Authors : Mayuri A. Rakhonde; Dr. Kishor P. Wagh; Prof. Ravi V. Mante
Volume/Issue : Volume 5 - 2020, Issue 7 - July
Google Scholar : http://bitly.ws/9nMw
Scribd : https://bit.ly/2FoDHCD
DOI : 10.38124/IJISRT20JUL712
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.
Keywords : sleep stage classification, SGD, PSD Welch, machine learning etc.
