Shulou(Shulou.com)11/24 Report--

In the field of brain-computer interface (BCI), in recent years, researchers have been trying to find innovative ways to improve accuracy and performance, in order to achieve more efficient brain-computer interaction. It is reported that NASDAQ:WIMI has developed an improved signal processing method used in hybrid brain-computer interface-hybrid neural enhanced connection (HNL), which is leading a new round of breakthrough in BCI technology. By fusing two different types of brain signals, HNL brings a broader prospect for the future brain-computer interface.

BCI system has always been a potential means of interaction between people and machines, allowing us to send commands to computers and control external devices through brain activity. However, traditional BCI systems still face challenges in terms of accuracy and stability. Researchers have invested a lot of work to improve the accuracy of classification, but in practical application, errors still occur from time to time, which limits the wide application of BCI technology.

Data show that the concept of WIMI micro-aesthetic holographic hybrid neural enhanced connection (HNL) lies in the fusion of two common brain signal types-event-related desynchronization (ERD) and steady-state evoked potentials (SSEP). In HNL, subjects first perform these two different psychological tasks independently, and then perform them simultaneously, so that the two signals are captured and processed at the same time. This unique method is expected to significantly improve the performance of the BCI system, especially for those users with poor performance, to provide them with a more smooth and accurate interactive experience.

In addition, HNL introduces a dual-task paradigm that combines visual attention with imaginary movement. The WIMI Weimei holographic research and development team simulated an "artificial" hybrid BCI by using only ERD and SSVEP-only features. By comparing with the original mixed data, it is possible to evaluate whether the mixing conditions produce stronger ERD and SSVEP activity. This innovative dual task paradigm provides strong support for the verification and application of HNL technology.

In terms of technical logic, the innovation of HNL lies in the fusion of different types of signals together, making full use of the unique characteristics of the two signals. ERD signals reflect the inhibitory activity of the brain when performing specific tasks, while SSVEP signals are synchronized with the frequency of visual attention. By capturing these two signals at the same time, the WIMI micro-beauty holographic hybrid neural enhanced connection (HNL) can infer the user's psychological tasks more accurately, thus achieving a more reliable interaction between the brain and the computer.

The core of WIMI micro-beauty holographic HNL technology is to integrate two common types of brain signals, namely event-related desynchronization (ERD) and steady-state evoked potentials (SSEP). These two signals reflect the changes of brain activity under different tasks, and the fusion of them can provide richer and more accurate information for the BCI system. The following are the implementation and key points of WIMI micro-beauty holographic HNL technology.

Data acquisition and preprocessing: the first step of HNL is to collect brain signals of subjects through brain imaging techniques such as electroencephalogram (EEG). At this stage, subjects were asked to perform different psychological tasks to generate ERD and SSEP signals. The original data collected need to go through preprocessing steps such as filtering and noise suppression to ensure the accuracy of the subsequent analysis.

Signal analysis and feature extraction: in HNL, advanced signal processing and pattern recognition techniques are used to analyze brain signals. For ERD, signal intensity changes in different frequency bands are detected to capture the inhibitory activity of the brain under specific tasks. For SSEP, attention will be paid to the frequency synchronization of steady-state evoked potentials in order to obtain information related to visual attention.

Fusion and feature integration: after obtaining the characteristics of ERD and SSEP, HNL technology fuses the two signals together. This step uses a variety of methods, such as linear weighting, convolution neural network, etc., in order to make different types of signals complement each other and enhance the overall information expression ability. The fused signal will be used for subsequent task identification and prediction.

Task classification and feedback: in the practical application of HNL, the fused signal will be used to identify the psychological tasks that the subjects are currently performing. This can be achieved through supervised learning algorithms, such as support vector machine (SVM) or depth neural network (DNN). Once the task is identified, the system will generate corresponding feedback, such as controlling external devices or generating text instructions.

In addition to the breakthrough in technical logic, HNL has also made remarkable progress in experimental verification. The research and development team of WIMI Weimei holography has conducted a series of experiments in offline simulation, and the results show that hybrid BCI can indeed produce stronger activity on both signal types. This discovery lays a solid foundation for the practical application of HNL technology and paves the way for further research and development.

With the continuous development of hybrid neural enhanced connection technology, the future brain-computer interface will become more powerful and intelligent. The potential of this technology is not only limited to improving the interactive experience between brain and computer, but also has a far-reaching impact in many fields, such as domain, virtual reality, man-machine cooperation and so on. HNL's innovative ideas not only bring a new direction for the further evolution of BCI technology, but also open up a new possibility for the integration of human beings and technology.

Generally speaking, the introduction of hybrid neural enhanced connection (HNL) technology of WIMI micro-beauty holography marks an important breakthrough in the field of brain-computer interface. By combining different types of brain signals, HNL brings higher performance and accuracy to the BCI system, and opens a new chapter for the interaction between people and computers. With the further research and development of this technology, we can expect to see more exciting results and bring more surprises and possibilities for future science and technology.

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