Brain computer interface is such a concept that translates the neuronal into signals that can be processed to perform different types of output. It is also called neural control interface (NCI) or brain machine interface (BMI). Generally, in this concept it acquire the brain signal, analyse them, and translate them into corresponding outputs. The main objectives of Brain Computer Interface is help disable person to restore their useful functions.

Components of BCI

The purpose of a BCI is to detect and quantify features of brain signals that indicate the user’s intentions and to translate these features in real time into device commands that accomplish the user’s intent. To achieve this, a BCI system consists of 4 sequential components.

To achieve this, a BCI system consists of 4 sequential components.

(1) signal acquisition

(2) feature extraction

(3) feature translation

 (4) device output.

Signal Acquisition

Signal Acquisition is the process of measurement of the analog signal from the brain using different particular sensors. The received signal is then amplified and filtered in order to remove the noise from the signal. Finally, the signal is digitalized using analog to digital converter and transferred to the processing unit.

Feature Extraction

Feature Extraction is the process of extracting the unique features from the received signal. These features should have strong correlations with the user’s intent. Because much of the relevant (ie, most strongly correlated) brain activity is either transient or oscillatory.

Feature Translation

When the feature is Extracted and classified it is passed through the feature translation algorithm. The main task of feature Extract algorithm is to convert the received signal to appropriate command to output device.

Device Output

The output of the feature translation unit is provided to the specific output device. The commands from the feature translation algorithm operate the external device, providing functions such as letter selection, cursor control, robotic arm operation, and so forth. The device operation provides feedback to the user, thus closing the control loop.

Types of BCI

They are mainly classified in three group:

  1. Non-Invasive
  2. Semi Invasive
  3. Invasive

BCIs That Use Activity Recorded Within the Brain

Intracortical microelectrode array and its placement in a patient with tetraplegia.

A) The 100-microelectrode array on top of a US penny.

B) The microelectrode array in a scanning electron micrograph.

C) The preoperative axial T1-weighted magnetic resonance image of the patient. The red square in the precentral gyrus shows the approximate location of the array.

 D) The patient sitting in a wheelchair and working with a technician on a brain-computer interface task. The gray arrow points to a percutaneous pedestal that contains the amplifier and other signal-acquisition hardware.


Many researchers throughout the world is working with BCI systems. A few people with severe disabilities are already using a BCI for basic communication and control in their daily lives. With better signal-acquisition hardware, clear clinical validation, viable dissemination models, and, probably most important, increased reliability, BCIs may become a major new communication and control technology for people with disabilities and possibly for the general population also.

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