The application provides a method,
system, device and medium for determining
anesthesia consciousness, which comprises: obtaining a target electroencephalogram
signal of a target object; determining
consciousness state information of the target
object based on the target electroencephalogram
signal through a
consciousness determination model, wherein the consciousness state includes a
conscious state, a light
anesthesia state and an unconscious state; wherein the consciousness determination model is a
machine learning model, and the consciousness determination model is obtained based on training samples, wherein the training samples include sample electroencephalogram signals, and the sample electroencephalogram signals include sample
conscious state data, sample light
anesthesia state data and sample unconscious state data. Through the trained consciousness determination model, the change in anesthesia depth of the target object during the operation and the smooth transition thereof can be accurately tracked on the basis of accurately determining the unconscious state or the non-unconscious state of the target object, so that the regulation of the amount of
anesthetic drugs for the target patient during the operation is more accurate.