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A Brain-Computer Interface (BCI) is a system that allows for a direct communication link between the human brain and an external device. A BCI captures and translates brain signals into commands able to control computers, prosthetics, and other machines.
A Brain-Computer Interface (BCI) is a system that allows for a direct communication link between the human brain and an external device. A BCI captures and translates brain signals into commands able to control computers, prosthetics, and other machines.
HOW BRAIN COMPUTER INTERFACES WORK
HOW BRAIN COMPUTER INTERFACES WORK
1.SIGNAL ACQUISITION
1.SIGNAL ACQUISITION
Electrodes placed on or inside the brrain detect electrical activity generated by neurons. The types of BCIs include:
Non- Invasive BCIs
Non- Invasive BCIs
While being non-invasive and considered the safest, these BCIs suffer from decreased signal fidelity because of interference caused by the skull and scalp.
Examples:
Electroencephalography (EEG) Headsets – Devices such as OpenBCI and Emotiv record brain waves using electrodes placed on the surface of the scalp.
Functional Near-Infrared Spectroscopy (fNIRS) – Uses light to measure changes in brain blood flow.
Application: Used for gaming, meditation training, cognitive improvement, and assistive technology for disabled persons.
Partially Invasive BCIs
Partially Invasive BCIs
These BCIs are implanted by a relatively small surgery to implant sensors beneath the skull but outside the brain parenchyma. They provide an improved signal-to-noise ratio than non-invasive techniques while reducing the risk than fully invasive BCIs.
Example:
ECoG (Electrocorticography) Sensors - Electrodes are implanted onto the brain's surface and record high-quality neural activity.
Applications: Applied to epilepsy monitoring, neuroprosthetic control, and early brain disease detection.
Invasive BCIs
Invasive BCIs
Invasive BCIs are the type of neural interface that includes the precise recording of the activities of the single neurons as well as the electrical stimulations, which results in the restoration of a desired brain function. They are implanted directly into the brain tissue.
Example:
Microelectrode Arrays – Microelectrode arrays are implanted in small brain areas to establish communication between the brain and a device.
Neuralink –Elon Musk's company representing the development of super-thin, high-resolution, and high-density neural implants for brain-computer interfaces.
Applications: The implementation of the technology for the revival of the motor function in paralyzed people, the improvement of thinking and eventually its direct combination with artificial intelligence.
2. SIGNAL PROCESSING
2. SIGNAL PROCESSING
Noise is frequent in brain signals due to muscle activity and intrusion from external and electrical elements.
Key Steps:
Noise Reduction: Filters unwanted noise signals like movement of musclesand eye blinks.
Feature Extraction: Identifies the patterns of brainwaves such as alpha, beta, and gamma waves.
Machine Learning: The Artificial Intelligence model gets the right thoughts to the movement or command.
Real-Time Translation: Converts coded signals into actions, enables digital responses to be exhibited.
Example: Irrelevant signals are filtered out for movement control to focus only on motor cortex activity.
3. TRANSLATION ALGORITHM
3. TRANSLATION ALGORITHM
Once the brain signals are cleaned up and processed, the machine learning model converts these into actionable digital commands. This step is essential because it fills the gap between neural activity and the external control of devices for BCIs to be useful.
HOW IT WORKS
Pattern Identification:
It identifies specific patterns in the nervous system associated with specific thoughts or intentions, such as moving a hand. Large datasets are used to train machine learning models to recognize the patterns.
Signal Mapping: Each brain signal is assigned to do a specific action.
Classification Algorithms: AI models like SVM, CNN and RNN classify brain signals into their respective categories.
Command Execution: Translated signals once classified are sent to external devices like cursor, robotic arm, wheelchair, etc.
4. DEVICE CONTROL
4. DEVICE CONTROL
Once the brain signals are processed and turned into commands, they are transmitted to external systems for execution. These systems may include robotic limbs, assistive devices, computers, or smart home controls.
How It Works
Signal Transmission: The translated brain command is sent through wireless (Bluetooth, Wi-Fi) or wired connections.
System Integration: The device that receives the command interprets it and carries out the corresponding action.
Real-Time Feedback: Some BCIs offer feedback to the brain, enhancing accuracy and user control over time.
Eg: In March 2012 g.tec introduced the intendiX-SPELLER, the first commercially available BCI system for home use which can be used to control computer games and apps. It can detect different brain signals with an accuracy of 99%.
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