"Brain-Computer Interface" ed. by Vahid Asadpour, Andries Engelbrecht

The book provides a comprehensive summary of conventional and novel methods for processing brain signals. The chapters cover a range of topics including noninvasive and invasive signal acquisition, signal processing methods, deep learning approaches, and implementation of brain-computer interfacing (BCI) in experimental problems.

Brain-computer interfacing (BCI) with the use of advanced artificial intelligence identification is a rapidly growing new technology that allows a silently commanding brain to manipulate devices ranging from smartphones to advanced articulated robotic arms when physical control is not possible. BCI can be viewed as a collaboration between the brain and a device via the direct passage of electrical signals from neurons to an external system.

Contents
1. Language as the Working Model of Human Mind
2. A Brief Summary of EEG Artifact Handling
3. Pain Identification in Electroencephalography Signal Using Fuzzy Inference System
4. Multivariate Real Time Series Data Using Six Unsupervised Machine Learning Algorithms
5. Therapeutic Effect of Infra-Low-Frequency Neurofeedback Training on Children and Adolescents with ADHD
6. Training the Conductor of the Brainwave Symphony: In Search of a Common Mechanism of Action for All Methods of Neurofeedback
7. Entropy and the Emotional Brain: Overview of a Research Field
8. Evaluating Steady-State Visually Evoked Potentials-Based Brain-Computer Interface System Using Wavelet Features and Various Machine Learning Methods
9. Brain Computer Interface Drone

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