Publikationen Fakultät Ingenieurwissenschaften HTWK Leipzig

Robotics and AI in Sports & Health Applications

• D. Matthes, P. Frenzel, M. Englert, J. Marek, T. Warnke, T. Kövari, M. Fuchs: Computer-Vision-gestützte Methoden zur Technik- und Wettkampfanalyse im Kanu-Rennsport. Tech-Werkstatt Leistungssport 2025, 06.-07. März 2025, Münster
• S. Rockstroh, P. Frenzel, D. Matthes, K. Schubert, D. Wollburg, M. Fuchs: Using deep neural networks to detect non-analytically defined expert event labels in canoe sprint force sensor signals. 2024 IEEE International Workshop on Sport Technology and Research (IEEE STAR), July, 2024, Lecco, Italy, pp. 205-210, doi: 10.1109/STAR62027.2024.10635918
• J. Sobisch, Ž. Bizjak, JH Choi, W. Park, M. Fuchs, Ž. Špiclin: Intracranial aneurysm rupture prediction: A deep learning based approach. 17th Research Festival for Life Sciences 2024, 18. Januar 2024, Leipzig
• F. Weiske, J. Jäkel: Robust and Cheap Safety Measure for Exoskeletal Learning Control with Estimated Uniform PAC (EUPAC). In: Proc. 31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Brügge, Belgien, 4.-6.10.2023
• B. Reichard, F. Schrumpf, F. Anders, K. Bode, M. Fuchs: Camera-based Pain Assessment during Surgical Interventions. Current Directions in Biomedical Engineering, vol. 8, no. 2, 2022, pp. 423-426. https://doi.org/10.1515/cdbme-2022-1108
• F. Schrumpf , P.R. Serdack, M. Fuchs: „Regression or Classification? Reflection on BP prediction from PPG data using Deep Neural Networks in the scope of practical applications“, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June, 2022, 2171-2180, doi: 10.1109/CVPRW56347.2022.00236, New Orleans, LA, USA, https://arxiv.org/abs/2204.05605
• M. Böhme, F. Weiske, J. Jäkel, J. Zentner, M. Witt: Evaluation of the power deficit of elderly people during stair negotiation - Which joints should be assisted at least by an exoskeleton and with what amount? Wearable Technologies, 2022, vol. 3, e4, DOI: https://doi.org/10.1017/wtc.2022.1
• M. Böhme, H.-P. Köhler, R. Thiel, J. Jäkel, J. Zentner, M. Witt: Preliminary Biomechanical Evaluation of a Novel Exoskeleton Robotic System to Assist Stair Climbing, Appl. Sci. 2022, 12(17), 8835; https://doi.org/10.3390/app12178835
• F. Schrumpf, P. Frenzel, C. Aust, G. Osterhoff, M. Fuchs: Assessment of non-invasive blood pressure prediction from PPG and rPPG signals using deep learning. Sensors, vol. 21(18), 2021, doi: 10.3390/s21186022
• F. Schrumpf, P. Frenzel, C. Aust, G. Osterhoff, M. Fuchs: Assessment of deep learning based blood pressure prediction from PPG and rPPG signals. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June, 2021, 3815-3825, doi: 10.1109/CVPRW53098.2021.00423, Nashville, TN, USA, https://arxiv.org/abs/2104.09313
• F. Weiske, M. Böhme, J. Jäkel, J. Zentner, M. Witt: Stair ascent comparison of lower limb kinematics with differing time normalization techniques, J. Biomech. Vol. 119, 15 Apr 2021; 110316. doi: 10.1016/j.jbiomech.2021.110316
• B. Reichard, F. Schrumpf, F. Anders, C. Mönch, K. Bode, M. Fuchs: Utilizing automatically estimated facial descriptors for pain detection during surgical interventions. 54th DGBMT Annual Conference / Jahrestagung Biomedizinische Technik (BMT 2020), September, 2020, Leipzig, Germany
• F. Schrumpf, P. Frenzel, C. Mönch, G. Osterhoff, M. Fuchs: PPG-based blood pressure estimation using residual neural networks and spectrograms. 54th DGBMT Annual Conference / Jahrestagung Biomedizinische Technik (BMT 2020), September, 2020, Leipzig, Germany
• M.-S. von Braun, P. Frenzel, C. Käding, M. Fuchs: Utilizing Mask R-CNN for Waterline Detection in Canoe Sprint Video Analysis. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June, 2020, 3826-3835, doi: 10.1109/CVPRW50498.2020.00446, Seattle, WA, USA, http://arxiv.org/abs/2004.09573
• M. Fuchs, P. Wagner, G. Bausch, P. Frenzel: Kamerabasierte Erfassung von Skelettdaten und Vitalparametern. Proceedings 19. Frühjahrsschule Technologien im Leistungssport, Schriftenreihe für Angewandte Trainingswissenschaft, 13, p. 62-73, May, 2018, Leipzig, Germany, Meyer & Meyer Verlag, ISBN 978-3-8403-7628-3
• F. Schrumpf, G. Bausch, M. Sturm, M. Fuchs: Similarity based hierarchical clustering of physiological parameters for the identification of health states – a feasibility study. Proceedings of the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 458-462, 2017, doi: 10.1109/EMBC.2017.8036861, Jeju Island, Korea, https://arxiv.org/abs/1803.09592