Advances in Neural Engineering: Brain-Computer Interfaces, Volume Two covers the broad spectrum of neural engineering subfields and applications. The set provides a comprehensive review of dominant feature extraction methods and classification algorithms in the brain-computer interfaces for motor imagery tasks. The book's authors discuss existing challenges in the domain of motor imagery brain-computer interface and suggest possible research directions. The field of neural engineering deals with many aspects of basic and clinical problems associated with neural dysfunction, including sensory and motor information, stimulation of the neuromuscular system to control muscle activation and movement, analysis and visualization of complex neural systems, and more.

• Presents Neural Engineering techniques applied to Signal Processing, including feature extraction methods and classification algorithms in BCI for motor imagery tasks
• Includes in-depth technical coverage of disruptive neurocircuitry, including neurocircuitry of stress integration, role of basal ganglia neurocircuitry in pathology of psychiatric disorders, and neurocircuitry of anxiety in obsessive-compulsive disorder
• Covers neural signal processing data analysis and neuroprosthetics applications, including EEG-based BCI paradigms, EEG signal processing in anesthesia, neural networks for intelligent signal processing, and a variety of neuroprosthetic applications
• Written by engineers to help engineers, computer scientists, researchers, and clinicians understand the technology and applications of signal processing