Innovative sleep solution provider dayzz announced this week the results of its first clinical trial. dayzz’ machine learning engine enables assessment of common sleep disturbances using a proprietary questionnaire. The clinical trial was conducted in collaboration with the Johns Hopkins Center for Interdisciplinary Sleep Research and Education.
In the U.S., more than 30% of the adult population suffer from sleep problems, and it is estimated that 50-70 million Americans have a sleep disorder that affects their health and quality of life. Many of them are undiagnosed and untreated. Insufficient sleep alone costs the US economy over $400 billion a year, and sleep problems among employees have huge financial implications on employers and payers. dayzz has developed and validated the Digital Sleep Questionnaire (DSQ) to identify common societal sleep disturbances including insomnia, delayed sleep phase syndrome, insufficient sleep syndrome, and risk for obstructive sleep apnea.
“dayzz’ machine learning algorithm was trained on gold-standard sleep expert diagnoses of people in the community with common sleep complaints and has shown high accuracy in predicting those at risk for prevalent sleep disorders,” said Dr. Mairav Cohen-Zion, Chief Science Officer at dayzz. “This is a critical step forward for dayzz in identifying sleep disorders at scale and offering a personalized sleep training experience for our users.”
In the upcoming months, dayzz will launch a randomized clinical trial in collaboration with researchers at Brigham and Women’s Hospital and Harvard Medical School to examine the effectiveness of its solution in a large community-based organizational setting. Read more here.