Automated Detection and Classification of Sleep Apnea Types using Opencv Python

Description

Obstructive sleep apnea (OSA) is a prevalent but severely undiagnosed sleep disorder that impacts the natural breathing cycle during sleep with decreased breathing periods or no airflow at all. New sleep apnea classification techniques are nowadays being developed by bioengineers for most comfortable and timely detection. This project focuses on logistic regression and k-means Clustering algorithms to get better accuracy.