New wrist-worn gadget to track your sleep habits: study

A new wrist-worn gadget may help people with sleep problems by objectively tracking their real-life sleep habits and quality, scientists say.
The gadget, called actimeter, records data on wrist movement from which one can obtain activity patterns for up to three months.
The researchers from the Ludwig Maximilian University of Munich (LMU) in Germany used the actimeters to assess rest/activity cycles not just over the course of the waking day, but also during sleep itself.
The findings are the latest in a larger, ongoing human sleep project, designed to learn more about sleep and its essential role in our lives by collecting sleep data on thousands of people in the real world.

"This will help many who have sleep problems and will hopefully increase the appreciation for the importance of sleep for our health and well-being," Till Roenneberg from LMU Munich said.
The team of researchers had been collecting information on sleep duration and quality via questionnaire.

The next step was to find a way to collect objective measurements of sleep characteristics on similarly large numbers of people.
In the new study published in the journal Current Biology, the researchers looked at actimeter data collected over more than 20,000 days from 574 subjects, aged 8 to 92 years.
However, the patterns of activity during sleep collected using the devices appeared rather messy. It was hard to discern the cyclical sleep patterns normally seen with other, more complicated devices in the lab.

By focusing on periods of inactivity during the night, a much clearer cyclical pattern began to emerge.
They used a simple conversion to measure inactivity (as opposed to activity) on a scale of near zero to 100, with 100 representing total inactivity.
"It was flabbergasting how it clarified the structures," Roenneberg said.
The researchers called the new measure "locomotor inactivity during sleep" (LIDS). Those measures showed that movement patterns reflect sleep cycles and replicate the dynamics seen in the lab.
"Many devices have tried to use activity to assess sleep structures, but our method is simple, transparent, and works especially in long-term recordings," Roenneberg said.