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Sleep Cycle and Carnegie Mellon To Explore Sleep Data To Detect Outbreaks
Sleep Cycle and Carnegie Mellon To Explore Sleep Data To Detect Outbreaks
About this update from Sleep Cycle Ab
Research collaborative will investigatehow cough and breathing signals can support epidemiological modeling and forecasting efforts in the United States.Sleep Cycle, the world’s leading AI sleep technology company, today announced the kickoff of a five-year research collaboration withThe Delphi GroupatCarnegie Mellon University(CMU). This collaboration focuses on understanding how privacy-preserved data and sleep-based signals, such as nighttime cough patterns, may complement and enhance traditional respiratory disease surveillance systems and early detection of both seasonal and emerging disease outbreaks.Under the collaboration, Sleep Cycle will provide Delphi with deidentified research data related to coughing and breathing to support epidemiological modeling and forecasting research. The study will analyze trends derived from anonymized, differentially private data from Sleep Cycle’s Cough Radar, a public visualization tool that shows aggregated trends in nightly coughing intensity across regions. Researchers will explore whether these signals can provide earlier visibility into respiratory disease activity, including viruses such as influenza, RSV and SARS-CoV-2. Relevant research insights will be announced continuously during the research program.This study marks the first time that CMU’s Delphi Group — a leading epidemiologic research group that is coordinated by Professor Roni Rosenfeld — will systematically assess sleep app data as a potential input for national epidemiological monitoring and research in conjunction with other health indicators available on its Delphi Epidata platform.“This research will evaluate the utility of Sleep Cycle-derived cough and breathing signals for epidemiological surveillance applications,” said Professor Roni Rosenfeld, principal investigator of the Delphi Group at Carnegie Mellon University. “Our goal is to rigorously assess where these indicators can add value alongside existing public health data streams. Bolstered monitoring could lead to earlier detection of seasonal and emerging respiratory disease outbreaks, allowing health officials to react faster and safeguard the public health."Advancing Sleep Cycle’s Mission: From Reactive to Predictive HealthSleep Cycle’s data science and respiratory-signal research, including its proprietary audio-based cough detection technology, have demonstrated that nighttime cou...