Overview
Brain Computer Interface (BCI) System is such a concept that translates the neuronal into signals that can be processed to perform different types of output. It is also called the neural control interface (NCI) or brain-machine interface (BMI). Generally, in this concept, it acquires the brain signal, analyses them, and translates them into corresponding outputs. The main objectives of Brain-Computer Interface are helped disable person to restore their useful functions.
Components of Brain Computer Interface (BCI) System
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
1. 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 an analog to digital converter and transferred to the processing unit.
2. 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.
3. Feature Translation
When the feature is Extracted and classified it is passed through the feature translation algorithm. The main task of the feature Extract algorithm is to convert the received signal to an appropriate command to the output device.
4. 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 Brain-Computer Interface (BCI) System
1. Invasive BCIs
Invasive BCI requires surgery to implant electrodes under the scalp for communicating brain signals. The main advantage is to provide a more accurate reading; however, its downside includes side effects from the surgery. After the surgery, scar tissues may form which can make brain signals weaker. In addition, according to some researchers once implanted electrodes, the body may not accept the electrodes which may cause medical complications.
2. Semi Invasive BCIs
Semi Invasive or Partially invasive BCI devices are implanted inside the skull but rest outside the brain rather than within the grey matter. They produce better resolution signals than non-invasive BCIs where the bone tissue of the cranium deflects and deforms signals and have a lower risk of forming scar tissue in the brain than fully invasive BCIs.
3. Non-invasive BCIs
The term “non-invasive Brain-Computer Interfaces” encompasses all the technology that allows for brain-to-computer stimulation without needing to penetrate the skull. Indeed, most non-invasive Brain-Computer Interfaces, or BCIs, simply rely on electrodes that are strategically placed onto certain areas of the scalp in order to record brain activity. Amongst the main technologies used in the process of non-invasive BCIs are electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), magneto-encephalography (MEG), near-infrared spectroscopy (NIRS), and functional transcranial doppler sonography.
Applications
The applications of Brain-Machine Interface spread across multiple and diverse fields and are not limited to the medical field alone. Applications include, but are not limited to, neuroergonomics, medical, smart environment, education and self-regulation, games and entertainment, neuromarketing and advertisement. In the field of healthcare alone, Brain-Machine Interface can be employed to prevent, detect and diagnose, and rehabilitate and restore a sickness.
Brain-Machine Interface also extends excellent cooperation between the Internet of Things and the BMI technologies, creating smart environments such as smart houses, transportations, or workplaces.
The marketing field has also shown great interest in BMI technologies. Brain-Machine Interface helps measure the attention generated post watching a commercial on TV or any other marketing channel. On the other hand, researchers are also interested in estimating the memorization of advertisements using a Brain-Machine Interface. Similarly, Brain-Machine Interface utilizes brain electrical signals to determine the degree of clarity in the information studied, in the field of Education. Cognitive biometrics in the field of security and authentication is an application of BMI technology to overcome the vulnerabilities encountered in this field.
BCI provides a channeling facility between the brain and external equipment. The possibilities with this technology are infinite and promising. You must, therefore, consider its application in a way, which is pertinent to your business.
