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Research from 5 million nights of sleep revealed that sleep trackers can help detect chronic and acute health conditions by analyzing transitions between identified sleep phenotypes, offering a deeper insight into health than traditional sleep metrics alone.
UC San Diego PhD student Varun Viswanath is the paper’s corresponding author. The researchers analyzed data from the Oura ring, a smart wearable that tracks temperature, sleep, and other information. Credit: David Baillot/University of California San Diego The analyses were led by Smarr, who is also faculty in the University of California San Diego Shu Chien – Gene Lay Department of Bioengineering, and Professor Edward Wang in the University of California San Diego Department of Electrical and Computer Engineering, collaborating with the study lead at University of California, San Francisco, Professor Ashley E. Mason, a practicing sleep clinician.
Phenotype 5: People only sleep for very short periods of time every night. This phenotype was the rarest the researchers found, and represents extremely disrupted sleep.To measure how sleep phenotypes changed over time, Viswanath constructed a spatial model of all 5 million nights, in which the phenotypes were represented as different islands, composed of mostly similar weeks of sleep.
Conversely, people did not tend to remain in patterns defined by broken-up sleep. But how often they visited specific disrupted sleep patterns says a lot about how well they’re doing.
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