Neural engineering is an emerging and fast-moving interdisciplinary research area that combines engineering with (a) electronic and photonic technologies, (b) computer science, (c) physics, (d) chemistry, (e) mathematics, and (f) cellular, molecular, cognitive, and behavioral neuroscience. This helps us understand the organizational principles and underlying mechanisms of the biology of neural systems and to further to study the behavioral dynamics and complexity of neural systems in nature. The field of neural engineering deals with many aspects of basic and clinical problems associated with neural dysfunction, including (i) the representation of sensory and motor information, (ii) electrical stimulation of the neuromuscular system to control muscle activation and movement, (iii) the analysis and visualization of complex neural systems at multiscale from the single cell to system levels to understand the underlying mechanisms, (iv) development of novel electronic and photonic devices and techniques for experimental probing, the neural simulation studies, (v) the design and development of human-machine interface systems and artificial vision sensors, and (vi) neural prosthesis to restore and enhance the impaired sensory and motor systems and functions. To highlight this emerging discipline, Dr. Ayman El-Baz and Dr. Jasjit Suri have developed Advances in Neural Engineering, covering the broad spectrum of neural engineering subfields and applications. This Series includes 7 volumes in the following order: Volume 1: Signal Processing Strategies, Volume 2: Brain-Computer Interfaces, Volume 3: Diagnostic Imaging Systems, Volume 4: Brain Pathologies and Disorders, Volume 5: Computing and Data Technologies, Volume 6: Advanced Brain Imaging Techniques and Volume 7: Neural Science Ethics. Volume 1 provides a comprehensive review of dominant feature extraction methods and classification algorithms in the brain-computer interfaces for motor imagery tasks. The authors discuss existing challenges in the domain of motor imagery brain-computer interface and suggest possible research directions.
Table of Contents
1. Framework for segmentation, optimization, and recognition of multivariate brain tumors. 2. The Neural Circuitry of PTSD An RDOC Approach 3. CNN-based Artifact Recognition from Independent Components of EEG Signals 4. Deep multimodal representation learning for non-invasive neural speech decoding 5. Neural signals processing using deep learning for diagnosis of cognitive disorders 6. Brain tumor recognition using Semi Supervised Generative Adversarial Network 7. Multivariate adaptive signal decomposition techniques and their applications to EEG signal processing: An introduction 8. Split Learning for Human Activity Recognition 9. Machine Learning Approaches for Epilepsy Analysis in Current Clinical Trials 10. Brainwave and Head Motion Control of a Smart Home for Disabled People 11. Blind source separation methods for motor imagery-based brain-computer interfaces 12. Advancing neural engineering: hierarchical control strategies with human-centered focus for hand prosthetics 13. Advances in non-invasive EEG-Based brain-computer interfaces: signal acquisition, processing, emerging approaches, and applications
Authors
Ayman S. El-Baz University of Louisville, USA. Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master's degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents). Jasjit Suri Chairman, AtheroPoint LLC, USA.Dr. Jasjit Suri, PhD, MBA, is an innovator, visionary, scientist, and internationally known world leader. Dr Suri received the Director General's Gold medal in 1980 and Fellow of (i) American Institute of Medical and Biological Engineering, awarded by the National Academy of Sciences, Washington DC, (ii) Institute of Electrical and Electronics Engineers, (iii) American Institute of Ultrasound in Medicine, (iv) Society of Vascular Medicine, (v) Asia Pacific Vascular Society, and (vi) Asia Association of Artificial Intelligence. Dr. Suri was honored with life time achievement awards by Marcus, NJ, USA and Graphics Era University, Dehradun, India. He has published nearly 300 peer-reviewed Artificial Intelligence articles, nearly 2000 Google Scholar Publications, 100 books, and 100 innovations/trademarks leading to an H-index of nearly 100 with about 43,000 citations. He has held positions as chairman of AtheroPoint, CA, USA, IEEE Denver section, Colorado, USA, and advisory board member to healthcare industries and several universities in the United States of America and abroad.
