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Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab30200114c6?from=tech
April 15, 2023
It is reported that WIMI is developing a wearable EEG electronic device for the brain-AI closed-loop system, which can enhance autonomous machine decision-making. The device monitors an electroencephalogram (EEG) of human brain activity and transmits this data to a computer system connected to it. The device uses electroencephalography (EEG) technology, which captures the electrical activity of the brain by attaching electrodes to the scalp. These signals can reflect the state of human perception, including the degree of brain activation, frequency and time domain characteristics, etc. These signals are very weak, generally at the level of microvolts to millivolts.
Therefore, high-sensitivity electrodes and signal enhancement equipment such as amplifiers are required in the signal collection process to ensure accurate signal collection and reliable transmission. After the data acquisition is completed, the device needs to transmit the data to an external computer system for analysis and processing. Therefore, the device is equipped with a communication module that uses wireless technology for data transmission, which allows real-time data transmission and processing. At the same time, signal interference and distortion during transmission can be avoided.
WIMI's wearable EEG electronic device for brain-AI closed-loop system is a complex system integrating sensors, high-sensitivity electrodes, signal enhancement and processors, communication modules, etc., which can capture the brain's electrical activity signals and transmit it to an external computer system for analytical processing. Accurate signal acquisition and real-time data transmission and processing can be achieved, thus providing a reliable data source and decision support for the brain-AI closed-loop system. Wearing comfort and portability were also important considerations in the design of the device. Since the device is worn for extended periods of time, it must be comfortable to wear. At the same time, in order to facilitate portability and use, the device uses lightweight materials and a flexible design that can adapt to the shape of the head, thereby ensuring wearing comfort and stability.
Through the wearable EEG electronic device used by WIMI for the brain-AI closed-loop system, we can realize two-way communication from the human brain to the computer system to realize autonomous machine decision-making. An example of such a system is a brain-machine interface (BMI), which allows people to control external devices such as computer games, artificial limbs, etc. through purely mental activities. In a closed-loop system, the EEG device detects changes in brain activity and transmits this information to a computer system. Computer systems may analyze this data to determine whether certain actions are warranted or to be taken. For example, if the system detects that the user's brain activity indicates that they are experiencing cognitive overload, the system can automatically adjust the difficulty of the task or provide appropriate prompts to help the user complete the task.
The technology to realize the brain-AI closed-loop system requires the following steps and components:
Wearable EEG device:
This device can monitor brain activity through sensors and electrodes, and transmit the signal to a computer system.
Data acquisition and processing:
Process and analyze the signals collected from EEG equipment, such as removing noise, screening useful signals and extracting features. These operations can be done using some data processing tools and algorithms, such as filtering, time-frequency analysis, machine learning and other techniques.
Human brain activity decoding:
Decode the signals collected from EEG equipment into specific human brain activities, such as cognition, emotion, movement, etc. This requires the use of some human brain activity decoding algorithms, such as classifiers, neural networks and other technologies.
AI algorithms and models:
use decoded human brain activity data to train and optimize machine learning models and algorithms. These models and algorithms can be used to analyze human brain activity, predict user intentions, emotions, and needs, and make decisions and adjust tasks autonomously.
Autonomous machine decision-making:
By combining human brain activity decoding with AI algorithms, autonomous machine decision-making is realized. For example, the system could automatically adjust the difficulty of tasks or provide hints when a user's brain activity indicates they need help. These decisions can be made in a closed-loop system, enabling real-time interaction between humans and machines.
With the rapid development of AI technology, artificial intelligence plays an increasingly important role in various fields. However, the existing AI systems can have amazing performance in the feeding of large amounts of data and system algorithms, but they often cannot accurately capture human emotions and intentions, which limits the scope of application of AI technology. The wearable EEG electronic device used in the brain-AI closed-loop system by WIMI can measure the electrical activity signals of the brain, and through these signals, we can accurately capture human emotions and intentions. A closed loop is established between the AI ??system and humans. Through the data collected by the device, the AI ??system can make more intelligent decisions based on human emotions and intentions. Through wireless communication technology, it can communicate with the AI ??system in real time to achieve fast data transmission and response. In addition, the device can also detect the emotional state of human beings by monitoring the electrical signals of the brain, so as to adjust the working state of the AI ????system in time to better adapt to human needs.
WIMI (NASDAQ: WIMI) has a very broad market prospect and application space for wearable EEG electronic devices used in brain-AI closed-loop systems. It will promote more intelligent interactions between humans and machines, enhance autonomous machine decision-making, enhance the intelligence level of AI systems, and improve user experience and efficiency. At the same time, the device also has strong adaptability and comfort, and can be used more and more widely in fields such as medical treatment, entertainment, games, human-computer interaction, and robotics.
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