Anesthesia patient resuscitation early warning method based on facial micro-action change detection

Abstract

The invention relates to an anaesthetic patient resuscitation early warning method based on facial micro-action change detection, which comprises the following steps: acquiring and preprocessing facial information video data of a patient to obtain a test sample; performing face detection on the face image of the patient in the test sample, and finding out a face position; detecting 68 feature key points on a human face by using a face feature point algorithm of a cascade regression tree model, obtaining feature points of 12 related eyes and 20 related mouths from the 68 feature key points, and calculating an eye EAR value and a mouth MAR value according to the segmented eye and mouth areas; and through calculating a waking state evaluation value F, carrying out waking state identification, and carrying out early warning according to the waking state. The real-time health data of the patient is obtained by calculating and analyzing the eye and mouth state data of the patient, and nursing personnel nurse the patient according to the obtained health data, so that the working efficiency is greatly improved, and the problem of insufficient nursing personnel is relieved to a certain extent.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a recovery early warning method for anesthetized patients based on facial micro-movement change detection. Background technique [0002] In recent years, with the continuous improvement of the medical level, the continuous development of modern anesthesiology and the continuous updating of testing equipment, the application of general anesthesia has become more and more extensive and safe. Both anesthesia and surgery will affect the physiological functions of patients, especially the first hour after anesthesia and surgery is the period that requires the most close care. Almost all anesthesia complications that endanger the patient's life safety will appear during this period. [0003] Traditional anesthesia patient resuscitation monitoring mainly relies on experienced doctors and nurses to monitor the patient's physical condition. The main problems are as follows: (1) ...

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Problems solved by technology

[0003] The traditional resuscitation monitoring of anesthesia patients mainly relies on experienced doctors and nurses to monitor the patient's physical condition. The main problems are as follows: (1) The human resources of the hospital are relatively tight, and the number of medical staff in the anesthesia recovery room is insufficient. There is a phenomenon of untimely nursing; (2) artificial monitoring is highly subjective, and negligence and misjudgment are often prone to occur during the monitoring process; (3) since artificial monitoring cannot realize real-time monitoring of each patient, monitoring and Nursing is usually lagging behind, making it difficult to realize timely detection and care of anesthesia recovery

[0004] Traditional monitoring methods can no longer meet the needs of today's hospitals in the current complex environment of recovery rooms

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