Video laryngoscope with automatic blade detection

A video laryngoscope comprising:

• a handle portion;
• a display screen coupled to the handle portion;
• a blade portion, coupled to the handle portion and coupled to a blade, configured to be inserted into a mouth of a patient;
• a camera, positioned at a distal end of the blade portion, that acquires a video feed while the video laryngoscope is powered on;
• a memory storing a trained machine-learning (ML) model;
• and
• a processor that operates to:
• receive an image of the video feed from the camera, the image including a portion of the blade;
• provide the image as input to the trained ML model;
• receive an output from the trained ML model in response to the input image, wherein the output includes an identification of the blade;
• and
• transmit the blade identification to a remote device.

A method for blade size detection by a video laryngoscope, the method comprising:

• acquiring one or more images using a camera of the video laryngoscope;
• based on the one or more images:
• identifying a blade coupled to the video laryngoscope;
• determining a percentage of glottic opening (POGO) visible;
• and
• determining an outcome of intubation;
• and
• based on the blade identification, the POGO visible, and the outcome of intubation, determining a video classification of intubation (VCI) score.