This project integrates the characteristics of electroencephalo-graph（EEG）, cerebral oxygen, blood pressure, heart rate, etc., based on nonlinear theory and neural oscillation, large sample data and machine learning theory, to develop a multi-modal monitoring system suitable for domestic patients, taking into account changes in sedation, analgesia, cerebral hemodynamics and other factors, regardless of patient age and type of general anesthesia drugs.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
the depth of anesthesia (too deep or too shallow)
Timeframe: During general anesthesia