Headwind

A Hypoglycaemia Warning System for the Prevention of Road Traffic Accidents
Background

Hypoglycemia has consistently been shown to be associated with an increased risk of driving mishaps.

Objective
As a prevention, this project investigates if machine learning models can be used to detect hypoglycemia in an early stage to trigger direct interventions through a support module.

People
The project is led by Prof. Dr. Christoph Stettler from the Inselspital Bern / University of Bern and Prof. Dr. Elgar Fleisch from the Center for Digital Health Interventions, University of St. Gallen and ETH Zurich. Prof. Dr. Mathias Kraus contributes to the development of the machine learning module.

Project Website
dcberne.com/de/projekte/headwind