BCIs are often categorized according to the type of mental activity the users have to perform to send messages or commands. Most BCIs rely on one of three types of mental activities:

Motor Imagery

The subject imagines performing an action, like squeezing a ball. The EEG data are classified online, and the result is graphically presented to the subject as a horizontal bar on the screen that moves right if right hand motor imagery is detected or moves left if left hand motor imagery is detected. The continuous feedback helps the subject to train the motor imageries leading to a correct classification. To improve the performance the classifier should be updated after some successful sessions. Offline analysis of the recorded data supports feature optimization.

Example Applications: Motor Rehabilitation, Ping Pong

Recently BCI systems were also used for motor rehabilitation purposes for stroke patients. The BCI system is used to measure the activation of the sensorimotor cortex to control external supporting robotic devices such as exoskeletons or orthotic devices. The robotic device has the purpose to move the limbs of the patient and this activates again the sensorimotor cortex. The activation can be seen as ERD/ERS changes in the EEG signals. A motor imagery based BCI system is again able to measure this ERD/ERS changes and can use it as control signal. Common Spatial Patterns overlaying the whole sensorimotor cortex help to gain faster and more accurate control and weight each electrode according to its importance. Instead of real robotic devices also virtual representations of body limbs can be used to activate the mirror neurons. g.tec offers a complete BCI research bundle for rehabilitation including a 32 channel BCI system and a Virtual Reality projection system. More information about BCI systems for rehabilitation purposes can be found under State-of-the-Art in BCI Research (Intec, 2011): BCI Award 2010 with sections from Infocomm Research, A*Star, Singapore and Keio University, Japan. Two of the 10 nominated BCI Award 2010 projects used BCI systems for rehabilitation purposes.

Everybody knows the famous Ping-Pong game that was played in the seventies on TV sets. In this example, two persons are connected to the BCI system and each one is controlling the paddle with motor imagery. The paddle moves upwards by left hand movement imagination and downwards by right hand movement imagination. The algorithm extracts EEG bandpower features in the alpha and beta ranges of two EEG channels per person. Therefore in total 4 EEG channels are analyzed and classified.

P300

The P300 is another type of brain activity that can be detected with the EEG. It was first discovered by Sutton [1]. The P300 is a brainwave component that occurs after a stimulus that is both important and relatively rare. In the EEG signal, the P300 appears as a positive wave 300 ms after stimulus onset. The electrodes are placed over the posterior scalp.

Example Applications: Spelling Device & Smart Home Device & Second Life

The P300 paradigm presents e.g. 36 letters in a 6 x 6 matrix on the computer monitor. Each letter (or row or column of letters) flashes in a random order, and the subject has to concentrate on the letter that he or she wants to communicate. As soon as the corresponding letter flashes, a P300 component is produced inside the brain. The algorithms analyze the EEG data and select the letter with the highest P300 component. Then, this letter is written onto the screen. Normally, between 2-15 flashes per letter are required to achieve a high accuracy. The number is dependent on many factors, including the electrode position used, the data processing parameters, and the individual height of the P300 response of the subject.

The BCI was connected to a Virtual Reality (VR) system. The virtual 3D representation of the smart home had different control elements (TV, music, windows, heating system, phone), and allowed the subjects to move through the apartment. Some tasks could be done, like playing music, watching TV, open doors, or moving around. Therefore, seven control masks were created: a light mask, a music mask, a phone mask, a temperature mask, a TV mask, a move mask and a "go to" mask. The controlling mask for the TV is shown.

g.tec implemented a BCI system based on the P300 principle. Therefore different symbols are arranged on a computer screen and are highlighted in a random order. If the subject focuses on one specific symbol that is flashing, the P300 should be elicited, and the BCI system can recognize this P300 and therefore the symbol. To control Second-Life, different masks (GUI with icons) were created for moving around, chatting, or other tasks specialized to each user's wishes.

Steady State Visual Evoked Potential (SSVEP)

Steady state visual evoked potentials (SSVEP)-based BCIs use several stationary oscillating light sources (e.g. flickering LEDs, or phase-reversing checkerboards), each of which oscillates at unique frequency. When a person gazes at one of these lights, or even focuses attention on it, then the EEG activity over the occipital lobe will show an increase in power at the corresponding frequency.

With four choices, anyone could easily move a robot forwards, backwards, to the left and to the right. Hence, in our SSVEP BCI, we have four lights. (Of course, SSVEP BCIs have been developed with more or less than four lights, depending mainly on how many commands are required.) All the user has to do now is to look at one specific flickering light (for example, the one which is assigned to the "move forward"-command). Our algorithms determine which EEG frequency component(s) are higher than normal, which reveals which light the user saw and thus which movement command the user wanted to send. This system also uses a "no-control" state. When the user does not look at any oscillating light, the robot doesn't move.

[1] S. Sutton, M. Braren, J. Zubin, and E. R. John, “Evoked-potential correlates of stimulus uncertainty,” Science, vol. 150, pp. 1187–1188, 1965.

You can find some additional basic information about BCIs at the future BNCI website.

In order to facilitate Brain-Computer Interface research in the clinical environment many of our customers want to use their clinical EEG/ECoG system in parallel to the BCI system. g.tec offers various solutions to connect clinical EEG machines and the g.tec Brain-Computer Interface system. Below there are two examples. g.tec's employees are prepared to find the best solution for existing systems togehter with our customers. Please contact  for an individual setup.

Depending on the clinical EEG/ECoG machine in principal two different connection options can be identified:

i) on the jackbox of the clinical system the EEG/ECoG analog signals are available via an additional D-sub type connector. Here the 1.5mm safety plugs coming from the EEG cap/ECoG grid are connected to the jackbox on the clinical machine. Then the g.tec connection cable connects via the parallel D-SUB type connector to the multi pole input sockets of up to 8 g.USBamp or one g.HIamp.

ii) the jackbox of the clinical system has no option for an additional connection. In this case the g.tec 64 channel breakout box can be connected to the clinical system instead of the original jackbox. Here the 1.5mm safety plugs coming from the EEG cap/ECoG grid are connected to the g.tec breakout box which is connected on one side to the clinical system and on the other side to the multi pole input sockets of up to 8 g.USBamp or one g.HIamp.

Example 1: On the clinical system the jackbox on the patient side has a parallel output option for EEG/ECoG signals via e.g. D-SUB type like connectors: Solution:  Connect the parallel output on the jackbox via the g.tec D-SUB type connection cable to the BCI system. Supported systems come from: BIOLOGIC, STELLATE, XLTEK

Example 2: On the clinical system there is no parallel output option on the jackbox available: detailed picture of the splitter boxes and connection cables Solution: Connect the 1.5mm safety plugs coming from the EEG cap/ECoG grid to the g.tec splitter box and connect the box to the clinical system as well as to BCI system using the g.tec connection cables. Supported systems come from: NIHON KOHDEN