Eeg-Based Experiment Design for Major Depressive Disorder

Machine Learning and Psychiatric Diagnosis
Erscheinungsjahr 2019
ISBN: 978-0-12-817420-3
Verlag: Elsevier Science

Buch, Englisch, 254 Seiten, Format (B × H): 152 mm x 226 mm, Gewicht: 431 g

EEG-Based Experiment Design for Major Depressive Disorder: Machine Learning and Psychiatric Diagnosis introduces EEG-based machine learning solutions for diagnosis and assessment of treatment efficacy for a variety of conditions. With a unique combination of background and practical perspectives for the use of automated EEG methods for mental illness, it details for readers how to design a successful experiment, providing experiment designs for both clinical and behavioral applications. This book details the EEG-based functional connectivity correlates for several conditions, including depression, anxiety, and epilepsy, along with pathophysiology of depression, underlying neural circuits and detailed options for diagnosis. It is a necessary read for those interested in developing EEG methods for addressing challenges for mental illness and researchers exploring automated methods for diagnosis and objective treatment assessment.

Zielgruppe

<p>Graduate students in biological and biomedical sciences and engineering, neuroscientists, neurobiologists, biomedical engineers, post-doctoral fellows, researchers</p>

Autoren/Hrsg.

Malik, Aamir Saeed

Mumtaz, Wajid

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Psychiatrie, Sozialpsychiatrie, Suchttherapie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe

Inhaltsverzeichnis

1. Introduction: Depression and Challenges2. EEG Fundamentals3. EEG-Based Brain Functional Connectivity and Clinical Implications4. Pathophysiology of Depression5. Using EEG for Diagnosing and Treating Depression6. Neural Circuits and EEG Based Neurobiology for Depression7. Design of EEG Experiment for Assessing MDD8. EEG-based Diagnosis of Depression9. EEG-based Treatment Efficacy Assessment Involving Depression

Über Autor(innen)

Mumtaz, Wajid
Dr. Wajid Mumtaz has completed his PhD degree from Center for Intelligent Signal and Imaging Research (CISIR), Universiti Teknologi PETRONAS (UTP), Malaysia in 2017. He continued as post doctorate researcher from 2017 to 2018 from the same institution. Recently, he has joined University of West Bohemia, located in Pilsen, Czech Republic as a Postdoctoral Research Fellow. In addition, he accomplished his masters in computer engineering and bachelor in electrical engineering from University of Engineering and Technology, Taxila, Pakistan in 2009 and 2005, respectively. His research interest includes biomedical signal processing and applications, machine learning application to medical problem solving, such as diagnosis and treatment assessment, adaptive noise cancellation for real-world data, such as Electroencephalogram (EEG).

Malik, Aamir Saeed
Dr. Malik has a B.S. in Electrical Engineering from University of Engineering and Technology, Lahore, Pakistan, M.S in Nuclear Engineering from Quaid-i-Azam University, Islamabad, Pakistan, another M.S in Information & Communication and Ph.D in Information & Mechatronics from Gwangju Institute of Science & Technology, Gwangju, Korea. He has more than 15 years of research experience and has worked for IBM, Hamdard University, Government of Pakistan, Yeungnam University and Hanyang University in Korea. He is currently working as Associate Professor at Universiti Teknologi PETRONAS in Malaysia. He is fellow of IET and senior member of IEEE. He is board member of Asia Pacific Neurofeedback Association (APNA) and member of Malaysia Society of Neuroscience (MSN). His research interests include neuro-signal & neuro-image processing and neuroscience big data analytics. He is author of 3 books and a number of international journal and conference papers with more than 1000 citations and cumulative impact factor of more than 180. He has a number of patents, copyrights and awards.