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Publications, Faculty of Engineering, HTWK Leipzig

Research Profile: Robotics, Control & AI

Robotics and AI in Sports and Health Applications

  • D. Matthes, P. Frenzel, M. Englert, J. Marek, T. Warnke, T. Kövari, M. Fuchs: Computer vision-based methods for technique and competition analysis in canoe sprint. Tech-Werkstatt Leistungssport 2025, 6–7 March 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 January 2024, Leipzig
  • F. Weiske, J. Jäkel: Robust and Cheap Safety Measure for Exoskeletal Learning Control with Estimated Uniform PAC (EUPAC). In: Proc. 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, 4–6 October 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 to what extent? 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 normalisation 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: Utilising automatically estimated facial descriptors for pain detection during surgical interventions. 54th DGBMT Annual Conference / Annual Conference on Biomedical Engineering (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 / Annual Conference on Biomedical Engineering (BMT 2020), September 2020, Leipzig, Germany
  • M.-S. von Braun, P. Frenzel, C. Käding, M. Fuchs: Utilising 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: Camera-based acquisition of skeletal data and vital parameters. Proceedings of the 19th Spring School on Technologies in Competitive Sport, Series on Applied Training Science, 13, pp. 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

 

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