Innovative Solutions for Respiratory Rate Assessment: Computer Vision-based Estimators for Young Children

Respiratory diseases in children under the age of two, such as bronchiolitis or pneumonia, are a major cause of emergency consultations in hospital and primary care settings, being also a significant cause of mortality in low-income countries. Early detection of respiratory distress and high respiratory rate is crucial for timely intervention and improved clinical outcomes. In this study, we developed and evaluated two computer vision techniques for respiratory rate estimation in young children. The first technique, remote photoplethysmography, uses changes in skin color due to blood flow modulation to estimate the respiratory rate, while the second technique, designed in this work, uses the motion of a sticker placed on the patient's abdomen, and captures the variations of the reflected light throughout inhalation and exhalation. Both techniques were tested on a dataset of video recordings of children under the age of two taken in the Hospital 12 de Octubre of Madrid. Our results show that both techniques achieved accurate respiratory rate estimation, being the second technique the one with lower mean absolute error. For high respiratory frequencies, the values of the estimator are less than 3 bpm. These techniques have the potential to be used as low-cost and non-invasive tools for respiratory rate monitoring in low-resource settings, including remote and underserved areas of Africa. Besides, the elaboration of a labeled dataset will serve as potential groundwork for further research in this matter.