New feature in Sleep Cycle will identify who is snoring using technology with machine learning models.
Sleep Cycle, the market-leading app for sleep analysis, is now launching an innovative and patented function that, based on machine learning, identifies which snoring comes from each person in the same bedroom.
The new “Who snores?” feature distinguishes snoring sounds from two or more people sharing a bedroom.
Analysis from millions of users
Based on aggregated data from millions of users of the Sleep Cycles app, the company’s developers have succeeded in developing a feature that can differentiate between human snoring using machine learning models. This gives users an even more detailed picture of their sleep health.
Snoring can be a sign of obstructive sleep apnea, which has been linked to a number of negative health problems. Providing the user with sleep analysis that includes accurate snoring data, even in cases where users share a bedroom, is essential to act appropriately to improve sleep health and well-being.
Will help in the bedroom
– For those who share a bed with a snoring partner, the noise during the night can also disturb one’s own sleep health and one does not get the good night’s sleep one needs. Getting the opportunity to know more about snoring can help both the snorer and the person who shares a bed with a snorer to better sleep health, says Li Åslund, psychologist and sleep researcher at Sleep Cycle.
The new function complements existing tools in the app such as smart alarm, analysis through sound or motion detection, sleep music and meditations.
Sleep Cycle has patented the new feature which is initially available exclusively on the iOS platform.