New Closed-Loop Platform for Processing Brain Signals
The uMR Shenguan platform, developed by Shanghai United Imaging Healthcare and Tianjin University, is creating new infrastructure for brain-computer interface (BCI) technology. The system brings together signal acquisition, decoding, neuromodulation and evaluation within the same technical architecture. Introduced at the 1st National MR Brain-Computer Interface Conference held in August 2026, the infrastructure goes beyond traditional external device connections to provide a closed-loop control mechanism.
High Resolution in Time and Space
The platform can detect neural activity in the brain at millisecond-level intervals while examining the structure of brain tissue with sub-millimeter precision. It thus offers both temporal resolution, which enables the instantaneous monitoring of signals, and spatial resolution, which allows locations to be determined at the cellular level. The system also includes a specialized toolkit designed to eliminate magnetic field distortions caused by the implantation of BCI hardware.
Neural Plasticity Brought Under Control
By transforming the MR device from a tool used solely for imaging into a feedback center, this structure enables the measurement and control of neural plasticity, the brain’s capacity for reorganization. Using the same platform, researchers can monitor brain activity, carry out targeted interventions and measure the outcomes of these interventions in real time. This shift is progressing in parallel with the acceleration of biomedical investments in the country. In this direction, China is accelerating the state-supported commercialization of brain-chip technology and expanding the scope of clinical applications.
An Ecosystem from Clinical Use to Consumer Applications
The uMR Shenguan platform is intended for use in clinical fields such as motor rehabilitation, neurocritical care, psychiatry, ophthalmology and hearing disorders. Equipped with a magnetic compatibility toolbox, the system minimizes mutual interference between the scanner hardware and interface components. As the technology matures, it is expected to be widely used not only in the healthcare sector but also in education, sports, gaming technologies, sleep quality improvement and industrial safety.