Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial

Autor: Caterina Bérubé, Vera Franziska Lehmann, Martin Maritsch, Mathias Kraus, Stefan Feuerriegel, Felix Wortmann, Thomas Züger, Christoph Stettler, Elgar Fleisch, A Baki Kocaballi, Tobias Kowatsch

Publikováno v: JMIR Human Factors, Vol 11, p e42823 (2024)

BackgroundHypoglycemia is a frequent and acute complication in type 1 diabetes mellitus (T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be detected and signaled through flash glucose monitoring or continuous gl

Externí odkaz: https://doaj.org/article/1e4b350e113548a68878864120251206

Toward Nonintrusive Camera-Based Heart Rate Variability Estimation in the Car Under Naturalistic Condition

Autor: Xiaoxi He, Martin Maritsch, Felix Wortmann, Zimu Zhou, Elgar Fleisch, Kevin Koch, Shu Liu

Publikováno v: IEEE Internet of Things Journal. 9:11699-11711

Driver status monitoring systems are a vital component of smart cars in the future, especially in the era when an increasing amount of time is spent in the vehicle. The heart rate (HR) is one of the most important physiological signals of driver stat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f9db16a211a2c1adaef51ed1628a9e5
https://doi.org/10.1109/jiot.2021.3131742

Non-invasive hypoglycemia detection in people with diabetes using smartwatch data

Autor: Christoph Stettler, Felix Wortmann, VThomas Zueger, Elgar Fleisch, Caroline Albrecht, Katja Odermatt, Sophie Lagger, Mathias Kraus, Eva van Weenen, Martin Maritsch, Simon Föll, Vera Lehmann

Aim To develop a non-invasive hypoglycemia detection approach using smartwatch data. Research Design and Methods We prospectively collected data from two wrist-worn wearables (Garmin vivoactive 4S; Empatica E4) and continuous glucose monitoring value

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dac3f1b918c08ba646f7249e93fcf3b5
https://doi.org/10.2337/figshare.21995150

Leveraging driver vehicle and environment interaction: Machine learning using driver monitoring cameras to detect drunk driving

Autor: Kevin Koch, Martin Maritsch, Eva Van Weenen, Stefan Feuerriegel, Matthias Pfäffli, Elgar Fleisch, Wolfgang Weinmann, Felix Wortmann

Publikováno v: CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Koch, Kevin; Maritsch, Martin; Van Weenen, Eva; Feuerriegel, Stefan; Pfäffli, Matthias; Fleisch, Elgar; Weinmann, Wolfgang; Wortmann, Felix (2023). Leveraging driver vehicle and environment interaction: Machine learning using driver monitoring cameras to detect drunk driving. In: CHI '23: CHI Conference on Human Factors in Computing Systems (pp. 1-32). New York, NY, USA: ACM 10.1145/3544548.3580975

Excessive alcohol consumption causes disability and death. Digital interventions are promising means to promote behavioral change and thus prevent alcohol-related harm, especially in critical moments such as driving. This requires real-time informati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dedd1e48aadfdb689938f0550124c091

Driver state prediction from vehicle signals: An evaluation of segmentation approaches

Autor: Martin Maritsch, Kevin Koch, Hauke Thomsen, Niklas Kuhl, Matthias Pfaffli, Wolfgang Weinmann, Felix Wortmann

Publikováno v: 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

Modern vehicles typically are equipped with assistance systems to support drivers in staying vigilant. To assess the driver state, such systems usually split characteristic vehicle signals into smaller segments which are subsequently fed into algorit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::814ef179f4cf19f3b690e7b0e9845870
https://hdl.handle.net/20.500.11850/556281