Open AccessSleep Stage Classification for Prediction of Human Sleep Disorders by Using Machine Learning Approach
Author(s) -
Mayuri A. Rakhonde,
Kishor P. Wagh,
R. V. Mante
Publication year - 2020
Publication title -
international journal of innovative science and research technology
Language(s) - English
Resource type - Journals
ISSN - 2456-2165
DOI - 10.38124/ijisrt20jul712
Subject(s) - sleep (system call) , sleep stages , artificial intelligence , computer science , stage (stratigraphy) , sleep patterns , machine learning , feature extraction , feature (linguistics) , pattern recognition (psychology) , electroencephalography , psychology , polysomnography , psychiatry , paleontology , linguistics , philosophy , biology , operating system
Sleep is a fundamental need of human body. In order to maintain health, sufficient sleep is must. 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. In this paper, we used Stochastic Gradient Descent(SGD) a machine learning algorithm for sleep stage classification. In feature extraction, Power Spectral Density(Welch method) is used. We acheived 89% overall accuracy using this model.