Washington: A team of researchers has come up with a system to accurately track the dynamic process of falling asleep, which may help in diagnosing sleep disorders.
Researchers at Massachusetts General Hospital (MGH) have described how combining key physiologic measurements with a behavioral task that does not interfere with sleep onset gives a better picture of the gradual process of falling asleep.
Lead author Michael Prerau said that while their personal experience tells us that falling asleep is a gradual process, current clinical methods only define a single point in time at which one has fallen asleep.
Prerau added that their new research shows that it's not simply when you fall asleep that's important, it's how you fall asleep that really matters and they now have the power to chart the entire trajectory of your neurological, physiological and behavioral activity as you transition from wake to asleep, rather than simply reporting the time it takes.
To link changes in brain activity to loss of consciousness during sleep onset, the investigators developed a new, minimally disruptive means of tracking behavior as someone falls asleep.
Earlier methods either used tasks in which a participant was asked to respond to auditory cues, something that could disrupt falling asleep, or actigraphy, the method of measuring movement used in most clinical sleep devices and consumer wearables, which cannot distinguish between sleep and motionless wakefulness.
The study is published in the open-access journal PLOS Computational Biology.