Traceable sleep data platform in Sweden forecasts impending COVID-19 outbreaks autonomously
Sleep Cycle, a popular sleep tracking app with over two million active users in over 150 countries, is making strides in the field of health monitoring. The app, listed on Nasdaq Stockholm under the ticker SLEEP, is currently investing heavily in the development of features related to snoring and coughing.
In a recent analysis, Sleep Cycle found a direct link between coughing and confirmed Omicron outbreaks in the United States, revealing the outbreaks before official statistics. This was made possible by a sound-detection algorithm that captures and analyzes movements, breathing, snoring, sounds from fans and pets, and sleep talking.
The app uses an intelligent alarm clock and sleep pattern analysis (deep, light, and REM cycles) measured through device sensors to provide insights into sleep quality and disturbances. While Sleep Cycle itself specifically tracks sleep phases and disturbances, the emerging AI-powered health monitoring technologies in sleep apps increasingly analyze data patterns to detect early signs of illness, including potential COVID-19 related physiological changes. These apps often integrate with wearable devices collecting heart rate, respiratory rate, and movement data to enhance detection accuracy and provide early alerts.
However, no direct detailed scientific description from the search results explains Sleep Cycle's exact COVID symptom detection mechanism. The closest correlation is their sleep pattern tracking and AI-driven analytics that could highlight anomalies in sleep indicative of health changes. For detecting COVID-19 specifically, other home testing technologies using biomarkers and AI smartphone analysis offer rapid virus identification within minutes.
Sleep Cycle's role is to detect early signs of illness through anomalous sleep data as an indirect marker, while rapid biomarker tests and advanced wearable health monitors provide more direct COVID detection tools.
In November 2021, Sleep Cycle analyzed coughing frequency during sleep in hundreds of thousands of American users. The company can continuously present frequency curves for a country or region, providing insights for the successful management of potential future Covid outbreaks.
Carl Johan Hederoth, CEO of Sleep Cycle, discusses the development of functions linked to snoring and coughing, foreseeing the launch of features that can indicate early stages of diseases linked to conditions such as snoring. The discovery poses opportunities to quickly identify and act on risks of potential future outbreaks without time-consuming data collection projects.
Sleep Cycle's mission is to improve global health by empowering people to sleep better. The app shares its aggregated data anonymously and collaborates with several universities around the world, contributing to research in the field of sleep and health. The head office of Sleep Cycle is located in Gothenburg, Sweden.
The analysis of cough data can have great social and economic significance, as it can be used to identify future Covid outbreaks in different parts of the world at an early stage. With its continuous data collection method, Sleep Cycle is well-positioned to play a crucial role in the early detection of diseases and the management of potential health crises.
- Sleep Cycle, a sleep tracker app, has discovered a correlation between coughing and confirmed Omicron outbreaks in the United States, highlighting outbreaks before official statistics.
- The emerging AI-powered health monitoring technologies within sleep apps, like Sleep Cycle, analyze data patterns to detect early signs of illness, including potential COVID-19 related physiological changes.
- Sleep Cycle's analysis of cough data, collected from hundreds of thousands of American users, can provide valuable insights for successful management of potential future Covid outbreaks worldwide.
- Sleep Cycle's data analytics, combined with technology, science, and collaboration with universities, positions it to play a vital role in detecting diseases like COVID-19 and managing potential health crises on a global scale.
