An intelligent detection and therapeutic device to support sleep apnea in infants

Abstract

Among the numerous sleep-disorders breathing patterns encountered by babies, such as intermittent respiration, premature apnea, obstructive sleep apnea wa sconsidered a major cause of concern. Upper airway structure, pulmonary system mechanics, etc. are only a few reasons why the babies are vulnerable to obstructive sleep disorder. An imbalance in the viscoelastic properties of the pharynx, dilators and pressure can lead to airway collapse. Low level of oxygen in blood or hypoxemia is considered a characteristic in infants with severe Obstructive Sleep Apnea (OSA). Invasive treatments like nasopharyngeal tubes, continuous positive airway pressure (CPAP), or tracheostomy are found to be helpful in most cases where infants experience sleep apnea. This paper suggests an appropriate method for long-term monitoring of obstructive sleep apnea in infants and, if any abnormalities are observed, the tool provides continuous airway pressure treatment until the abnormality is stabilized. Resilient propagation algorithm is utilised to train the datasets and produce a relevant output.