The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this a reality, opening the door to restoring and potentially augmenting human physical and mental capabilities. Medical applications such as cochlear implants for the deaf and deep brain stimulation for Parkinson’s disease are becoming increasingly commonplace. Brain- computer interfaces (BCIs) (also known as brain- machine interfaces or BMIs) are now being explored in applications as diverse as security, lie detection, alertness monitoring, telepresence, gaming, education, art, and human augmentation. This introduction to the field is designed as a textbook for upper- level undergraduate and first year graduate courses in neural engineering or brain- computer interfacing for students from a wide range of disciplines. It can also be used for self- study and as a reference by neuroscientists, computer scientists, engineers, and medical practitioners. Key features Essential background in neuroscience, brain recording and stimulation technologies, signal processing, and machine learning.
An incubation period for the BCI researcher. This book is foundational. From page 1 you're meticulously taken to a higher understanding of Brain-Computer Interfacing. Though, this book is an exceptional introduction to the field, it would help the reader to have background knowledge in the fields of computational neuroscience and computer architecture. Regardless of primer knowledge, any reader with a genuine interest in the subject should not be disappointed.
This book is a reasonably comprehensive primer to brain interfacing research. Some concepts treated in great detail and explained lucidly. The brief section on hierarchical BCIs was especially thought-provoking. Neuroscience, signal processing, and the history and types of BCIs are treated in-depth, with some gaps in the areas of materials//bioelectronics. Like most textbooks, this is a bit dated, considering the rate at which the field is evolving. Nevertheless, a worthwhile introduction because of its comprehensive big-picture approach.
Good (though out-dated) overview of different BCIs & their empirical methods. From low level neuronal chemistry, signal processing, to BCI types and highlights of their existing research.