Brain computer interface Abstract:
A brain-computer interface (BCI), also referred to as a mind-machine interface (MMI) or a brain-machine interface (BMI), provides a non-muscular channel of communication between the human brain and a computer system. With the advancements in low-cost electronics and computer interface equipment, as well as the need to serve people suffering from disabilities of neuromuscular disorders, a new field of research has emerged by understanding different functions of the brain. The electroencephalogram (EEG) is an electrical activity generated by brain structures and recorded from the scalp surface through electrodes. Researchers primarily rely on EEG to characterise the brain activity, because it can be recorded non-invasively by using portable equipment. The EEG or the brain activity can be used in real time to control external devices via a complete BCI system. A typical BCI scheme generally consists of a data acquisition system, pre-processing of the acquired signals, feature extraction process, classification of the features, post-processing of the classifier output, and finally the control interface and device controller. The post-processed output signals are translated into appropriate commands so as to control output devices, with several applications such as robotic arms, video games, wheelchair etc.
Brain-Computer Interfacing: An Introduction
The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this idea 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.
Reference Link:
https://ieeexplore.ieee.org/document/7449615
http://bci.cs.washington.edu/
https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface
https://www.atera.com/blog/cognitive-systems-teaching-technology-to-learn/
