Intelligent anesthesia system based on EEG-NIRS

Abstract

The invention discloses an intelligent anesthesia system based on EEG-NIRS. The intelligent anesthesia system based on EEG-NIRS includes a head-mounted signal acquisition module, an anesthesia automatic control module and a data storage module, wherein the head-mounted signal acquisition module comprises a near-infrared light source driving part, an acquisition part, and a control and WIFI communication part, synchronously collects EEG signals and NIRS signals, and transmits the pre-processed EEG and NIRS signals to the anesthesia automatic control module through WIFI communication; the automatic anesthesia control module has functions of dynamic monitoring of anesthesia index, calculation of the required dose and injection speed for a patient through a feedback controller, deep neural network optimization, multi-channel anesthetic injection, etc; and the data storage module can dynamically record the anesthesia data and key nodes, and upload the anesthesia data and key nodes to a server. The intelligent anesthesia system based on EEG-NIRS collects EEG and NIRS signals at the same time, dynamically monitors sedation, analgesia and muscle relaxation of intraoperative patients, accurately controls the infusion rate and infusion volume of anesthetic agents, greatly improves the utilization rate of medical resources, and reduces the use-cost of medical equipment.

Description

technical field [0001] The present invention relates to the field of intelligent anesthesia control, in particular to an intelligent anesthesia system based on EEG-NIRS signals, which can realize automatic and precise administration of anesthesia during operation, monitoring of vital signs, and safety monitoring and early warning. Background technique [0002] At present, in clinical anesthesia operations, the number of general anesthesia operations has increased significantly, but the number of anesthesiologists is obviously insufficient, resulting in excessive work pressure for anesthesiologists and increased surgical risks. At the same time, the inaccurate infusion of anesthesia drugs is inevitably caused by the inherent operating errors of human hands. Therefore, how to use modern scientific and technological achievements to reduce the workload of anesthesiologists and improve the accuracy of anesthesia infusion has become urgent. [0003] In the process of general anes...

AI Technical Summary

Problems solved by technology

[0004] Although there have been many studies on anesthesia monitoring and closed-loop control, because BIS, TOF, ANI and other monitoring equipment are independently configured, medical resources have not been well integrated to achieve automatic information feedback and communication, and automatic

Images