2results about How to "Guaranteed reversibility" patented technology

The present application relates to the technical field of nerve stimulation, and discloses a closed-loop vagus nerve precise blocking system and method based on physiological signal feedback, comprising a physiological signal monitoring unit for acquiring physiological signals of an individual in real time; a data acquisition and analysis module connected with the physiological signal monitoring unit, for receiving and analyzing the physiological signals, judging the physiological state of the individual, and generating a feedback signal; a stimulation device unit for outputting an electric stimulation signal based on the feedback signal, so that the vagus nerve stimulation reaches a functional block state; and a closed-loop feedback unit connected with the data acquisition and analysis module and the stimulation device unit, for dynamically adjusting the stimulation parameters according to the feedback signal and controlling the electric stimulation signal of the stimulation device in real time. Through the real-time monitoring and real-time feedback mechanism, the present application realizes functional block of the vagus nerve, and ensures the accuracy, safety and individualization of the inhibition operation.

This invention discloses a method and system for anomaly identification in multi-source monitoring data of steel structures, belonging to the field of steel structure monitoring data processing technology. The method includes acquiring multi-source monitoring data of steel structures and unifying time-scale alignment, generating a preprocessed dataset containing working condition features and quality markers. Based on the working condition features, the physical baseline prediction value is calculated; based on the preprocessed dataset, the data baseline prediction value is calculated, and dual residuals are obtained. The physical residual strength is calculated based on the dual residuals; and the residual inconsistency degree and sliding window adaptive threshold are calculated to output anomalies. This invention constructs a stable input through unified time-scale and quality marker constraints, generates physical and data dual baselines in parallel, and outputs dual residuals. Online discrimination is completed using correlation robustness strength + residual divergence adaptive weight + sliding window threshold, achieving an interpretable, traceable, and more robust anomaly identification process for long-term monitoring under working condition drift.