Sleep disorders: A review on different deep learning algorithm.

As per our health is concern main parameter we can consider like sleep for our health regeneration, memorization and main aspect like recovery of our immune system. An essential part of overall health. Before detecting sleep issues in our body suppose if we have some machine or any ideas that helps to patients who is goes in narrow for their sleep issues for that if we can go with some tools and help us to analyzed before happening to sleep disorder. Using the algorithm of DL, we can explore the research in healthcare system. DL models helps to work with wide range of unformatted dataset which helps to understand how sleep issues are coming into human being based on some parameters we can learn some procedure. By using survey, we are going to specifies the different DL models are used to detect various types of problems present into the human being with different sleep stages. It compares different approaches by several authors who are working in this area, consider some different channels like eeg, ecg and many more. Also, they have worked with classification of DL models and different Methodologies with some pros, cons and conclusion. The main and very important aspect is sleep for regenerating some cells of body during sleeping time of any human being. As we consider better sleep in any people, they need to take proper nutrition, sleep, enough amount of H2O, breathing rate to balance. It is as important as eating, drinking and breathing, necessary for the normal maintenance of fitness and psychological filling well. There are many health issues are related to sleep disorders like sugar level, heart problems, long time sleeping, not getting sleep and many others. [ABSTRACT FROM AUTHOR]