To understand how a Brain-Computer Interface (BCI) works, one has to know how the brain works. Every time we do anything, small electrical signals move from neuron to neuron as a result of differences in electric potential carried by ions in the membrane of the neurons. As the electrical signal is sent through the dendrite and along the axon, scientists are able to interpret the signals.
Brain-Computer Interfaces can vary on how invasive they are. Electroencephalograph can be attached to the scalp, which is not invasive at all. However, the skull blocks a lot of electrical signal, making the results not as strong. For better signals, electrodes can be implanted into the gray matter on the surface of the brain. However, scar tissue can form, which ends up blocking the signal too. The electrodes measure the difference in voltage between the neurons.
1. Signal acquisition
2. Signal Pre-Processing
3. Signal Classification
4. Computer Interaction
First the EEG signals are obtained (step 1) through either invasive of non-invasive means. Once the signals are acquired, they are cleaned (step 2) and processed to find which mental task the subject is thinking about (step 3). Once they are classified, the appropriate algorithm interprets them by the computer (step 4). The image below provides a general overview of this process in regards to moving a cursor across a computer screen using thought alone.
source: computer.howstuffworks.com
Several methods of applications use operant condition on spontaneous EEG signals to control the BCI. For example, the signal mu is a spontaneous EEG wave associated with motor activities and is mostly recorded in the sensorimotor cortex. It doesn’t require that subject have any remaining motor control, making it essential for BCI operation in paralyzed or locked-in patients. Jonathan Wolpaw and his colleagues, train individuals to, the course of many sessions, move a cursor on a computer screen by controlling the amplitude of their mu waves. Essentially, signal processing is the crucial part of BCI development and functioning.
The modern-day use of BCI technology is dependent on interdisciplinary cooperation. A lot of progress has been made, to the benefit of a lot of people who need it. Developments in the technology have only been made over the last decade, making this project still young in years. A lot of progress has been made, but the search for a more developed and efficient BCI is ongoing.
[1] Ochoa, Jorge B. "EEG Signal Classification for the Brain: Computer Interface Application." N. pag. 28 Mar. 2002. Web. 16 Nov. 2009. .
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