Neural Engineering Techniques for Autism Spectrum Disorder: Volume 1: Imaging and Signal Analysis - Tapa blanda

Acerca de los autores

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).

Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.

De la contraportada

Neural Engineering for Autism Spectrum Disorder, Volume 1: Imaging and Signal Analysis Techniques presents the latest advances in neural engineering and biomedical engineering applied to clinical diagnosis and treatment of Autism Spectrum Disorder (ASD). Advances in the role of neuroimaging, magnetic resonance spectroscopy, sMRI, fMRI, DTI, and video analysis of sensory-motor and social behaviors and suitable data analytics useful for clinical diagnosis and research applications for Autism Spectrum Disorder are covered, including relevant case studies. The application of brain signal evaluation, EEG analytics, fuzzy model, and temporal fractal analysis of rest state BOLD signals and brain signals are presented for detection and estimation of the degree of ASD. Neural Engineering for Autism Spectrum Disorder is presented in two volumes. Volume 1: Imaging and Signal Analysis Techniques includes two Parts: Autism and Medical Imaging, and Autism and Signal Analysis. Volume 2: Diagnosis and Treatment includes two Parts: Autism and Clinical Analysis: Diagnosis, Autism and Clinical Analysis: Treatment.