New deep learning model identifies sleep stages

Updated:5 years, 8 months ago

New Delhi, Feb 04 (ANI): 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. 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). 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. When untreated, OSA increases the risk of cardiovascular diseases and diabetes, among other severe health consequences. 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. According to the researchers, deep learning enables automatic sleep staging for suspected OSA patients with high accuracy.

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New deep learning model identifies sleep stages

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