Nowadays, sleep disorders are contemplated as the major issue in the human lives. The
current work aims at extraction of time-frequency information from recorded dataset and …

The Sleep stage classification has been accomplished using fuzzy inference system, where
the prerecorded data of sleep EEG has been processed with the help of wavelet transform …

The aim of this study is to detect the changes in frequency and power through wavelet
transform and assess the effects of externally induced heat stress in the classification of …

Human's sleep is divided into two segments, Rapid Eye Movement (REM) sleep and Non-
REM (NREM) sleep. NREM sleep is further divided into 4 stages. Sleep staging attempts to …

The present work aims at automatic identification of various sleep stages like, sleep stages
1, 2, slow wave sleep (sleep stages 3 and 4), REM sleep and wakefulness from single …

Sleep classification can be time-consuming and challenging for professionals since
electroencephalograms (EEGs) need to be segmented, evaluated, and manually annotated …

Depending on its intensity, sleep disorders can affect a person's ability to function mentally,
emotionally, and physically. These are medical abnormalities of the subject's sleep structure …

In the recent years analysis of Electroencephalogram (EEG) signal has played vital role in
automatic sleep scoring technique. Classification of sleep stages help in understanding …

In the current scenario, sleep-related problems increase day by day, which is a problem of
public health, where lot of many people are suffering from sleep disorder that affects their …

Sleep is a fundamental requirement of human life. It is one of the vital roles in human life to
maintain the proper mental health, physical health, and quality of life. In this proposed …