
EEG-Based Experiment Design for Major Depressive Disorder
Machine Learning and Psychiatric Diagnosis
- 1st Edition - May 16, 2019
- Imprint: Academic Press
- Authors: Aamir Saeed Malik, Wajid Mumtaz
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 7 4 2 0 - 3
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 7 4 2 1 - 0
EEG-Based Experiment Design for Major Depressive Disorder: Machine Learning and Psychiatric Diagnosis introduces EEG-based machine learning solutions for diagnosis and assessmen… Read more
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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.
- Written to assist in neuroscience experiment design using EEG
- Provides a step-by-step approach for designing clinical experiments using EEG
- Includes example datasets for affected individuals and healthy controls
- Lists inclusion and exclusion criteria to help identify experiment subjects
- Features appendices detailing subjective tests for screening patients
- Examines applications for personalized treatment decisions
Graduate students in biological and biomedical sciences and engineering, neuroscientists, neurobiologists, biomedical engineers, post-doctoral fellows, researchers
- Edition: 1
- Published: May 16, 2019
- Imprint: Academic Press
- Language: English
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Aamir Saeed Malik
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