To facilitate the performance comparison of new methods for sleep patterns analysis,
datasets with quality content, publicly-available, are very important and useful. We introduce …

Multiple types of sleep arousal account for a large proportion of the causes of sleep
disorders. The detection of sleep arousals is very important for diagnosing sleep disorders …

This book offers a comprehensive report on the technological aspects of Mobile Health
(mHealth) and discusses the main challenges and future directions in the field. It is divided …

Over the past decade, converging evidence from diverse studies has demonstrated that
sleep is closely associated with the mental and physical health, quality of life, and safety …

Manual classification of sleep stage is a time-consuming but necessary step in the diagnosis
and treatment of sleep disorders, and its automation has been an area of active study. The …

Diagnosis of depression using electroencephalography (EEG) is an emerging field of study.
When mental health facilities are unavailable, the use of EEG as an objective measure for …

Automatic diagnosis of the Sleep Apnea‐Hypopnea Syndrome (SAHS) has become an
important area of research due to the growing interest in the field of sleep medicine and the …

Poor-quality sleep substantially diminishes the overall quality of life. It has been shown that
sleep arousal serves as a good indicator for scoring sleep quality. However, patients are …

Sleep arousals are transient periods of wakefulness punctuated into sleep. Excessive sleep
arousals are associated with symptoms such as sympathetic activation, non-restorative …

Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an
optimized, state-of-the-art approach using data from daily work in our university hospital …