Publications – AI for Sensor Data Analytics Ulm

Spilz, A., & Munz, M. (2024). Data Augmentation by Synthesizing IMU Data of Physiotherapeutic Exercises using Musculoskeletal Models. Current Directions in Biomedical Engineering, 10(4), 604–607. https://doi.org/10.1515/cdbme-2024-2148 Cite

Oppel, H., & Munz, M. (2024). IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems (No. arXiv:2411.02954). arXiv. https://doi.org/10.48550/arXiv.2411.02954 Cite

Karus, H., Schwenker, F., Munz, M., & Teutsch, M. (2024). Towards Explainable Visual Vessel Recognition Using Fine-Grained Classification and Image Retrieval. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 82–92. Cite

Oppel, H., & Munz, M. (2024). Smart Belay Device for Sport Climbing—An Analysis about Falling. Engineering Proceedings, 68(1), 29. Cite

Spilz, A., & Munz, M. (2023). Synchronisation of wearable inertial measurement units based on magnetometer data. Biomedical Engineering / Biomedizinische Technik, 68(3), 263–273. https://doi.org/10.1515/bmt-2021-0329 Cite

Kreuzer, D., & Munz, M. (2023). Transformer-Based UNet with Multi-Headed Cross-Attention Skip Connections to Eliminate Artifacts in Scanned Documents (No. arXiv:2306.02815). arXiv. https://doi.org/10.48550/arXiv.2306.02815 Cite

Oppel, H., & Munz, M. (2023). A Time Window Analysis for Time-Critical Decision Systems with Applications on Sports Climbing. AI, 5(1), 1–16. Cite

Spilz, A., & Munz, M. (2022). Automatic assessment of functional movement screening exercises with deep learning architectures. Sensors, 23(1), 5. Cite

Oppel, H., & Munz, M. (2022). Intelligent Instrumented Belaying System in Sports Climbing. Sensors and Measuring Systems; 21th ITG/GMA-Symposium, 1–7. Cite

Spilz, A., & Munz, M. (2021). Novel Approach To Synchronisation Of Wearable IMUs Based On Magnetometers (No. arXiv:2107.03147). arXiv. https://doi.org/10.48550/arXiv.2107.03147 Cite

Kreuzer, D., & Munz, M. (2021). Deep convolutional and LSTM networks on multi-channel time series data for gait phase recognition. Sensors, 21(3), 789. Cite

Oppel, H., & Munz, M. (2021). Analysis of Feature Dimension Reduction Techniques Applied on the Prediction of Impact Force in Sports Climbing Based on IMU Data. AI, 2(4), 662–683. Cite

Herbert, C., Nachtsheim, J., & Munz, M. (2020). Analysis of Gait-Event-related Brain Potentials During Instructed And Spontaneous Treadmill Walking -- Technical Affordances and used Methods (No. arXiv:2003.00783). arXiv. https://doi.org/10.48550/arXiv.2003.00783 Cite

Kreuzer, D., Munz, M., & Schlüter, S. (2020). Short-term temperature forecasts using a convolutional neural network—An application to different weather stations in Germany. Machine Learning with Applications, 2, 100007. Cite

Herbert, C., & Munz, M. (2020). Measuring gait-event-related brain potentials (gERPs) during instructed and spontaneous treadmill walking: technical solutions and automated classification through artificial neural networks. Applied Sciences, 10(16), 5405. Cite

Spilz, A., Engleder, T., Munz, M., & Karge, M. (2019). Development of a smart fabric force-sensing glove for physiotherapeutic Applications. Current Directions in Biomedical Engineering, 5(1), 513–515. https://doi.org/10.1515/cdbme-2019-0129 Cite

Munz, M., & Wolf, N. (2019). Simulation of Breathing Patterns and Classification of Sensor Data for the early detection of impending Sudden Infant Death. Current Directions in Biomedical Engineering, 5(1), 401–403. https://doi.org/10.1515/cdbme-2019-0101 Cite

Munz, M., & Engleder, T. (2019). Intelligent Assistant System for the Automatic Assessment of Fall Processes in Sports Climbing for Injury Prevention based on Inertial Sensor Data. Current Directions in Biomedical Engineering, 5(1), 183–186. https://doi.org/10.1515/cdbme-2019-0047 Cite

Kreuzer, D., Munz, M., Peifer, S., & Schlueter, S. (2019). Short-term Temperature Forecasts using Deep Learning–an Application to Data from Ulm, Germany. In ITISE 2019. Proceedings of papers. Vol 2. Cite

Munz, M., Och, F., Wenzel, U., Hessling, M., Hasch, K., Goldberg-Bockhorn, E., & Rotter, N. (2018). Histological Image Processing for the Assessment of Tissue Engineered Cartilage. Current Directions in Biomedical Engineering, 4(1), 461–464. https://doi.org/10.1515/cdbme-2018-0110 Cite

Wenzel, U., Princz, S., Dettmann, C., Goldberg-Bockhorn, E., Hasch, K., Körber, L., Lepiarz, T., Munz, M., Riepl, R., & Rotter, N. (2017). Neuer Knorpel aus dem Reaktor? Entwicklung eines Tissue-Engineering-Bioreaktors für Knorpel des Kopf-Hals-Bereichs. Cite

Lepiarz, T., Wenzel, U., Munz, M., Hasch, K., Goldberg-Bockhorn, E., Rotter, N., & Hessling, M. (2017). Computational analysis of histological images of tissue engineered cartilage for evaluation of scaffold cell migration. Journal of Biomedical Engineering and Medical Imaging, 4(6), 01. Cite

Maile, S., Kobel, S., Munz, M., Engleder, T., Steinacker, J. M., & Capanni, F. (2015). 3D-based visual physical activity assessment of children. Current Directions in Biomedical Engineering, 1(1), 462–465. https://doi.org/10.1515/cdbme-2015-0111 Cite