Wednesday 30 April 2025
A team of researchers has developed a novel approach to reduce the number of electrodes used in brain-computer interfaces (BCIs), making them more portable and practical for everyday use.
BCIs are devices that allow people to control technology with their thoughts. They work by detecting electrical signals from the brain, which are then translated into commands or actions. However, these devices typically require dozens of electrodes to be placed on the scalp, which can be cumbersome and uncomfortable.
The new approach, called PlugSelect, uses a machine learning algorithm to automatically select the most important channels of information from the brain signals. This allows the BCI to function with just a few dozen electrodes, rather than hundreds.
To test the effectiveness of PlugSelect, the researchers used it on three different types of brain-computer interfaces: one that helps people control robots, another that can detect auditory attention, and a third that recognizes emotions. In each case, the algorithm was able to identify the most important channels of information, allowing the BCI to function with reduced electrode counts.
One of the key advantages of PlugSelect is its ability to adapt to different brain signals and tasks. This means that it could be used in a variety of applications, from helping people with paralysis communicate, to enhancing gaming experiences by reading brain signals.
The researchers also found that PlugSelect was able to improve the accuracy of the BCIs, even when using fewer electrodes. This is because the algorithm is able to focus on the most important information, rather than trying to process all of the available data.
While there are still many challenges to overcome before BCIs become widely used, the development of PlugSelect represents an important step forward. It has the potential to make these devices more practical and accessible, which could have a significant impact on people’s lives.
The researchers plan to continue refining their algorithm and testing its effectiveness in different scenarios. They also hope to collaborate with industry partners to develop commercial versions of the technology.
In the meantime, the potential benefits of PlugSelect are clear. By reducing the number of electrodes needed for BCIs, it could make these devices more comfortable and convenient to use, while also improving their accuracy and functionality. As the technology continues to evolve, we can expect to see even more innovative applications emerge.
Cite this article: “Reducing Electrodes in Brain-Computer Interfaces”, The Science Archive, 2025.
Brain-Computer Interfaces, Plugselect, Machine Learning Algorithm, Electrodes, Brain Signals, Robot Control, Auditory Attention, Emotional Recognition, Paralysis Communication, Gaming Enhancement
