Determination of Various Deep Learning Parameter for Sleep Disorder

Artificial Intelligence (AI) is one of the major fields in computer science that is used to create the intellectual machine. AI refers to the imitation of human intelligence in machines that are programmed to work like humans and mimic their actions.[6] Deep Learning (DL) is one of the podium of artificial intelligence that work like a human brain in processing data and creating forms for use in decision making[1]. Sleep plays the important role in human life, they cannot sleep properly because some sleep related disorders can occur like sleep apnea, insomnia, hypersomnia. The preprocessing the feature extraction data, the sleep pattern features are import into a Bidirectional LSTM network for classifying the sleep stages [3]. The Bi-directional and Stacked LSTM are used to predict these disorders. Bi-directional LSTM is the part of recurrent neural network structure, it performed both forward and backward to predict the sleep related disorders.