Development of an Intelligent App for Obstructive Sleep Apnea Prediction on Android Smartphone Using Data Mining Approach

Abstract

In recent years, sleep apnea syndrome is considered an important research direction in sleep medicine. According to statistics, the disease prevalence of obstructive sleep apnea (OSA) is more than 3% of the total population and even up to 25% for 40-aged men. More and more clinical evidences showed that obstructive sleep apnea is highly associated with hypertension, diabetes, metabolic syndrome, cardiovascular disease, nocturnal enuresis, and even depression. If we can detect the potential OSA patients early, and offering them appropriate treatments, it is worth not only promoting the quality of patients¡¦ life, but also reducing the possible serious complications and medical costs. Mobile phones are now playing an ever more crucial role in people¡¦s daily lives. The latest generation of smart phones is increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage applications (Apps) development. In this study, an intelligent "OSA prediction App" on Android Smart phone has been developed based on medical decision rules from a clinical large dataset. The proposed application can provide an easy and efficient way to quickly pre-screen high-risk groups of OSA potential patients, aid medical works to achieve early diagnosis and treatment purposes, prevent the occurrence of complications, and thus reach the goal of preventive medicine.