In this paper, a rule-based automatic sleep staging method was proposed. Twelve features
including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized …

Scoring sleep stages from biological signals is an essential but labor-intensive inspection for
sleep diagnosis. The existing automated scoring methods have achieved high accuracy but …

This is a literature review paper covering state-of-the-art sleep technologies to measure
sleep and clinical sleep disorders. This paper addresses an interdisciplinary audience from …

Sleep is an essential process for the body that helps to maintain its health and vitality. The
first stage in the diagnosis and treatment of sleep disorders is sleep staging. Due to the …

Sleep quality, which is an undervalued health issue that affects well-being and daily lives, is
checked through the polysomnography (PSG), considered as the gold standard for …

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 …

Sleep is important part for human health and quality of life in the daily routine basis.
However, numerous individuals face sleep problems due to rapid changes occurred in both …

Background and objective: This paper presents a new framework for automatic classification
of sleep stages using a deep learning algorithm from single-channel EEG signals. Each …

Purpose With the advancement of deep neural networks in biosignals processing, the
performance of automatic sleep staging algorithms has improved significantly. However …

Sleep stage classification plays a significant role in the accurate diagnosis and treatment of
sleep-related diseases. This study aims to develop an efficient deep learning based scheme …