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What is Brain-Computer Interface (BCI)? System Overview & Applications

The Brain-Computer Interface (BCI) System is a concept that converts neural activity into signals that may be processed to produce a variety of outputs. Also known as the neural control interface (NCI) or the brain-machine interface (BMI). In general, this notion acquires brain signals, analyses them, and converts them into outputs. The primary purpose of the Brain-Computer Interface is to assist disabled individuals in regaining their useful functions.

Components of Brain-Computer Interface (BCI) System

The objective of a BCI is to detect and quantify characteristics of brain signals that indicate the user’s intents and to translate these characteristics into device commands that fulfill the user’s intent in real-time. A BCI system consists of four consecutive components to do this.

Components of Brain Computer Interface (BCI) System

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

  • Signal Acquisition
  • Feature Extraction
  • Feature Translation
  • Device Output

1. Signal Acquisition

Signal Acquisition is the technique of measuring the brain’s analog signal utilizing a variety of specific sensors. The received signal is subsequently amplified and filtered to remove noise. The signal is then digitalized using an analog-to-digital converter and sent to the processing unit.

2. Feature Extraction

Feature Extraction is the process of extracting the signal’s distinctive characteristics. These features should correlate strongly with the user’s arm. Because a significant portion of the relevant (i.e., most highly correlated) brain activity is either transitory or oscillatory.

3. Feature Translation

Following the extraction and classification of a feature, the feature is transferred through the feature translation method. The primary function of the feature Extract algorithm is to turn the incoming signal into an output device instruction.

4. Device Output

The output of the feature translation unit is transmitted to the designated output device. The external device is operated by the commands from the feature translation algorithm, giving features such as letter selection, cursor control, robotic arm movement, and so on. The operation of the device gives the user with feedback, thus closing the control loop.

Types of Brain-Computer Interface (BCI) System

1. Invasive BCIs

In invasive BCI, electrodes are surgically implanted beneath the scalp to transmit brain signals. The primary advantage is a more accurate reading, while the disadvantages include surgery-related side effects. After surgery, scar tissue may grow, potentially weakening brain messages. According to some researchers, after electrodes are implanted, the body may not accept them, which may result in medical issues.

2. Semi-Invasive BCIs

Semi-Invasive or Partially-Invasive Brain-Computer Interfaces (BCI) are implanted within the skull, but rest outside of the grey matter. They create signals with a higher resolution than non-invasive BCIs, in which cranial bone tissue deflects and deforms signals, and have a reduced risk of causing scar tissue formation in the brain than fully invasive BCIs.

3. Non-invasive BCIs

The term “non-invasive Brain-Computer Interfaces” refers to all technologies that enable brain-to-computer stimulation without penetrating the skull. In fact, the majority of non-invasive Brain-Computer Interfaces (BCIs) rely on electrodes strategically placed on the scalp in order to monitor brain activity. Electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), magneto-encephalography (MEG), near-infrared spectroscopy (NIRS), and functional transcranial doppler sonography are among the most used non-invasive BCI methods.

Applications

BCI Applications

The applications of Brain-Machine Interface are not restricted to the medical sphere alone but span various and diverse fields. Applications include, but are not limited to, neuroergonomics, medicine, the intelligent environment, education and self-regulation, gaming and entertainment, neuromarketing, and advertising. Brain-Machine Interface can be utilized to prevent, detect, and diagnose illnesses, as well as to rehabilitate and recover from them.

Brain-Machine Interface also facilitates good cooperation between the Internet of Things and BMI technologies, thereby enabling intelligent surroundings such as smart homes, transportation, and workplaces.

BMI technologies have also garnered considerable interest in the marketing field. Brain-Machine Interface aids in measuring the attention created after viewing a television commercial or other marketing channel. Using Brain-Machine Interface, researchers are also interested in measuring the memorization of adverts. Similarly, Brain-Machine Interface uses brain electrical signals to assess the intelligibility of the studied knowledge in the field of Education. Cognitive biometrics in the realm of security and authentication is an application of BMI technology designed to circumvent the vulnerabilities inherent to this field.

BCI facilitates communication between the brain and external equipment. The technological possibilities are limitless and promising. Therefore, you must examine its implementation in a manner suitable to your business.

Conclusion

Hope this blog helps you to understand Brain-Computer Interface (BCI), System Overview & Applications. We, MATHA ELECTRONICS will come back with more informative blogs.

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