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WiMi Developed Steady State Visual Evoked Potential Based Flight Control System

BEIJING, Nov. 1, 2023 /PRNewswire/ — WiMi Hologram Cloud Inc. (NASDAQ: WIMI) (“WiMi” or the “Company”), a leading global Hologram Augmented Reality (“AR”) Technology provider, today announced that it developed a flight control system (FCS) based on steady state visual evoked potentials (SSVEP) was developed. SSVEP acts as a frequency-specific EEG signal that can be triggered by stimulating the blinking frequency of an LED. Combining SSVEP with the visual stimulation panel of the UAV provides an intuitive and natural method of control for the user.

WiMi’s SSVEP-based FCS is derived from the brain-computer interface (BCI), which translates brain signals into actual machine control. SSVEP is widely used in this innovative technology as an important electroencephalographic signal. SSVEP works by setting up an LED visual stimulation panel on the drone, which utilizes flashing LEDs at different frequencies to trigger specific frequencies of brain waves, thus realizing precise control of the drone.

The key aspects of the whole system are signal acquisition and transmission. First, the EEG signal acquisition system captures the brain waves from the subject’s head through an electrode array, which is a non-invasive method with low cost, high utility and portability. Next, the SSVEP triggers brain waves of specific frequencies by stimulating the blinking of LEDs, and these signals are amplified and converted into digital signals, which are processed by a signal processing computer and transmitted to a wireless transmission signal module.

The WiMi SSVEP-based FCS consists of five main components:

EEG signal acquisition system: This system utilizes an electrode array to non-invasively capture the subject’s brain waves. This non-invasive method of data acquisition greatly enhances user convenience and comfort.

Visual stimulus panel: This is the core part of the system, which triggers SSVEP through the flashing frequency of LEDs. Different frequencies of LEDs are used for different flight control commands, such as left turn, forward turn, right turn, and so on.

Signal processing computer: The signal processing computer is responsible for converting the captured EEG signals into digital signals and performing real-time signal processing and analysis. It decodes the user intent from the EEG signals and translates it into specific control commands for the UAV.

Wi-Fi 6E wireless transmission signal module: This module transmits the processed signals to the UAV wirelessly. the application of Wi-Fi 6E ensures high-speed and stable signal transmission, providing a solid foundation for the real-time and reliability of the system.

Drone: The drone receives control signals from the signal module and realizes various flight actions based on the user’s EEG intentions, making it intuitive and easy to control the drone.

The WiMi’s SSVEP-based FCS not only applies brain-computer interface technology, but also introduces SSVEP as a means of control in the field of drone manipulation, breaking through the traditional manipulation mode. The development of this technology will enable ordinary people to easily control drones without the need for a specialized technical background, thus expanding the range of drone applications. This technology will not only give rise to new business opportunities, but also accelerate the convergence of artificial intelligence, neuroscience and robotics.

In terms of the commercialization and application prospects of the technology, the SSVEP-based FCS has great market potential. On the one hand, the technology can lower the control threshold of UAVs to a whole new level, enabling more people to control UAVs with ease, thus expanding the application fields of UAVs. On the other hand, the technology also has a wide range of application prospects in virtual reality, medical rehabilitation and other fields, which is expected to create brand new business opportunities.

The WiMi’s SSVEP-based FCS involves several key aspects, ranging from the acquisition of EEG signals to the actual manoeuvring of the UAV, and the implementation process of the technology is as follows:

EEG signal acquisition: First, EEG signals need to be acquired from the subject’s head. This step is usually accomplished by placing an array of electrodes on the scalp. The electrodes will record the electrical activity in the brain via SSVEP. Since SSVEP is an EEG signal that is synchronized with the frequency of the visual stimulus, it is necessary to set up different frequencies of visual stimuli in the experiment.

Visual stimulation panel design: To trigger SSVEP, a visual stimulation panel needs to be designed with LEDs mounted on it. each LED emits a light signal of a specific frequency, which is used to stimulate the brain to produce brain waves of the corresponding frequency. For example, LED A may flash at 15 Hz, while LED B flashes at 20 Hz, and so on.

Signal processing and parsing: When a subject gazes at an LED of a specific frequency, the brain generates brain waves synchronized with that frequency. The captured EEG signals need to be signal processed and parsed to extract the brainwave information associated with the LED frequency. This step requires precise algorithms and real-time performance to ensure accurate parsing of the user’s intent.

Control command generation: The parsed brainwave information will be converted into actual control commands. Depending on the frequency of the user’s gaze LED, the system will generate the corresponding flight control commands, such as left turn, forward turn, right turn, etc. This step requires an accurate mapping between EEG signals and UAV control commands.

Signal transmission and UAV control: The generated control commands will be transmitted to the UAV through the wireless transmission signal module. The UAV receives the control commands and realizes the corresponding flight actions according to the commands. This requires efficient communication and real-time performance to ensure that the commands are transmitted quickly and accurately to the UAV control system.

Real-time feedback and optimization: In order to improve the accuracy and user experience of the system, the system also needs to provide a real-time feedback mechanism. Users can get feedback on the status of the UAV during operation to help them better grasp the flight situation. At the same time, data is collected through the actual use of the user to continuously optimize the algorithm and system performance and achieve continuous improvement of the technology.

User interface and ease of use: The SSVEP-based FCS user interface enables users to intuitively understand the operation process and status of the system to ensure that the system is easy to use and user-friendly.

WiMi’s SSVEP-based FCS is not only limited to UAV maneuvering, but also has a wide range of applications in other fields. For example, this technology can be applied in the field of virtual reality (VR) and augmented reality (AR) to realize a more natural and intuitive user interaction experience. Users can control objects and environments in the virtual world through EEG signals, further expanding the possibilities of VR.

WiMi’s SSVEP-based FCS still faces some technical challenges in practical applications. The acquisition and parsing of EEG signals is one of the key issues. Since EEG signals are susceptible to disturbances, such as muscle activity and environmental noise, more precise signal processing algorithms are needed to improve the accuracy and stability of the system.

In the future, as BCI technology continues to evolve, WiMi’s SSVEP-based FCS is expected to achieve higher performance and a wider range of applications. More compact and comfortable EEG signal acquisition devices may emerge, enabling users to use the system more conveniently. Meanwhile, advances in signal processing algorithms and AI technology will further enhance the system’s intelligence and adaptivity.

WiMi’s development of SSVEP-based FCS is not only an integration of BCI and UAV, but also an active exploration of future technological innovation. By solving technical challenges, optimizing system architecture, and developing solutions suitable for applications in different fields, companies can bring unique and innovative contributions to this field and drive the accelerated development of the UAV control revolution. At the same time, cooperation and exchanges with other fields will provide more possibilities for technological upgrades and help human society move towards a smarter and more convenient future.

About WIMI Hologram Cloud

WIMI Hologram Cloud, Inc. (NASDAQ:WIMI) is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.

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