Simplified Process of Obstructive Sleep Apnea Detection Using ECG Signal Based Analysis with Data Flow Programming

The work is focused on detection of Obstructive Sleep apnea (OSA), a condition of cessation of breathing during night sleep caused by blockage of upper respiratory tract in an individual. ElectroCardioGram (ECG) signal is one of the clinically established procedures that can be relied on for deciding on the presence or absence of sleep apnea along with its severity in the subject at an earlier stage, so that the expert can advise for the relevant treatment. Earlier detection of OSA, can avoid the severe consequences leading to hypertension, Atrial-Fibrillation and day-time sleepiness that can affect the patient. ECG signal recordings from Apnea database from Physiobank, MIT website have been used for the purpose. The ECG signal based methods like QRS complex detection, RR interval variability, Respiratory Variability, Heart rate variability parameters used to detect OSA are compared and evaluated in order to select the most accurate method. Here we present the stepwise procedures, results and analysis of implementation methods used for detection of sleep apnea based on ECG signal using robust dataflow programming feature available in LabVIEW2014. Results indicate that accuracy, specificity and sensitivity of Heart Rate based detection method of OSA are 83%, 75% and 88% respectively and thus rated as one of the simple and reliable ways of detecting OSA.