Researchers have developed a brain-computer interface that should make it possible to control things using thought transfer. This could make life easier for people with disabilities in particular.

The world has changed drastically due to the advancement of computer chips. Computers have now become an integral part of our everyday lives. But many enthusiasts see upgrading our personal supercomputer as the end goal. We're talking about the human brain.

But Elon Musk is not the only one working with Neuralink on an interface to our thinking organ. Researchers at the University of Texas at Austin recently achieved success in the field of brain-computer interfaces (BCIs). Their approach makes it possible to control computer games through thoughts.

Adaptive BCI uses machine learning to support individuals with motor disabilities without the need for individual calibration. This should make possible use much easier.

Brain-computer interface can be applied to any person

The researchers achieved this through a machine learning algorithm. Traditionally, however, such devices require extensive calibration for each user because every brain is different. However, the new solution can quickly understand an individual's needs and easily calibrate itself through repetition.

As a result, multiple patients can use the same device without having to adjust the system each time. Users wear a cap with electrodes that is connected to a computer. The electrodes measure the electrical signals from the brain and forward them to a decoder.

This interprets the information and translates it into actions in the game. The brain-computer interface helps users guide and strengthen their neural plasticity. This is the brain's ability to change, grow and reorganize over time.

Device is intended to improve brain function and restore quality of life

The experiments are primarily aimed at improving the patients' brain function. Because this can increase the quality of life and make everyday life easier for those affected. The research lays the foundation for further innovations in the area of ​​brain-computer interfaces.

In the first pilot test, 18 participants without motor impairments were tested. In the future, however, the researchers plan to test this technology on people with motor impairments in order to apply it to larger groups in clinical settings. Controlling automated wheelchairs and rehabilitation devices should then no longer be a major problem.

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