New deep learning model identifies sleep stages

RESEARCHERS at the University of Eastern Finland have developed a new deep learning model that can identify sleep stages as accurately as an experienced physician.

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Sleep is manually classified into five stages, which are wake, rapid eye movement (REM) sleep and three stages of non-REM sleep. The study published in the IEEE Journal of Biomedical and Health Informatics opened up new avenues for the diagnostics and treatment of sleep disorders including obstructive sleep apnoea (OSA). OSA is a nocturnal breathing disorder that causes a major burden on public health care systems and national economies.

It is estimated that up to one billion people world-wide suffer from obstructive sleep apnoea, and the number is expected to grow due to population ageing and increased prevalence of obesity. When untreated, OSA increases the risk of cardiovascular diseases and diabetes, among other severe health consequences.