A quick overview of the top ten brain-computer interface key technologies released

Shanghai Securities News China Securities Network reported that according to the Brain-Computer Interface Industry Alliance on July 14, in order to commemorate the 50th anniversary of the scientific concept of brain-computer interface and to further strengthen the scientific and technological forward-looking research and judgment in the field of brain-computer interface and lead original scientific research, To promote self-reliance and self-reliance in science and technology, the Brain-Computer Interface Industry Alliance organized and mobilized member units, alliance working groups and alliance experts as well as brain-computer interface industry, academia, research and medical science and technology workers to collect the top ten key brain-computer interface technologies that are of common concern around the world. At the first Tianjin Brain-Computer Interface Conference and the first plenary session of the Brain-Computer Interface Industry Alliance, ten key technologies were released. These technologies are important breakthroughs in the field of brain-computer interface.

Brain-Computer Interface System Rapid Calibration EEG Sample Amplification Technology

Limited by the strong cross-individual and cross-time variability of EEG signals, brain-computer interface systems usually require lengthy and cumbersome calibration processes to obtain sufficient training samples, which hinders the practical application of brain-computer interfaces. EEG sample amplification technology for rapid calibration of brain-computer interface systems can effectively reduce the calibration burden of brain-computer interface systems, promote the realization of "plug and play" high-performance brain-computer interaction, and accelerate the industrialization process of brain-computer interfaces.

Key technologies for large-scale instruction set brain-computer encoding and decoding based on hybrid EEG features

The number of instructions, as one of the core indicators of the brain-computer interface (BCI), determines the control dimension of BCI and is one of the key factors affecting the performance of BCI. The number of traditional non-invasive BCI instructions is small and the application scenarios are greatly limited. By designing a new time-frequency-space division multiple access encoding strategy and efficiently decoding mixed EEG features, key technologies for high-speed brain-computer encoding and decoding with over 200 instructions can be achieved, which is of great significance to improving BCI system performance and expanding BCI application scenarios.

Key technology of high-performance brain-computer encoding and decoding based on visual evoked potential

Visual evoked potential brain-computer interface has the advantages of non-invasiveness, fast communication speed, and high stability, and has become one of the most mainstream brain-computer interface application paradigms. On the one hand, a high-rate brain-computer encoding and decoding theoretical method is constructed based on the principle of communication modulation and demodulation. On the other hand, the retina-visual cortex spatial mapping model is used to construct a comfortable brain-computer encoding and decoding theoretical method based on peripheral visual field evoked potentials, which is friendly to promoting interaction. The practical progress of visual brain-computer interface is of great significance.

Robust EEG decoding technology for human motion parameter estimation

Neural decoding technology converts human body motion parameters into signals. It is a key technology for sports brain-computer interface and has important application value for rehabilitation and improving human body performance. However, in real application scenarios, perception, cognition and motor distraction will affect the neural decoding performance of motion parameters. Therefore, developing motor neural decoding technology that is robust to various factors and achieving stable motion parameter decoding performance is an important step for sports brain-computer systems. A key technology of interface. Specifically, it includes: discovering robust neural representations of motion parameters and robust neural decoding models.

Brain-computer interface decoding technology based on deep brain signals

The deep brain is an important source of basic life functions, and it is very important to study the deep areas of the brain. Deep brain regions are involved in many important functions such as movement, emotion, cognition, and more. By decoding deep brain signals and understanding how relevant nuclei work, it is expected to improve our understanding of basic human behavior and propose new treatments for neurological and psychiatric diseases.

Micro and miniaturized brain signal collection technology

Brain nerve activity signals are extracted by sensors in the form of analog signals. The acquisition technology uses dedicated electronic circuits to convert a large number of weak analog signals into data in the form of digital signals that can be transmitted and stored over long distances. The miniaturization of this specialized electronic circuit will significantly improve the convenience of brain-computer interfaces.

Online or real-time processing technology of brain signals

Brain-computer interface is a technology that allows the brain and computer to directly interact with each other. In order to quickly process and interpret the information collected from the brain, the computer needs to send feedback information back to the brain through human-computer interaction devices.

Precise control technology of brain nerve activity

The method by which the computer transmits feedback information directly to the brain relies on precise brain nerve regulation technology, that is, direct stimulation of the brain nerves (mainly electrical stimulation) can trigger the brain to produce correct reconstruction of the information to be input by the computer. .

Safe wireless power supply and brain signal transmission technology

For portable brain-computer interface systems for universal use, wireless transmission mode is required for energy supply and brain-computer information communication. The biological safety of energy transmission and energy storage and the information security of brain data are the key to brain-computer interface. The popularization of technology must seriously solve the problem.

Multiple modal neural signal sensing technologies

The most basic premise of brain-computer interface is to be able to obtain signals of brain nerve activity, that is, to extract the electrical, optical, magnetic and other physical manifestations of brain nerve activity through sensing technology.

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