Eeg Signal Processing And Feature Extraction

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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.

Autism Eeg Signal Processing Feature Extraction And Deep Learning

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Author : Melinda, Na Li, Erick Purwanto, Muliyadi, Yunidar, Syahrul
language : en
Publisher: Syiah Kuala University Press
Release Date : 2024-10-18

Autism Eeg Signal Processing Feature Extraction And Deep Learning written by Melinda, Na Li, Erick Purwanto, Muliyadi, Yunidar, Syahrul and has been published by Syiah Kuala University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-18 with Medical categories.

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.

Eeg Signal Processing

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Author : Wai Yie Leong
language : en
Publisher: Healthcare Technologies
Release Date : 2019-03

Eeg Signal Processing written by Wai Yie Leong and has been published by Healthcare Technologies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03 with Technology & Engineering categories.

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.

Cognitive Systems And Signal Processing

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Author : Fuchun Sun
language : en
Publisher: Springer Nature
Release Date : 2021-05-04

Cognitive Systems And Signal Processing written by Fuchun Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-04 with Computers categories.

This book constitutes the refereed post-conference proceedings of the 5th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2020, held in Zhuhai, China, in December 2020. The 59 revised papers presented were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections on algorithm; application; manipulation; bioinformatics; vision; and autonomous vehicles.

Electroencephalogram Signal Analysis

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Author : Salah Hamdi
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2022-07-06

Electroencephalogram Signal Analysis written by Salah Hamdi and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-06 with Medical categories.

This book will assist medical diagnosis and aid clinical decision-making. It shows that neuronal networks, machine learning, and VAR models proved useful for EEG signal analysis, and details EEG signal processing methods. The book also highlights how to use learning machine for epileptic cerebral activity localisation, and details a parallel implementation for EEG artefact rejection.

Eeg Signal Processing A Machine Learning Based Framework

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Author : R. John Martin
language : en
Publisher: Ashok Yakkaldevi
Release Date : 2022-01-31

Eeg Signal Processing A Machine Learning Based Framework written by R. John Martin and has been published by Ashok Yakkaldevi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-31 with Art categories.

1.1 Motivation Analysis of non-stationary and non-linear nature of signal data is the prime talk in signal processing domain today. On employing biomedical equipments huge volume of physiological data is acquired for analysis and diagnostic purposes. Inferring certain decisions from these signals by manual observation is quite tedious due to artefacts and its time series nature. As large volume of data involved in biomedical signal processing, adopting suitable computational methods is important for analysis. Data Science provides space for processing these signals through machine learning approaches. Many more biomedical signal processing implementations are in place using machine learning methods. This is the inspiration in adopting machine learning approach for analysing EEG signal data for epileptic seizure detection.

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.

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

Brain Seizure Detection And Classification Using Eeg Signals

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Author : Varsha K. Harpale
language : en
Publisher: Academic Press
Release Date : 2021-09-09

Brain Seizure Detection And Classification Using Eeg Signals written by Varsha K. Harpale and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Science categories.

Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals. In addition, the authors also present new methods of feature extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types, specifically epileptic and Non-Epileptic Seizures (NES). The performance of the system is compared with existing methods of feature extraction using Wavelet Transform (WT) and Empirical Wavelet Transform (EWT). The book's objective is to analyze the EEG signals to observe abnormalities of brain activities called epileptic seizure. Seizure is a neurological disorder in which too many neurons are excited at the same time and are triggered by brain injury or by chemical imbalance. - Presents EEG signal processing and analysis concepts with high performance feature extraction - Discusses recent trends in seizure detection, prediction and classification methodologies - Helps classify epileptic and non-epileptic seizures where misdiagnosis may lead to the unnecessary use of antiepileptic medication - Provides new guidance and technical discussions on feature-extraction methods and feature selection methods based on One-way ANOVA, along with high performance machine learning classifiers for classification of EEG signals in normal and epileptic EEG signals, and new methods of feature extraction developed by the authors, including Singular Spectrum-Empirical Wavelet

Signal Processing Techniques For Knowledge Extraction And Information Fusion

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Author : Danilo Mandic
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-23

Signal Processing Techniques For Knowledge Extraction And Information Fusion written by Danilo Mandic and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-23 with Technology & Engineering categories.

This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.