Entropy and Sleep Disorders

Dear Colleagues,

Although we spend about 1/3 of our life asleep, there has been relatively little attention paid to disorders of sleep until recently. Sleep disorders are amongst the most prevalent illness in today’s society. Unfortunately, the consequences of impaired sleep and sleep disorders are frequently under recognized and many patients go undiagnosed and untreated for years. Some of the most common sleep disorders are insomnia, sleep apnea, restless leg syndrome, narcolepsy, REM sleep behaviour disorder and parasomnias. These sleep disorders are often related to major medical conditions, such as heart disease, strokes and hypertension.

Polysomnography (PSG) is commonly ordered to search for sleep pathological conditions. PSG is a study conducted while patients are fully asleep or trying to sleep. Several biomedical signals are registered, including brain waves (electroencephalogram), eye movements (electroculogram), electrical activity of muscles (electromyogram), heart rate and electrical activity of hearth (electrocardiogram), blood oxygen levels, breathing effort or airflow. The aim of this Special Issue is to encourage researchers to present original and recent developments on time series analysis using entropy metrics, complexity quantifiers and related measures to study these biomedical signals during a PSG to help in the diagnosis of different sleep disorders.

Prof. Dr. Roberto Hornero
Guest Editor

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