-6%-6%
Availability: Άμεσα Διαθέσιμο

Advanced Electroencephalography Analytical Methods. Fundamentals, Acquisition, and Applications

Gaetano Gargiulo, Ganesh Naik, Wellington Pinheiro dos Santos
ISBN: 9781032171708
ISBN: 9781032171708
Εκδόσεις:
Διαστάσεις 23 × 15 cm
Μορφή

Εκδόσεις

Ημ. Έκδοσης

Σελίδες

Έκδοση

Κύριος Συγγραφέας

, ,

119,00€(Περιλαμβάνεται ΦΠΑ 6%)

Διαθεσιμότητα: Υπό έκδοση

Κατηγορίες: ,

Περιγραφή

Advanced Electroencephalography Analytical Methods: Fundamentals, Acquisition, and Applications presents the theoretical basis and applications of electroencephalography (EEG) signals in neuroscience, involving signal analysis, processing, signal acquisition, representation, and applications of EEG signal analysis using non-linear approaches and machine learning. It explains principles of neurophysiology, linear signal processing, computational intelligence, and the nature of signals including machine learning. Applications involve computer-aided diagnosis, brain-computer interfaces, rehabilitation engineering, and applied neuroscience.

This book:

    • Includes a comprehensive review on biomedical signals nature and acquisition aspects.
    • Focuses on selected applications of neurosciences/cardiovascular/muscle-related biomedical areas.
    • Provides a machine learning update to a classical biomedical signal processing approach.
    • Explains deep learning and application to biomedical signal processing and analysis.
    • Explores relevant biomedical engineering and neuroscience state-of-the-art applications.

This book is intended for researchers and graduate students in biomedical signal processing, electrical engineering, neuroscience, and computer science.

Περιεχόμενα

Section 1: EEG Applications and Challenges

1. Diagnostic Applications of EEg Signal Patterns in Neuroscience

Arun Sasidharan, Sumit Sharma, Vrinda M, Kusumika Krora Dutta, and Chetan S Mukundan

2. Deep Learning Techniques for Automatic Sleep Pattern Identification and Disorder Evaluation Using EEG Signals

K R Shylaja

3. Recent Trends in EEG-Based MI and SSVEP Brain-Computer Interface Applications: A Review

Sheikh Farhana Binte Ahmed, Saiful Islam Leon, Jarina Akter, Maisha Anjum, Nazmus Sakib, and Md. Kafiul Islam

4. Recent Trends in EEG-Based P300, Neuromarketing and E-Sports Brain-Computer Interface Applications: A Review

Sheikh Farhana Binte Ahmed, Mehedi Hasan, Md. Tawhid Islam Opu, Faisal Bin Shahin, Md. Ahsan-Ul Kabir Shawon, Tasnuva Faruk, and Md. Kafiul Islam

Section 2: EEG – Signal Processing

5. Significance of Fourier Transform for Epileptic EEG Signals Analysis

Pooja, Sourav Maity, and Karan Veer

6. Alternative treatment with Non-Periodic Acoustic Stimulation for Pharmacoresistant Epileptic Patients: An Exploratory Study

Juliana Carneiro Gomes, Marília Marinho de Lucena, Jeniffer Emídio de Almeida Albuquerque, Igor Tchaikovsky Mello de Oliveira, Belmira Lara da Silveira Andrade da Costa, Wellington Pinheiro dos Santos, and Marcelo Cairrão

7. Artifacts Removal in Electroencephalogram (EEG) Signals

Jammisetty Yedukondalu, M Krishna Chaitanya, and Lakhan Dev Sharma

8. Multi-Channel and Multi-Label Decision-Making System (MCL-DMS) for Sleep Stage and Sleep Disorder Recognition from EEG Signals

Yi-Hsuan Cheng, Margaret Lech, and Richardt H Wilkinson

Section 3: EEG – Signal Classification

9. Analyzing and Decoding Natural Reach and Grasp Action Using Convolutional Neural Network

Abida Nazir, Asim Waris, Shafiq Alam, Shafaq Mushtaq, Rabia Nazir, and Imran Khan Niazi

10. Classification of Motor Imagery EEG Signals Based on Sparse Representations of Empirical Mode Decomposition Features

José Antonio Alves de Menezes, Juliana Carneiro Gomes, Vitor de Carvalho Hazin, Júlio César Sousa Dantas, Marcelo Cairrão Araújo Rodrigues, Pedro Luís Gurgel Nogueira, and Wellington Pinheiro dos Santos

11. Prediction of Onset of Seizures from EEG Signals Using ML Techniques

Sumathi A, Priya R Sankpal, Jyoti R Munavalli, and Anusha A N

Σχετικά προϊόντα