#Digital Health
Informations- und Kommunikationstechnologie spielt im Gesundheitswesen eine immer größere Rolle. Digital-Health-Forschung bewegt sich an der Schnittstelle von Gesundheit, Sozialem und Digitalisierung – Resultate sind unter anderem Apps für das Gesundheitswesen und verbesserte Verfahren für Forschung, Diagnose, Therapie und Rehabilitation.
Publikationen
Horst, F., Hoitz, F., Slijepcevic, D., Schons, N., Beckmann, H., Nigg, B. M., & Schöllhorn, W. I. (2023). Identification of subject-specific responses to footwear during running. Scientific Reports, 13(1), 11284. https://doi.org/10.1038/s41598-023-38090-0
Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Towards more transparency: The utility of Grad-CAM in tracing back deep learning based classification decisions in children with cerebral palsy. Gait & Posture, 100, 32–33. https://doi.org/10.1016/j.gaitpost.2022.11.045
Durstberger, S., Kranzl, A., & Horsak, B. (2023). Effects of three different regression-based hip joint center localization methods in adolescents with obesity on kinematics and kinetics - preliminary results of the HIPstar study. Gait & Posture, 100, 42–43. https://doi.org/10.1016/j.gaitpost.2022.11.056
Vulpe-Grigorasi, A. (2023). Cognitive load assessment based on VR eye-tracking and biosensors. Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia, 589–591. https://doi.org/10.1145/3626705.3632618
Vulpe-Grigorasi, A. (2023). Multimodal machine learning for cognitive load based on eye tracking and biosensors. 2023 Symposium on Eye Tracking Research and Applications, 1–3. https://doi.org/10.1145/3588015.3589534
Slijepcevic, D., Horst, F., Simak, M., Lapuschkin, S., Raberger, A. M., Samek, W., Breiteneder, C., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2022). Explaining machine learning models for age classification in human gait analysis. Gait & Posture, 97, S252–S253. https://doi.org/10.1016/j.gaitpost.2022.07.153
Höld, E., Grüblbauer, J., Wiesholzer, M., Wewerka-Kreimel, D., Stieger, S., Kuschei, W., Kisser, P., Gützer, E., Hemetek, U., Ebner-Zarl, A., & Pripfl, J. (2022). Improving glycemic control in patients with type 2 diabetes mellitus through a peer support instant messaging service intervention (DiabPeerS): study protocol for a randomized controlled trial. Trials, 23(1), 308. https://doi.org/10.1186/s13063-022-06202-2
Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breitender, C., Schöllhorn, W., & Zeppelzauer, M. (2022). Explaining Machine Learning Models for Clinical Gait Analysis. ACM Transactions on Computing for Healthcare, 3(2), 14:1-14:27. https://doi.org/10.1145/3474121
Leung, V., Simone Hofbauer, Leonhartsberger, J., Kee, C., Liang, Y., & Schmied, R. (2022, 05). Influence of education systems on children’s visual behaviours as an environmental risk factor for myopia: a quantitative analysis with LIDAR-sensor tracking in classrooms. 18th International Myopia Conference, Rotterdam.
Rind, A., Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., & Horsak, B. (2022). Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy. Proc. 2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX), 7–15. https://doi.org/10.1109/TREX57753.2022.00006