ASCERTAINING THE SLEEP APNEA DISORDER IN CHILDREN AGE UNDER 15

The main purpose of this project is to detect the sleep apnea that is respiratory problem while sleeping. However, most minute-by-minute analysis techniques have difficulty detecting accurate event start/end positions. Furthermore, they require hand-engineered feature extraction and selection processes. In this project, we are going to approach for real-time apnea event detection using neural networks. This objective is used to predict the sleeping disorder for children by oxygen rate, sleep/wake status, noice in breathing by using neural network system and to bring about the ahi level in both boy and girl child who are affected by sleep hypnea.