Multi-Layer Perceptron for Sleep Stage Classification
Intan Nurma Yulita, Rudi Rosadi, Sri Purwani, Mira Suryani · Journal of Physics Conference Series · 2018
Sleep apnea is a sleep disorder that causes decreasing or even stopping of breathing during sleep. One way to detect whether a person has the disorder or not, then it can be done by conducting a sleep test (polysomnogram). Polysomnogram provides overall body activity during sleep. Polysomnogram records every process of breath changes, muscle tension, brain waves, eye movements that occur in sleep from awake to the patient has dreams and finally wakes up. Once polysomnogram is obtained, then the doctor will check it. One of the targets of the analysis conducted is sleep stage classification. It takes a long time if done manually. Therefore, it needs an application that automatically to make classification efficiently. It is the main reason for this research that must be done. Specifically, this research applies Multi-Layer Perceptron (MLP) to classify the sleep stage. The results show that MLP has a higher performance than Naïve Bayes, Bayesian Networks, K-Nearest Neighbours, and Decision Tree.