The algorithm is designed to detect early signs of apnea and assist in classifying central versus obstructive types. Which each require distinct clinical treatment. By capturing the neural respiratory drive directly through diaphragm sEMG, it shortens the time between apnea occurrence and effective intervention. Compared to conventional methods that rely on secondary symptoms like oxygen desaturation or bradycardia, this approach enables faster, more targeted clinical responses.