Towards wearable-based hypoglycemia detection and warning in diabetes
Maritsch M, Föll S, Lehmann V, Bérubé C, Kraus M, Feuerriegel S, Kowatsch T, Züger T, Stettler C, Fleisch E, Wortmann F (2020)
Publication Type: Conference contribution
Publication year: 2020
Publisher: Association for Computing Machinery
Conference Proceedings Title: Conference on Human Factors in Computing Systems - Proceedings
Event location: Honolulu, HI
ISBN: 9781450368193
Abstract
Rigorous blood glucose management is vital for individuals with diabetes to prevent states of too low blood glucose (hypoglycemia). While there are continuous glucose monitors available, they are expensive and not available for many patients. Related work suggests a correlation between the blood glucose level and physiological measures, such as heart rate variability. We therefore propose a machine learning model to detect hypoglycemia on basis of data from smartwatch sensors gathered in a proof-of-concept study. In further work, we want to integrate our model in wearables and warn individuals with diabetes of possible hypoglycemia. However, presenting just the detection output alone might be confusing to a patient especially if it is a false positive result. We thus use SHAP (SHapley Additive exPlanations) values for feature attribution and a method for subsequently explaining the model decision in a comprehensible way on smartwatches.
Authors with CRIS profile
Involved external institutions
Eidgenössische Technische Hochschule Zürich (ETHZ) / Swiss Federal Institute of Technology in Zurich
Switzerland (CH)
Universität St.Gallen
Switzerland (CH)
Inselspital, Universitätsspital Bern
Switzerland (CH)
Karlsruhe Institute of Technology (KIT)
Germany (DE)
Switzerland (CH)
Universität St.Gallen
Switzerland (CH)
Inselspital, Universitätsspital Bern
Switzerland (CH)
Karlsruhe Institute of Technology (KIT)
Germany (DE)
How to cite
APA:
Maritsch, M., Föll, S., Lehmann, V., Bérubé, C., Kraus, M., Feuerriegel, S.,... Wortmann, F. (2020). Towards wearable-based hypoglycemia detection and warning in diabetes. In Conference on Human Factors in Computing Systems - Proceedings. Honolulu, HI, US: Association for Computing Machinery.
MLA:
Maritsch, Martin, et al. "Towards wearable-based hypoglycemia detection and warning in diabetes." Proceedings of the 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020, Honolulu, HI Association for Computing Machinery, 2020.
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