchers, health professionals, postgraduate students, postdoc researchers, and academicians in the fields of BCI, prosthesis, computer vision, and mental state estimation, and all those who wish to broaden their knowledge in the allied field. - Focuses on the advancements, challenges, and prospects for future technologies over noninvasive brain computer interfaces (BCIs), including the processing and analysis of multimodal signals, integrated calculation-acquisition devices, and implantable technologies. - Presents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective BCIs. - Assists in understanding the predominance of BCI technology in various applications.

Artificial Intelligence Enabled Signal Processing Based Models For Neural Information Processing

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Author : Rajesh Kumar Tripathy
language : en
Publisher: CRC Press
Release Date : 2024-06-06

Artificial Intelligence Enabled Signal Processing Based Models For Neural Information Processing written by Rajesh Kumar Tripathy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-06 with Technology & Engineering categories.

The book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book: Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface Highlights the latest machine learning and deep learning methods for neural signal processing Discusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysis Showcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniques It is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.

Signal Processing For Intelligent Sensor Systems With Matlab

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Author : David C. Swanson
language : en
Publisher: CRC Press
Release Date : 2011-07-21

Signal Processing For Intelligent Sensor Systems With Matlab written by David C. Swanson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-21 with Computers categories.

Signal Processing for Intelligent Sensors with MATLAB, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections:

Advanced Methods In Biomedical Signal Processing And Analysis

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Author : Kunal Pal
language : en
Publisher: Academic Press
Release Date : 2022-09-07

Advanced Methods In Biomedical Signal Processing And Analysis written by Kunal Pal and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-07 with Technology & Engineering categories.

Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. - Gives advanced methods in signal processing - Includes machine and deep learning methods - Presents experimental case studies

Signal Processing For Intelligent Sensor Systems

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Author : David C. Swanson
language : en
Publisher: CRC Press
Release Date : 2000-04-18

Signal Processing For Intelligent Sensor Systems written by David C. Swanson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-04-18 with Technology & Engineering categories.

"Integrates a broad range of physics, algorithms, and sensing techniques for development of intelligent systems. Highlights adaptive least-squared error modeling. Covers complex sampling, physical system modeling using digital filters, frequency domain processing, beamforming, and much more."