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HEADWIND: A Vehicle Hypoglycemia Warning System in Diabetes

Diabetes mellitus and its associated complications represent an important challenge to society and the health care systems globally. It is estimated that in 2021 537 million adults are living with diabetes, and that this number will increase to 784 million by 2045. Despite ongoing developments in the treatment of diabetes, hypoglycaemia (critically low glucose level) remains one of the most cumbersome acute complications. Hypoglycemia affects neuro-cognitive and psychomotor function and is associated with a significantly increased risk of driving mishaps and accidents. The current state of research regarding prevention of hypoglycemia-associated accidents is, unfortunately, still limited to rather general insights, while interventional approaches are urgently needed.

We, therefore, propose to apply state-of-the-art machine learning to neuro-cognitive and psychomotor function, automotive parameters, and physiological markers to reliably detect hypoglycaemia and give early and effective warning. Our project aims at designing, implementing, and evaluating an on-board vehicle hypoglycemia warning system (“HEADWIND”). The overall goal is to detect hypoglycemia in an early stage with high accuracy using a sensing module and then to trigger direct interventions through a support module. For this purpose we will study individuals with diabetes under hypoglycemic conditions induced through so-called clamp technology, first in a simulator setting and second in field studies in a real car setting (closed driving track). High-resolution real-time driving data and physiological sensors will be algorithmically integrated with driver camera video streams (eye and head pose tracking) to detect hypoglycemia.

HEADWIND receives public funding by the Swiss National Science Foundation (SNF). We develop an in-vehicle hypoglycemia warning system together with colleagues from the Inselspital Bern (Department of Diabetes, Endocrinology, Clinical Nutrition and Metabolism; principal investigator), the Bosch IoT Lab and the Center for Digital Health Interventions (CDHI) at ETH Zurich and the University of St. Gallen, the Chair of Management Information Systems at ETH Zurich, the Institute of AI in Management at the Ludwig Maximilian University of Munich, the Group of Data Analytics at the University of Erlangen-Nuremberg, and the Diabetes Center Berne.

Media

Publications

Lehmann, V., Maritsch, M., Züger, T., Marxer, A., Bérubé, C., Kraus, M., Albrecht, C., Feuerriegel, S., Kowatsch, T., Fleisch, E., Wortmann, F., Stettler, C., A machine learning-based approach to non-invasively detect hypoglycemia from gaze behavior while driving, 81st Scientific Sessions of the American Diabetes Association, Late Breaking Abstract, 10.2337/db21-5-LB.

Tripyla, A., Lehmann, V., Herzig, D., Meier, J., Banholzer, N., Maritsch, M., Feuerriegel, S., Wortmann, F., Bally, L., Driving performance after intake of glucose vs. aspartame in patients with postprandial hypoglycemia following gastric bypass surgery, 81st Scientific Sessions of the American Diabetes Association, 10.2337/db21-51-OR.

Lehmann, V., Züger, T., Kraus, M., Maritsch, M., Feuerriegel, S., Wortmann, F., Kowatsch, T., Albrecht, C., Bérubé, C., Styger, N., Lagger, S., Laimer, M., Fleisch, E., Stettler, C., HEADWIND: Design and Evaluation of a Vehicle Hypoglycemia Warning System in Diabetes – Results from a Driving Simulator Study, ATTD Advanced Technologies & Treatments for Diabetes Conference.

Lehmann, V., Tripyla, A., Herzig, D., Meier, J., Banholzer, N., Maritsch, M., Zehetner, J., Giachino, D., Nett, P., Feuerriegel, S., Wortmann, F., Bally, L., Driving performance after intake of glucose vs. aspartame in patients with postprandial hypoglycemia following gastric bypass surgery: single-blind, randomized crossover study, Diabetes, Obesity and Metabolism, 10.1111/dom.14456. [PDF]

Lehmann, V., Züger, T., Kraus, M., Maritsch, M., Feuerriegel, S., Wortmann, F., Kowatsch, T., Albrecht, C., Bérubé, C., Styger, N., Lagger, S., Laimer, M., Fleisch, E., Stettler, C., Headwind: design and evaluation of a vehicle hypoglycaemia warning system in diabetes – Results from a driving simulator study, Virtual Day of Biomedical Research, University of Bern (Covid-Pandemic).

Maritsch, M., Föll, S., Lehmann, V., Bérubé, C., Kraus, M., Feuerriegel, S., Kowatsch, T., Züger, T., Stettler, C., Fleisch, E., Wortmann, F., Towards Wearable-based Hypoglycemia Detection and Warning in Diabetes, Conference on Human Factors in Computing Systems – Late Breaking Work (CHI 2020), 10.1145/3334480.3382808. [PDF]

Züger, T., Lehmann, V., Kraus, M., Feuerriegel, S., Kowatsch, T., Wortmann, F., Laimer, M., Fleisch, E., Stettler, C., Headwind: design and evaluation of a vehicle hypoglycaemia warning system in diabetes: a proof of principle study, EASD Virtual Meeting (Covid-Pandemic).

Lehmann, V., Züger, T., Kraus, M., Maritsch, M., Feuerriegel, S., Wortmann, F., Kowatsch, T., Albrecht, C., Bérubé, C., Styger, N., Lagger, S., Laimer, M., Fleisch, E., Stettler, C., Individual Estimation of Blood Glucose and Self-Assessment of Driving Performance in Individuals with Type 1 Diabetes Driving in Hypoglycemia, Annual Assembly Schweizerische Gesellschaft für Endokrinologie und Diabetes (SGED).

Lehmann, V., Züger, T., Kraus, M., Maritsch, M., Feuerriegel, S., Wortmann, F., Kowatsch, T., Albrecht, C., Bérubé, C., Styger, N., Lagger, S., Laimer, M., Fleisch, E., Stettler, C., HEADWIND: Design and Evaluation of a Vehicle Hypoglycemia Warning System in Diabetes – Results from a Driving Simulator Study, Annual Assembly Schweizerische Gesellschaft für Endokrinologie und Diabetes (SGED).

Maritsch, M., Bérubé, C., Kraus, M., Lehmann, V., Züger, T., Feuerriegel, S., Kowatsch, T., Wortmann, F., Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning, 4th International Workshop on Mental Health: Sensing & Intervention, co-located with the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), London, UK, 10.1145/3341162.3346276. [PDF]

Züger, T., Lehmann, V., Kraus, M., Feuerriegel, S., Kowatsch, T., Wortmann, F., Laimer, M., Fleisch, E., Stettler, C., HEADWIND: Design and Evaluation of a Vehicle Hypoglycemia Warning System in Diabetes – A Proof of Principle Study, Poster presented at the Swiss Society of Endocrinology and Diabetology Annual Meeting 2019 (SGED 2019). Nov 14-15, Bern, Switzerland. [PDF]

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Martin Maritsch
Martin MaritschPh.D. candidate and doctoral researcher
2021-12-02T07:58:49+01:00February 5th, 2019|