Preliminary diagnosis of sleep apnea using a mobile app

Abstract

We are building a low-cost and portable device, which can be controlled by patient's Android smartphone, to measure sleep. The device is easy to use and consists of Airow (Rate of respiration), Pulse Oximeter (Heart rate and SpO2), Accelerometer (PLM), and EEG (Brain waves) sensors. The data that is collected is stored in the Cloud. The results are summarized and seen on phones of doctors and patients. The product serves as a screening device for Sleep Apnea. We have also integrated popular fitness trackers (such as the Fitbit Charge HR) into the system, and utilised Machine Learning and Data Mining algorithms to analyse the quality of a person's sleep. One can now be tested in the comforts of their home to check whether they should go for an expensive Polysomnography Test (PSG) at a hospital. Doctors can now monitor their patients remotely for symptoms of Sleep Apnea, a disease which is hard to diagnose using conventional methods.