WiMi Hologram Cloud a leading global Hologram Augmented Reality (“AR”) Technology provider announced that WiMi has developed a hybrid bios-signal-based brain-computer interface (HBS-BCI) that is rapidly gaining prominence. HBS-BCI technology is designed to improve classification accuracy, increase the number of commands, and shorten the time it takes for brain commands to be detected by integrating multiple biological signals. As a company focused on innovation and technology, WiMi is committed to providing advanced solutions that improve the way people interact with technology. the introduction of HBS-BCI technology marks WiMi having made an important breakthrough in the field of brain-computer interfaces, which will bring broader application prospects and a more personalized user experience.
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The core of WiMi’s HBS-BCI technology is the integration of multiple biological signals, including electroencephalogram (EEG), functional near-infrared spectroscopy (fNIRS), electromyography (EMG), electrooculogram (EOG), and eye tracker. By integrating these biological signals, the HBS-BCI technology is able to acquire multi-modal and multi-perspective user information about the user’s intent and cognitive state through different perspectives and dimensions, thus improving classification accuracy, increasing the number of commands and reducing brain command detection time for brain-computer interfaces. This innovative approach to signal integration provides users with a richer and more natural interaction experience.
EEG: Electroencephalography is the recording of electrical signals from the brain’s electrical activity by means of an array of electrodes placed on the scalp. It is widely used in brain-computer interfaces because of its high temporal resolution and low cost.EEG signals reflect the electrical activity of neurons in the brain and can capture different types of brain activity such as motor imagery, cognitive tasks, and response tasks.
fNIRS: Functional near-infrared spectroscopy is a technique for indirectly assessing brain activity by measuring changes in blood oxygenation levels in the cerebral cortex. It uses transmitters and receivers to light and detect areas of the brain, measuring changes in cerebral blood oxygenation and deoxyhemoglobin. fNIRS provides information that is complementary to EEG, with better spatial resolution and higher wearability.
EMG: Electromyography records electrical activity during muscle contraction and relaxation. In the HBS-BCI, EMG signals can be used to recognize and control commands related to muscle activity, such as limb movements.
EOG and eye tracker: Electrooculograms record the electrical activity of the eye muscles and can be used to detect eye movements and gaze positions. Ophthalmoscopes, on the other hand, can more precisely measure and record the trajectory of eye movements and gaze points. These signals can be used in HBS-BCI technology for control and interaction, such as selecting commands or operating interfaces by looking at specific areas.
The components of WiMi’s HBS-BCI technology include a data acquisition system, signal processing and feature extraction, paradigm design and task setup, classifiers and recognition algorithms, real-time applications and feedback, as well as associated hardware and equipment. The data acquisition system consists of multiple electrodes, transmitters and receivers, and sensors for acquiring different biological signals. The signal processing and feature extraction phase filters, denoises and extracts features from the acquired biological signals to obtain meaningful information. Paradigm design and task setup determine the specific activities or tasks to be accomplished by the user in the brain-computer interface task. Classifiers and recognition algorithms identify and classify the user’s intentions or commands from the extracted features by training and building models. Real-time applications and feedback ensure seamless interaction between the user and the external device or system and provide timely feedback to help the user adjust and improve the brain commands.
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WiMi’s HBS-BCI technology has significant advantages over traditional single biosignal brain-computer interfaces. First, by integrating multiple biosignals, the HBS-BCI technology is able to improve classification accuracy, resulting in more accurate intent recognition and command classification. This enables users to control external devices or systems more reliably and improve interaction efficiency. Second, HBS-BCI technology is able to increase the number of control commands, thus expanding the application domain. Users can generate more commands through different tasks and paradigms, enabling more diverse control and operations. HBS-BCI technology also reduces the time for brain command detection, providing more immediate response and feedback. This enables users to interact with the external environment more fluidly and enjoy a more natural and seamless experience.
Although HBS-BCI has made significant progress in improving the performance of brain-computer interfaces, it still faces some challenges. Current sensors need to be taped or fixed to the scalp, limiting the practical application of the technology and user comfort. In addition, the real-time application of HBS-BCI technology still faces some challenges. Detecting and interpreting brain commands quickly and accurately remains a challenging task due to the noise and complexity of biological signals. Future developments will continue to optimize user devices as well as develop efficient signal processing and machine learning algorithms to make real-time applications feasible.
In addition to the basic application of HBS-BCI technology, WiMi will further research and develop HBS-BCI to promote its real-time application in daily life scenarios. WiMi’s R&D team will continue to improve the classifier and recognition algorithms, and to enhance the system’s intelligence and adaptive capability to achieve more accurate and efficient command recognition. WiMi plans to collaborate with partners in different fields. In the future, HBS-BCI technology has the potential to be integrated with other cutting-edge technologies, such as virtual reality, augmented reality and artificial intelligence. By integrating with these technologies, a more immersive and intelligent brain-computer interface system can be created, providing users with a richer and more personalized experience, and bringing more rich application experiences to users.
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