Brain-Computer Interface

•It explores the idea that language serves as a model for how the human mind works, and how it can be used to develop brain-computer interfaces (BCIs) that facilitate communication between the brain and external devices.

•It provides an overview of methods used to handle artifacts in electroencephalography (EEG) signals, and discusses the use of a fuzzy inference system to identify pain in EEG signals.

•It explores the use of unsupervised machine learning algorithms to analyze multivariate real-time series data in BCIs, with the potential to improve the accuracy and efficiency of these systems.

•It discusses the potential therapeutic effect of infra-low-frequency neurofeedback training on children and adolescents with attention deficit hyperactivity disorder (ADHD) and provides an overview of research exploring the relationship between entropy and the emotional brain.

•This book discusses the use of wavelet features and various machine learning methods to evaluate steady-state visually evoked potentials-based BCIs, with the potential to improve the accuracy and efficiency of these systems.

•It explores the use of a brain-computer interface drone, which can be controlled by the user's thoughts and may have potential applications in areas such as search and rescue, surveillance, and agriculture.

•This book is an excellent reference for scientists, researchers, neurologists, psychiatrists, and other medical professionals, engineers, technologists and the general public may be interested in learning about the latest research findings, as well as the potential benefits and risks of BCI technology.