Automatic Detection and Classification of Sleep Disorders Using AI-Learning Models

Sleep disorders are very common and throw a bad impact on a health of person as well as quality of his day-to-day life. For successful treatment and intervention, sleep disorders must be found and categorised quickly and correctly. Traditional diagnostic methods rely heavily on human assessments that take a lot of time and cost a lot of money. The main objective of the research is to find out how artificial intelligence-based learning models such as machine learning and deep learning will be used to automatically find and classify sleep disorders. Apart from this, a comparative analysis has been also done to analyse the work of the researchers on the basis of their outcomes and challenges that still persist. Moreover, a framework has been also proposed that can be used in future to detect as well as classify multiple sleep disorder diseases using various machine as well as deep learning models.