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. Sleep is manually classified into five stages, which are wake, rapid eye movement (REM) sleep and three stages of non-REM sleep. It is estimated that up to one billion people worldwide suffer from obstructive sleep apnoea, and the number is expected to grow due to population ageing and increased prevalence of obesity. To overcome these challenges researchers used polysomnographic recording data from healthy individuals and individuals with suspected OSA to develop an accurate deep learning model for automatic classification of sleep stages.