We developed a new, highly accurate sleep monitoring device that can comfortably records sleep at your home.
While sleep is essential for good health, sleep disorders are highly prevalent. This creates personal and economic costs, especially because inadequate sleep often remains undiagnosed. Sleep diagnostics are laborious and expensive for the health system and intrusive for the patients. Accurate monitoring requires nights in laboratories or setup by technicians, and diagnostics are almost exclusively done visually. As a result, waiting times for diagnostics are often >6 months, which keeps people from receiving effective treatment.
We developed a new, highly accurate sleep monitoring device that can comfortably records sleep at your home. We will create comprehensive sleep datasets using our new technology, incorporating a multitude of physiological and environmental sensors. Based on data collected in controlled and uncontrolled environments, we will realize robust AI-powered sleep analysis algorithms with medical-grade accuracy. We will publish the resulting datasets to stimulate the development of further data-driven solutions based on Bitbrain’s sleep data.
The main objectives of the experiment are:
- Explore new ways to accurately monitor sleep using comfortable physiological sensors.
- Collect multisensor sleep datasets in controlled laboratory and realistic home settings.
- Use these data to improve AI-powered sleep analysis.
- Publish the data to spark innovation in the sleep ehealth sector.
- new ergonomic sleep monitoring hardware for uncontrolled environments
- robust data analysis tools for the accurate assessment of sleep structure and quality
- Bitbrain has long taken steps to improve our environmental footprint and sustainability. All our devices are designed for long product life. In the EUH4D project, many parts of the systems are based on recycled and recyclable fabrics (under bluesign® certification) and can be replaced separately from the electronics.
- Gender equality is important at Bitbrain. 60% of Bitbrain’s management positions are filled by women (41 % of all positions), incl. our CEO.
- This project will produce comprehensive real-world sleep datasets. Based on these data we will develop accurate sleep stage scoring algorithms for noisy uncontrolled environments, which is a key data-driven innovation that will enable our future products.
- We will publish our recordings to demonstrate our technology and stimulate R&D and business operations in the space of sleep eHealth.
KPI 1. Create two comprehensive sleep datasets, in both laboratory and realistic settings.
KPI 2. Automatic offline and online detection of sleep stages with high accuracy using data from our new sensor technology.