Pain identification system based on confidence interval fusion threshold criterion

Abstract

The invention discloses a pain recognition system based on confidence interval fusion threshold criteria. The pain recognition system comprises a monitoring data acquisition module, a threshold processing module, a pain recognition module, an output module and an alarm module, the monitoring data acquisition module is used for acquiring multi-dimensional monitoring data; the threshold value processing module is used for fusing a threshold value criterion to preprocess the pain monitoring data; the pain recognition module carries out function training on the monitoring data by utilizing a constructed pain monitoring data grading model and determines a pain detection data confidence interval, and the output module is used for displaying a pain grade range corresponding to each real-time monitoring data training and transmitting the pain grade range to a medical personnel computer; and the alarm module is used for judging whether the monitoring data is within an effective range or not, and sending alarm information to prompt medical staff to process if the monitoring data is invalid. According to the invention, the pain degree of the patient can be accurately monitored and identified in real time, so that effective pain assessment and treatment of the patient are realized.

Description

technical field [0001] The invention relates to the field of medical technology, in particular to a pain recognition system based on confidence interval fusion threshold criterion. Background technique [0002] Pain is a feature of many diseases and causes some distress to patients. When the patient's condition changes, the pain will become more intense; when the patient's condition improves, the pain will weaken; when the patient recovers completely, the pain will disappear. At present, the results of pain assessment can be clinically used as an important indicator for monitoring the condition and measuring the effect of treatment. However, pain is a subjective feeling, which is easily interfered by many factors, such as state of consciousness, emotions, sensations and psychological effects. Because of its subjectivity, it brings unfavorable factors to the objective assessment of pain perception and follow-up treatment by medical staff. Currently, pain assessment mainly i...

AI Technical Summary

Problems solved by technology

At present, these technologies are basically based on traditional machine learning algorithms, which often collect physiological indicators such as patients’ vital signs and even brain waves and electromyographic signals. Among them, the indicators collected by vital signs monitoring are single, without data processing, and the training method is simple. There will be errors and false positives during the training process; the acquisition methods of brain waves and electromyography are relatively complicated, and require high equipment and technical requirements in actual clinical practice; pain recognition methods based on facial expressions are also becoming more and more complex. It has attracted the attention of scholars at home and abroad, but due to the complexity and controllability of adult facial expressions, few feature points are selected on the face, and the division of facial conditions and expressions is relatively general, so it is difficult to accurately detect the patient's own subjective pain degree

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