Creating Computer Vision Models for Respiratory Status Detection

Abstract

This study aims to use computers to detect and recognize ventilation objects (masks and tubes) and their positions on the patient's face. We created two models: the You Only Look Once (YOLO) and the Transfer Learning (TL) models, to perform this computer vision task. The development processes and comparison of performance will be described in this paper. The TL model had a better performance (93%) compared to the YOLO model (93%). Clinical Relevance- Healthcare providers and researchers interested in the field of computer vision applied in medicine, specifically automatic object detection using video streams or real-time video streaming may benefit from findings reported.