Engineers at the University of California (UCLA)<\/b> have created an innovative, wearable, and non-invasive Brain-Computer Interface (BCI)<\/b> system. This device uses Artificial Intelligence (AI)<\/b> as an assistant to more accurately decipher human intentions and perform various tasks based on them, such as controlling a robotic arm or a computer cursor.<\/p>\n
According to a study published in the journal Nature Machine Intelligence<\/b>, this new interface is a significant milestone<\/b> in the development of non-invasive BCI systems. The technology may be particularly beneficial for people with physical limitations\u2014those who are paralyzed or suffer from neurological diseases<\/b>.<\/p>\nHow the New BCI System Works<\/b><\/h3>\n
The engineering team developed special algorithms<\/b> to decipher Electroencephalography (EEG)<\/b> signals. The EEG method records the electrical activity of the brain and identifies the user’s movement intentions<\/b> from these signals.<\/p>\n
The deciphered signals were then connected to an AI-based platform<\/b> that interprets the user’s intentions in real-time<\/b>. With the help of this AI system, people perform tasks much faster.<\/p>\nOvercoming Limitations of Existing Technology<\/b><\/h3>\n
Currently existing, surgically implanted BCI devices manage to convert brain signals into commands, but their use is limited due to the high risks and costs associated with neurosurgery<\/b>. Although the first such devices appeared more than 20 years ago, they are still restricted to small pilot clinical trials.<\/p>\n
To overcome these limitations, researchers created and tested a new, non-invasive BCI system<\/b> aided by artificial intelligence. Four participants were involved in the experiment: three without motor impairments and one who was paralyzed from the waist down<\/b>.<\/p>\n
The participants wore an EEG helmet<\/b> that recorded their brain’s electrical signals. Then, using special algorithms, the researchers converted these signals into movements for a computer cursor and a robotic arm. Simultaneously, the AI system<\/b>, with a built-in camera, observed the deciphered movements in real-time and helped the participants complete two different tasks: controlling a computer cursor and a robotic arm<\/b>.<\/p>\nDemonstrated Success<\/b><\/h3>\n
The experiment showed that all four participants completed the tasks significantly faster with the help of artificial intelligence<\/b>.<\/p>\n
It is particularly noteworthy that the paralyzed participant was only able to control the robotic arm with the assistance of the AI<\/b>; without it, they could not complete the task.<\/p>\n