Publikationen Fakultät Ingenieurwissenschaften HTWK Leipzig

Biomesstechnik und Biosignalverarbeitung

• Poßner, L., Wilhelmy, F., Wegner, S., Müller, S., Pliquett, U., Knösche, T. R., ... & Lindner, D. (2022, September). Effect of contact pressure on porcine postmortem brain tissue impedance. In 2022 International Workshop on Impedance Spectroscopy (IWIS) (pp. 36-40). IEEE. https://ieeexplore.ieee.org/abstract/document/9975122
• Poßner, L., Seebeck, L., Laukner, M., Wilhelmy, F., Lindner, D., Pliquett, U., ... & Weise, K. (2021). A four-point measurement probe for brain tissue conductivity and permittivity characterization. bioRxiv, 2021-04. https://www.biorxiv.org/content/10.1101/2021.04.29.441988v2.abstract
• Poßner, L., Laukner, M., Wilhelmy, F., Lindner, D., Pliquett, U., Petkovic, B., ... & Weise, K. (2020). In situ impedance measurements on postmortem porcine brain. Current Directions in Biomedical Engineering, 6(3), 143-146. https://www.degruyter.com/document/doi/10.1515/cdbme-2020-3037/html
• Maaß, Sebastian (2023): Ein digitales Verfahren zur Ultraschall-Laufzeitdifferenzmessung. Dissertation, TU Dresden https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-868199
• Maaß, S., Laukner, M (2020): Ultrasonic Time Delay Difference Estimation With Analytic Signals and a Model System. IEEE Transactions on Circuits and Systems II: Express Briefs, Volume: 67 https://ieeexplore.ieee.org/document/8861086
• Guttke, Sebastian (2017): Ein Verfahren zur störungsarmen Erfassung der Pulsfrequenz unter Bewegungsbedingungen. Dissertation Universität Rostock https://rosdok.uni-rostock.de/resolve/id/rosdok_disshab_0000001725
• Guttke, S., Laukner, M., Weber, P. (2014): Flexible sensor for pulse rate measurement under moving conditions, BMT 2014 Hannover
• Guttke S., Laukner M., Weber P. (2013): Cross sensitivity of different electrode types for impedance plethysmography under motion conditions. 2013 J. Phys.: Conf. Ser. 434 012028 XV Int. Conf. on Electrical Bio-Impedance & XIV Conf. on Electrical Impedance Tomography. https://iopscience.iop.org/article/10.1088/1742-6596/434/1/012028
• Sebastian Guttke, Matthias Laukner (2011): Verfahren zur störungsarmen Erfassung der Pulsfrequenz unter extremen Bewegungsbedingungen, Konferenzband zur 12. Nachwuchswissenschaftlerkonferenz, Wernigerode, 2011
• Laukner, M.; Lehmann, F.; Gothe, C.; Kretschmer, C.-P. (2004): Digitale Rekonstruktionsverfahren für die Lungenfunktionsdiagnostik. Forschungsbericht 2004 der HTWK Leipzig
• 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
• 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. Schrumpf, C. Mönch, G. Bausch, M. Fuchs: Exploiting weak head movements for camera-based respiration detection. Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 6059-6062, 2019, doi: 10.1109/EMBC.2019.88563872019, Berlin, Germany, https://arxiv.org/abs/1906.08192
• 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
• F. Schrumpf, G. Bausch, M. Sturm, M. Fuchs: Derivation of the respiratory rate from directly and indirectly measured respiratory signals using autocorrelation. Current Directions in Biomedical Engineering, vol. 2(1), 241-245, September, 2016, ISSN (Online) 2364-5504, doi: 10.1515/cdbme-2016-0054
• C. Pieloth, T.R. Knösche, B. Maess, M. Fuchs: Online Distributed Source Localization from EEG/MEG Data. International Journal of Computing, vol. 13(1), p. 17-24, August, 2014, ISSN 2312-5381