Abstract
Sleep disorders are major healthcare problems that are increasing at a rapid rate throughout the world. Sleep disorders are major psychiatric disorders that have massive, long-lasting negative impacts on patients as well as society. The death rate due to sleep disorders is increasing every day. These disorders are a global problem in the health sector; millions of people are affected and die every year from sleep disorders. Sleep disorders have a great impact on the patient’s quality of life. A sleep study is crucial for proper diagnosis of sleep disorders. Because sleep disorders are so complex, proper treatment is often inefficient. Machine learning techniques are one of the emerging research domains in the health field, especially in the area of different types of sleep disorders. This chapter briefly presents various types of sleep disorders and treatment methods and technologies for the classification of sleep abnormalities. The main objective of this chapter is to analyze sleep abnormalities during different transition states of sleep and thereby help clinicians and researchers to design the most cost-effective and user-friendly systems to diagnose sleep diseases.
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