"不同的人脑电波差异很大，以往的脑机接口设备在使用前需要长达30分钟的校正实验，通过数据采 集、多次实验，现如今的脑机接口设备不用长时间校准，戴上就可以用。"琶洲实验室脑机智能研究中 心科研人员许凯琳表示，非侵入式装置小巧便捷，不仅不用做手术，避免出现排异反应，还因不会被长 出的体内细胞遮蔽信号，后期相较侵入式脑机接口装置信号更稳定。 将大脑状态"翻译"成可量化的信号 当"脑电波"隔空操控轮椅从科幻走进现实，AI手语翻译架起沟通的桥梁，科技正为残障群体带来生活新 可能。日前，广州市科技局（十五运会和残特奥会科技工作专班办公室）组织举办的"探秘全运黑科 技"公众开放日系列活动走进琶洲实验室，探索科技助残新路径。 非侵入式接口即戴即用 脑机AI轮椅可用"意念"隔空控制 "脑机接口"是指通过在人脑神经与具有高生物相容性的外部设备间建立直接连接通路，实现神经系统和 外部设备间信息交互与功能整合的技术。简而言之，便是直接通过大脑向机器发指令。 区别于传统轮椅只能用动作、语音控制，脑机AI轮椅依赖使用者高度集中的注意力与平缓的头部转 动，通过凝视屏幕光标实现操控。"你需要习惯它的灵敏度，就像与自己的意识对话。"华南理工大 ...

Core Insights - The rapid development of AI in the medical field is creating a new industry segment, but it does not equate to AI directly diagnosing patients [2] - The integration of AI with human brain functions aims to address issues like sleep disorders and mental health through real-time monitoring and intervention [2][8] - The research team led by Professor Li Yuanqing is pioneering non-invasive brain-computer interface (BCI) technology in China [2][5] Group 1: Technology and Products - The key innovation is the "multi-modal brain-computer AI headband," which collects and analyzes brainwave signals to provide feedback [3][5] - The system can monitor and intervene in mental health issues such as depression and anxiety, as well as assist in focus training for children [8][10] - The BCI technology allows for control of external devices through brain signals, enhancing the functionality of smart medical equipment [12][14] Group 2: Market and Applications - The BCI products have gained traction in both domestic and international markets, with positive reception in the U.S. and plans to expand into the UK, Germany, and Japan [10][11] - Institutions such as psychological counseling centers and schools show higher enthusiasm for these products compared to individual consumers [11] - Clinical trials for BCI applications are underway in various hospitals, targeting patients with physical disabilities and neurological conditions [16] Group 3: Research and Development - The research team has made significant breakthroughs in BCI technology over the past 20 years, focusing on the collection and processing of brainwave signals [18][19] - The integration of AI and deep learning has enhanced the performance and accuracy of BCI systems [22] - The team is also exploring the potential of semi-invasive and invasive BCI technologies, which could offer higher signal quality for medical applications [23] Group 4: Challenges and Future Directions - The transition from research to commercialization faces hurdles such as market development and regulatory approval for medical devices [24] - Achieving seamless brain-machine integration remains a long-term goal, with ongoing advancements expected to bring the technology closer to this vision [25]

Core Insights - The development of a brain-machine AI mouse allows paralyzed patients to control devices without physical movement, significantly enhancing their quality of life [1][2] - The technology, developed by a team led by Li Yuanqing, has been recognized for its potential in assisting individuals with disabilities and has been implemented in various hospitals [2][4] Group 1: Technology Overview - The brain-machine interface technology captures and decodes multi-modal signals such as EEG, eye movement, and head motion to accurately identify user intentions [2] - This technology serves as an interface between the human brain and external devices, translating brain signals into control commands for various applications [2] Group 2: Product Development and Application - The research team has focused on the commercialization of their findings since 2019, resulting in products like the brain-machine AI mouse, AI wheelchair, and smart hospital solutions [2] - The brain-machine AI mouse has been successfully tested in hospitals, improving the self-care capabilities of patients with physical disabilities [2] Group 3: Future Prospects - The advancement of brain science and machine learning algorithms presents significant opportunities for the application of brain-machine interface technology in monitoring and rehabilitating brain disorders [4]

Core Insights - The article discusses the advancements and applications of brain-computer interface (BCI) technology, highlighting its growing maturity and various industrial applications both domestically and internationally [1][2]. Signal Acquisition - The first step in BCI technology is signal acquisition, which involves using a headband equipped with electrodes and amplifiers to collect weak brain electrical signals, typically in the range of tens of microvolts [3]. - The technology requires high sensitivity to accurately capture these signals and amplify them for further processing [3]. Noise Reduction - The second step involves noise reduction, where advanced techniques such as independent component analysis and frequency analysis are employed to filter out irrelevant signals and enhance the fidelity of brain signals [3][4]. Signal Translation - The third step is translating brain signals into machine-readable digital signals using artificial intelligence algorithms and powerful chips, which is a key strength of the research team [4]. Device Control - The fourth step allows the BCI to control various external devices, enabling applications such as helping stroke patients operate exoskeletons [5]. Feedback Mechanism - The fifth step involves creating a feedback loop where external devices provide information back to the brain, enhancing the interaction between the user and the technology [7]. Technology Types - BCI technology is categorized into invasive and non-invasive types, with non-invasive methods being more popular due to their affordability and safety, while invasive methods offer higher accuracy but require surgical procedures [7]. Application Scenarios - The BCI mindfulness meditation system has gained popularity, particularly in international markets, with positive user reviews on platforms like Amazon [8]. - The team has developed a BCI AI mouse that allows users to control a computer cursor using brain signals, aimed at assisting individuals with disabilities [8]. - Clinical trials for BCI AI smart wards are underway in several hospitals, allowing patients to control their environment through brain signals [9][10]. Future Applications - BCI technology has the potential to assist patients with movement recovery, language restoration, and seamless interaction with smart home devices [11][12]. - It can also be applied in various fields such as industrial monitoring, transportation, education, and gaming to enhance user experience and safety [12]. Investment and Development - The BCI sector is attracting attention from investors, with discussions on the need for collaboration among researchers, clinical institutions, and capital to foster innovation and commercialization [13][14]. - The industry is in a transitional phase from basic research to clinical applications, with a growing number of clinical trials and patent applications in China [13][14]. Research Focus - The research center emphasizes the importance of ensuring safety in BCI technology while continuously improving the accuracy and efficiency of brain signal decoding [15][16].