脑机接口技术临床应用提速，多位专家解码实施路径

Core Viewpoint - The article discusses the advancements in brain-computer interface (BCI) technology and its potential applications in medical diagnosis and treatment, emphasizing the need for integration with AI and the establishment of standardized clinical protocols [3][5][6]. Group 1: Current Developments in BCI Technology - BCI technology is expected to reshape the diagnosis and treatment of neurological diseases, necessitating a stronger integration between basic research and clinical application [5]. - A consensus on the clinical application pathways for implanted BCIs (iBCI) was published in January 2026, outlining management methods and clinical application processes [6]. - The main clinical value of BCI technology currently lies in medical rehabilitation, particularly for high-level paraplegic patients, enabling them to perform tasks like eating and moving through the control of robotic arms [6][7]. Group 2: Challenges and Future Directions - Current BCI devices face challenges such as low signal-to-noise ratios, interference, and the lack of universal brain signal decoding models [7]. - Future directions in BCI development may include the use of nanomaterials and flexible electrodes, as well as non-invasive BCI devices that can support cognitive science and sleep enhancement [7]. - A clinical trial demonstrated a 67.4% improvement rate in consciousness among patients with prolonged disorders of consciousness, indicating a new pathway for precise recovery [7]. Group 3: Integration of AI with BCI - The integration of AI into BCI technology shows significant potential for enhancing the functionality and practical value of BCI systems [8][9]. - AI can improve the dynamic optimization capabilities of BCI devices in areas such as neural signal decoding and intervention strategies [9]. - In the field of neurological disease management, AI can facilitate real-time adjustments to deep brain stimulation parameters based on pathological neural signals, improving treatment outcomes [10].