Early detection of clinical risk through wearables

Purpose and goal:

Investigate opportunities to use wearables (smart watches) to identify risk of symptom-explaining and/or preventable onset/deterioration of medical illness, using AI-based analysis of health data from sensors. Identification of heart rhythm disturbances in people with heart failure is used as a model, with the aim of scaling up to other medical applications and disease groups in the next step.

The project is initial work to establish a long-term collaboration between Sweden and Stanford University Palo Alto, California. Expected results and effects:

The project intends to increase knowledge about how AI and wearables can be combined to early identify complications in people living with chronic disease. At the same time, it will lay the foundation for a long-term collaboration between Sweden and Silicon Valley. A successful project will, after ascertained positive effects in a scaled-up study, be able to contribute to people (regardless of gender and ethnicity) being able to live longer with maintained health as deteriorations are detected in early treatable stages.

Approach and implementation:

The project is carried out by Sahlgrenska Universitetssjukhus, with data analysis in Region Halland. Results and implementation are supported by experts at Stanford School of Medicine. At the same time, a national scale-up is planned in Sweden to establish a more extensive collaboration between Sweden and Silicon Valley where more parties will be involved and the thematic area will be broadened.

The project has experts from medical disciplines and departments involved as advisors as well as from other leading university hospitals in Sweden, such as the Karolinska Institute.