Scientists’ new brain-computer interface is based on silicon chips

By designing a small and efficient brain-computer interface (BMI), researchers have taken a big step towards improving the quality of life of people with severe motor disabilities. This new technology is able to convert brain signals into text, thus allowing people with movement disorders to communicate effectively with others.

According to Tekna technology media medical and health news service, the microcomputer brain interface (MiBMI), which was developed by researchers at the Federal Polytechnic University of Lausanne (EPFL), is based on silicon chips and has the ability to decode complex neural signals and convert them into understandable text. has to read MiBMI allows us to convert complex neural activity into comprehensible text with high accuracy and low energy consumption, says Mahsa Shahifan, one of the researchers of this project. This advance brings us closer to practical, implantable solutions that can significantly improve the communication abilities of people with severe motor disabilities.

In recent years, research in the field of brain-computer interfaces has made significant progress. These small devices have the potential to help people with severe mobility disabilities interact with the world around them and participate in everyday activities. Neuralink company under the guidance of Elon Musk is also active in the development of brain and computer interfaces. The company aims to create interfaces that can help people with neurological diseases such as paralysis or spinal cord injury. Compared to traditional brain-computer interfaces, the new MiBMI is more compact, efficient and flexible. Traditional systems are often large, consuming and have application limitations. To convert brain signals into text, this device decodes the neural signals produced when a person imagines writing. Electrodes implanted in the brain record the neural activity associated with these imaginary hand movements. The MiBMI chip then processes these signals and converts them into digital text.

This new technology can help people with locked-in syndrome and other severe motor disabilities to communicate effectively. Mohammad Ali Shaari, the main author of this research, says that while this chip has not yet been integrated into an operational brain-computer interface, the results of the experiments show that this device can convert handwritten activity into text with high accuracy. Considering the current ability of this chip to decode 31 characters, there is a great potential for future developments. Researchers hope to expand the use of this technology by increasing the number of decipherable characters.

The small size, low power consumption and low invasiveness of this chip make it suitable for implantation in the brain. The integrated design of this device enables the recording and processing of neural signals in a small package. This development could revolutionize the treatment of neurological diseases and help people with severe motor disabilities live a better quality of life.

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