Method of detecting difficult airway, electronic equipment thereof and storage medium

Abstract

The embodiment of the invention provides a method for detecting a difficult airway. The method comprises the following steps: carrying out acoustic feature extraction and voice activity detection on voice audio of a user; carrying out average pooling processing on the extracted acoustic features to obtain a first embedded vector; inputting the sound production frame after activity detection into a deep speaker model used for representing a speaker of the difficult airway to obtain a second embedded vector representing the difficult airway; and inputting the first embedded vector and the second embedded vector into a support vector machine to detect the difficult airway. The embodiment of the invention further provides a detection system for the difficult airway. The embodiment of the invention realizes the detection of the difficult airway based on the voice technology. The problems that a traditional method is tedious, high in professional requirement and not accurate enough are solved. The speaker embedding well characterizes the physical structure of the airway. The voice signal is convenient to transmit, so that the user can detect only by using edge equipment, and the detection of the user is greatly facilitated.

Description

technical field [0001] The invention relates to the field of physiological structure detection, in particular to a detection method for a difficult airway, an electronic device and a storage medium thereof. Background technique [0002] Difficult airway refers to the special airway structure of the human body, which makes it difficult for a conventionally trained anesthesiologist to perform mask ventilation or tracheal intubation on the human body. Failure to detect a difficult airway on physical examination is the most important contributor to major complications associated with long-term morbidity, accounting for 25% of anesthesia-related deaths. Accurate detection of a potentially difficult airway is key to reducing morbidity and mortality from failed airway management. However, existing clinical assessments of difficult airways are neither convenient nor accurate. [0003] The extraction of several physical features used in clinical practice to detect difficult airways...

AI Technical Summary

Problems solved by technology

[0009] In order to at least solve the problem that the detection of difficult airway in the prior art has h

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