Abstract
Sleep is fundamental need of human life. In order to maintain good health, sufficient sleep is must. Sleep deficiency causes many health issues. Efficiency of sleep is based on sleep stages. Sleep stage classification is required to identify sleep disorders. Sleep stage classification identifies different stages of sleep and it is an important as well as complex step in the identification of sleep diseases. Here, different techniques are studied about sleep stage classification. This study reviews various techniques which are used to classify sleep stages. For classification, polysomnographic recordings are used and it contains various signals like EEG, ECG, EMG. According to study, two main techniques are used as Machine Learning and Convolutional Neural Network.
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