Tracheal intubation difficulty detection method and system based on 3D video

The invention discloses a tracheal intubation difficulty detection method and system based on a 3D video, a depth camera and a 3D camera are used for collecting craniofacial morphology features, machine learning or an artificial intelligence model is used for analyzing the collected craniofacial morphology features, and then the tracheal intubation difficulty of an airway is detected. Therefore, the patient with laryngoscope exposure difficulty can be recognized as soon as possible, the difficult tracheal intubation and the intubation failure occurrence rate are reduced, and the method has important clinical significance. 本发明公开了一种基于3D视频的气管插管难度检测方法及系统，利用深度和3D相机采集颅面部形貌特征，利用机器学习或者人工智能模型对以上采集的颅面部形貌进行分析，进而对气道进气管插管难度检测，从而及早识别喉镜暴露困难的患者，降低困难气管插管及插管失败发生率，具有重要的临床意义。