In a recent study published in NPJ Digital Medicine , researchers used a large dataset consisting of five million nights of sleep monitoring data from wearable devices to examine changes in an individual's sleep phenotype over time and determine if these changes in sleep patterns or phenotypes are informative about periods of acute illness such as fever, coronavirus disease 2019 (COVID-19), etc. Study: Five million nights: temporal dynamics in human sleep phenotypes . Image Credit: New Africa/Shutterstock.
com The rapid advancements in wearable device technology have made wearable health monitoring devices easily available and affordable. Apart from various other health parameters, these devices are widely used to monitor sleep patterns and quality. However, despite the abundance of sleep monitoring data, converting the insights drawn from this data into actionable changes has been challenging due to the variability in sleep parameter combinations across individuals and within individuals across time.
The National Institutes of Health recommendations state that adults should get seven to nine hours of monophasic sleep every day. However, sleep studies have shown that sleep structures vary significantly in length and quality, and these variations are associated with lifestyle- and health-related factors. Studies that have used clustering analyses for large-scale sleep data to quantify variations in sleep characteristics have been effective in characterizing sleep phenotypes but.