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Brain-Computer Interfaces
Brain-computer interfaces (BCIs) are devices which connect the brain to a computer. BCIs read in electrical signals from neurons in the brain and then pass these signals to an external device for computation. Currently BCIs are used primarily to help aid either communication or physical movement, though recent research has tried to use BCIs for other purposes such as treating learning disorders or researching sleeping patterns. Other names for Brain-Computer Interfaces are human-machine interfaces (HMI) and neural interfaces.
History
Brain-computer interface research first started at UCLA in the 1970s. The basic idea behind BCIs was discovered when, using the theory of operant conditioning, researchers found that monkeys could be taught to control neuron firing. The idea of reconstructing motor movement from a neuron action potential dates back to the 1970s as well [1]. Apostolos Georgopoulos started the resurgence of BCI research in the 1980s when he discovered a relationship between the movement of arms and neurological firing patterns. Yet another major advance occurred in the 1990s when direct interfaces with computers were further developed and motor control was refined for BCI use.
The hardware and functioning of BCIs has continued to develop. Modern technology allows BCIs to use more electrodes for reading brain signals, while electroencephalograms became a more viable option for BCI use when computing hardware got more powerful[2].
Types of BCIs
BCIs can be classified into different groups based on how they are applied and their intended purpose. The two main categories of BCIs are: invasive and non-invasive. Invasive BCIs are attached directly to the brain to read in signals and require surgery for application. Non-invasive BCIs do not require entry to the brain and instead are placed on the top of the head or scalp and read neuron impulses there. These categories can be divided even further based on their intended use.
Categories based on use are: basic research, clinical, and commercial. Basic research BCIs are less specialized than other types and focus primarily on detecting and interpreting brain signals. These use electroencephalograms or electrocorticography to read in signals. Clinical BCIs are made with specific goals in mind and require more specialized hardware that depends on the intended purpose. Clinical BCIs might be used for tasks such as assisting speech production or stroke recovery. Consumer products are intended for sales to the general population and are typically less powerful and expensive than their research based counterparts[3].
Function
BCIs have two major components, the hardware itself and the user's brain[6]. The brain is responsible for generating the original message. All hardware consists of input methods, output methods, and a translating algorithm. The input is the method the BCI uses to read in the activity, typically these are the sensors reading neuron activity. The translating algorithm is used to convert signals read in from the brain into a usable output for the device. Since a lot of signals read by a BCI are not relevant to the desired output, the translation algorithm should be able to sift through the unnecessary signals and find only the relevant parts. Translating algorithms use a large body of equations and other forms of data analysis to properly read inputs. Some algorithms use an adaptive feature to change the analysis of the signal based on previous inputs from the user. The output of a BCI is the end goal of the device, for example moving a cursor or typing a message.
BCIs can also contain some implementation-specific features. These include such things as a signal for turning a device on or off or a signal amplifier. A signal amplifier is used if the method of signal detection is weak and works by increasing the strength of signals sent from the brain. Individual BCIs differ in the rate of information processing, translating algorithm used, as well as input and output formats.
The way a BCI functions is, in simplest form: the brain creates a signal, the input methods read the signal, the translation algorithm turns the input into a readable format and translates this to an appropriate action, and the output method carries out the desired action.
Applications
BCIs can be used for a variety of purposes. BCIs have been paired with tractors to allow a user to steer and control a vehicle with their mind. This was done using an Emotiv BCI and was only a few centimeters less accurate than manual or GPS-guided steering [1]. BCIs have also been used to type messages on a computer or as a way to interact in the massively-multiplayer online world of Second-life, using both speech generation and motor imagery to allow the player to navigate and communicate with other players in a virtual world. Another use is allowing users to interact with smart-homes so they can control things such as light or heating using a BCI.
More recent research has involved using brain-computer-brain interfaces. These devices are modified BCIs that have an additional link from the computer back to the brain. In one experiment, monkeys were able to control a virtual hand as if it were their own using their brain and were even able to tell a differences in textures in virtual objects felt by the virtual hand. Researchers claim that eventually “quadriplegic patients will take advantage of this technology not only to move their arms and hands and to walk again, but also to sense the texture of objects placed in their hands”[4]
Consumer Devices
A small number of BCIs have been developed for consumer purchase and use. The following can be bought for personal use:
Mindwave- Manufactured by Neurosky, released in March 2011.
MindFlex- Manufactured by Mattel, released in December 2009.
Emotiv EPOC- Manufactured by Emotiv, released in December 2009.
MindSet- Manufactured by Neurosky, released in March 2007.
Some of these contain SDKs for software developers to write new applications to allow the devices greater integration with computers. Other devices are intended as games and are more limited in what they are capable of.
References
- ↑ 1.0 1.1 Melwater, "The World's First Brain-Computer Interface + History of BCI", Make History
- ↑ "Brain-Computer Interface Technology: A Review of the First International Meeting", IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, June 2000
- ↑ Gugler et al (February 2011), Recent Advances in Brain-Computer Interface Systems
- ↑ Doherty et al (October 5, 2011), "Active tactile exploration using a brain–machine–brain interface", Nature