Deep Learning for Sleep Disorders: A Review

Deep Learning is a revolutionary technology that has the potential to enhance the health care industry. Deep Learning interprets enormous numbers of unstructured data that humans would typically take decades to comprehend and process. This article discusses how Deep Learning is applied to predict different types of sleep disorders. It compares the various approaches made by different researchers, including the signals used, different algorithms, processing techniques, as well as their advantages and drawbacks. Sleep is an essential component. It is as much important as food, drinking and respiring, necessary for the normal physical and mental health maintenance. A multitude of serious medical conditions such as heart failure and diabetes have been linked to sleep deprivation and excessive sleep. As a result, it is important to monitor sleep using more feasible methods, in order to diagnose and distinguish sleep disorders. While there are several difficulties ahead, self-monitoring the sleeping routine could help to resolve this issue.