What is a Brain-Computer Interface (BCI)?

Brain-computer interfaces (BCIs) or alternatively called brain-machine interfaces (BMIs) are systems that translate brain activity into action for some external device (think wheelchair or computer cursor).

What’s the point of a BCI?

BCIs are designed to collect, process, and translate brain signals into commands for an external device. These systems of human-machine interaction offer applications in various sectors from video gaming to sleep enhancement to control of a prosthetic. The goal of all BCIs is to establish a communication pathway by detecting a specific intention from the user. They represent a direct link between your brain and the outside world. Since BCIs are not necessarily dependent on the peripheral nervous system and muscular system, an obvious application is in motor restoration and rehabilitation. A BCI capable of supplementing or replacing damaged motor pathways would greatly extend the quality of life to that individual.

What are the different parts of a BCI?

While the exact number may depend on the purpose of the BCI, there are really four main parts.

1. Electrodes or sensors that are placed on the scalp or directly on the brain to record the electrical activity of neurons.
2. A computer or other device that processes the signals from the electrodes and translates them into commands for the device being controlled.
3. A user interface, such as a screen or keyboard, that allows the user to interact with the system and provide feedback on the output.
4. A feedback mechanism, such as a visual or auditory display, that allows the user to see or hear the results of their thoughts and make adjustments to their brain activity if necessary.

Why aren’t BCIs used everywhere?

BCIs are still in the early stages of development, and there are many challenges that need to be addressed before they can be widely used. These challenges include improving the accuracy and reliability of brain activity detection, as well as developing better algorithms for translating brain activity into commands that the computer can understand.The upfront cost of brain monitoring equipment such as EEG electrodes and amplifiers represents an initial hurdle. Furthermore, recording electrodes must offer high signal-to-noise ratios even outside laboratory settings. But beyond hardware developments, significant strides must be made in BCIs that are able to elicit appropriate brain modulation, extract relevant features, and obtain sufficient prediction accuracy to maintain user acceptance.

Usability relates to the ease of use and enjoyment a user has for a particular product. In the context of BCIs, this is especially relevant to training time. Current high-performing BCIs require extensive training with the user before intended use can begin. Such a time-consuming process is likely to deter many users who are not directly dependent on the BCI for basic communication.

Another issue hindering BCI development is the lack of variety in command signals. A BCI is only as versatile as its number of command signals and speed of prediction. Imagine the difficulty in moving across a room with a wheelchair that only moves a small distance in one direction every minute. BCI researchers describe such an issue as having a low information transfer rate (ITR). A term based on Shannon channel theory, ITR is a commonly used metric to access BCI performance and it depends on the number of classes, detection accuracy, and detection time. From this, an ideal BCI must be aimed at quickly and correctly detecting user intent from a multitude of options. Moving from a binary classification scheme to one in which many options are available is a method to increase the ITR.

What’s the takeaway?

In summary, a brain-computer interface is a system that allows a person to control a computer or other device using their brain activity. It involves the use of sensors to detect brain activity and algorithms to translate this activity into commands that the computer can understand. BCIs have a wide range of potential applications, but there are still many challenges that need to be addressed before they can be widely used.