Automatic anesthesia state recording and labeling method

Abstract

The invention relates to the technical field of electronic medical treatment, in particular to an automatic anesthesia state recording and labeling method, which comprises the following steps: aligning a camera of an intelligent terminal to the face of a patient to obtain face data of the patient during an operation; after the operation is started, sending short-sound stimulation information to a Bluetooth headset worn by the patient through the intelligent terminal, and recording the brain wave data of the patient through an auditory evoked potential monitor worn by the patient; obtaining a first labeling result according to the brain wave data, inputting the face data into a neural network model, and carrying out automatic judgment and labeling of an anesthesia event to obtain a second labeling result; and outputting the second labeling result, and carrying out association recording with the patient. According to the invention, anesthesia events can be automatically recorded and labeled, and the problem that recorded data are not beneficial to follow-up clinical anesthesia scientific research and application due to errors caused by misreading of time, writing of wrong contents and the like by a recorder is avoided.

Description

technical field [0001] The invention relates to the field of electronic medical technology, in particular to an automatic recording and labeling method of an anesthesia state. Background technique [0002] In the existing surgical environment, the records of the anesthesia state (including the start of the operation, drug administration, induction, intubation, extubation, recovery and other anesthesia events) are usually recorded by the anesthesiologist or nurse, and most of them are recorded manually, such as Start time of surgery, start time of anesthesia induction, time of loss of consciousness, etc. However, there are two main problems in this method: one is that doctors or nurses pay more attention to the care of patients during intense operations and tend to ignore the recording of anesthesia events, and only record the events according to their own estimates after a delay Second, due to the influence of human factors, it is inevitable that there will be errors caused...

AI Technical Summary

Problems solved by technology

However, there are two main problems in this method: one is that doctors or nurses pay more attention to the care of patients during intense operations and tend to ignore the recording of anesthesia events, and only record the events according to their own estimates after a delay Second, due to the influence of human factors, it is inevitable that there will be errors caused by the recorder misreading the time, writing the wrong content, etc.

However, time records with errors or mistakes are very unfavorable for subsequent clinical anesthesia research and application.

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