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Researchers use Fitbits, Apple Watches to help detect Parkinson's disease

New research suggests wearable devices like Apple Watches and Fitbits can provide information that can help detect sleep disorders linked to Parkinson's disease. File Photo by Keizo Mori/UPI
New research suggests wearable devices like Apple Watches and Fitbits can provide information that can help detect sleep disorders linked to Parkinson's disease. File Photo by Keizo Mori/UPI | License Photo

Feb. 14 (UPI) -- Researchers have developed a new method to detect early signs of Parkinson's disease by monitoring movements of patients during sleep by using available wearable technology, like Apple Watches or Fitbits, according to a study published in the journal Movement Disorders.

While the connection between Isolated rapid-eye-movement sleep behavior disorder and Parkinson's disease has been established, the researchers say, methods to gather accurate data to detect Parkinson's risk in individuals have not been available.

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"In the general population, the prevalence of [idiopathic REM sleep behavior disorder] is 1% to 2% of middle-aged and older adults. In neurology and sleep clinics the prevalence may be even higher; however diagnosing iRBD clinically is often challenging," according to the recently publlshed study.

Wearable devices like Apple Watches and Fitbits have "accelerometers," which monitor movement, even when the wearer is asleep. These devices are crucial to the new method of detection.

More than 80 participants in the study wore monitoring devices for 14 days, kept sleep journals and filled out a questionnaire. Of the participants, 40 had isolated rapid-eye movement sleep behavior disorder. A control group of 20 people with other sleep disorders and 20 people with no sleep disorders was used to compare data.

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"The methods involved analysis of home actigraphy data (for seven nights and more) and a nine-item questionnaire," the study says.

The data collected from the wearable devices in combination with the sleep journals and questionnaires will be used to develop machine learning to detect the potential signs of Parkinson's, researchers said.

A summary of the study reveals promising results, stating that analysis of movements during sleep could "detect isolated rapid-eye-movement sleep disorder with 92.9% accuracy," and that "all questionnaires combined achieved 91.7 % accuracy."

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