TY - JOUR A1 - Tröster, Mark A1 - Eckstein, Simon A1 - Kennel, Paula A1 - Kopp, Verna A1 - Benkiser, Alina A1 - Bihlmeier, Felicitas A1 - Daub, Urban A1 - Maufroy, Christophe A1 - Dendorfer, Sebastian A1 - Fritzsche, Lars A1 - Schneider, Urs A1 - Bauernhasl, Thomas T1 - Person-specific evaluation method for occupational exoskeletons - Biomechanical body heat map JF - Applied Ergonomics N2 - Human-centred and ergonomic work design is one of the most important drivers for increasing the competitiveness of the European Union. As a flexible, person-specific occupational measure, exoskeletons promise great potential for effectively reducing individual ergonomic stress. Digital human models can provide important insights and offer great potential for systematising the effect and targeted use of exoskeletons, supporting their effective implementation in practice. In this article, digital human models are applied on two levels. Firstly, a realistic industrial logistics scenario in which boxes had to be relocated is designed with the help of a digital human model for workplace and process planning and secondly, a new biomechanical evaluation methodology to analyse intended and unintended effects on internal stress on the human body is demonstrated by applying musculoskeletal exoskeleton human models of four test subjects. Finally, the modelled biomechanical support tendencies of one exoskeleton are preliminary validated using EMG measurement data of the back muscles collected from the four male workers. The preliminary analysis of two back-support exoskeletons to demonstrate the new methodological approach confirms the expected, intended effects in the lower back and reveals unintended effects, such as e.g. changes in knee kinetics when applying a soft or hard-frame exoskeleton. Furthermore, the exemplary results to demonstrate the methodological approach expose notable differences between the test subjects, which underlines the relevance of person-specific evaluation and consideration of exoskeleton support. The preliminary validation shows a correlation between the modelled and the EMG-measured biomechanical exoskeleton support of the considered back muscles. KW - Industry 5.0 KW - Ergonomics KW - Digital human modelling KW - Biomechanics KW - Musculoskeletal modelling KW - Occupational exoskeletons Y1 - 2025 U6 - https://doi.org/10.1016/j.apergo.2025.104671 VL - 132 PB - Elsevier ER - TY - GEN A1 - Gschoßmann, Lukas A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Impact of Model Parameters on Ground Reaction Force Predictions in Musculoskeletal Modelling T2 - ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27-31 July, Stockholm N2 - This study evaluated how model parameters affect ground reaction force (GRF) predictions in musculoskeletal simulations. A parameter study varying contact height and velocity thresholds and marker weights was conducted. While height and velocity thresholds had minimal impact, marker weights impact prediction errors. These findings highlight the importance of carefully selecting model parameters. Y1 - 2025 ER - TY - JOUR A1 - Winter, Lina A1 - Artinger, Annalena A1 - Böck, Hendrik A1 - Ramakrishnan, Vignesh A1 - Reible, Bruno A1 - Albin, Jan A1 - Schüffler, Peter J. A1 - Raptis, Georgios A1 - Brochhausen, Christoph T1 - Developing a smart and scalable tool for histopathological education—PATe 2.0 JF - Journal of Pathology Informatics N2 - Digital microscopy plays a crucial role in pathology education, providing scalable and standardized access to learning resources. In response, we present PATe 2.0, a scalable redeveloped web-application of the former PATe system from 2015. PATe 2.0 was developed using an agile, iterative process and built on a microservices architecture to ensure modularity, scalability, and reliability. It integrates a modern web-based user interface optimized for desktop and tablet use and automates key workflows such as whole-slide image uploads and processing. Performance tests demonstrated that PATe 2.0 significantly reduces tile request times compared to PATe, despite handling larger tiles. The platform supports open formats like DICOM and OpenSlide, enhancing its interoperability and adaptability across institutions. PATe 2.0 represents a robust digital microscopy solution in pathology education enhancing usability, performance, and flexibility. Its design enables future integration of research algorithms and highlights it as a pivotal tool for advancing pathology education and research. Y1 - 2026 U6 - https://doi.org/10.1016/j.jpi.2025.100535 SN - 2153-3539 VL - 20 PB - Elsevier ER - TY - GEN A1 - Stein, Leonhard A1 - Schmitz, Paul A1 - Kretschmer, Rainer A1 - Dendorfer, Sebastian T1 - Gait parameter based fall risk scoring N2 - This study explored the connection between subjective self-assessed gait insecurities and objective movement scores. 93 subjects answered detailed fall risk questionnaires and performed functional tests. Significantly different movement patterns between fallers and non-fallers were found. Y1 - 2025 ER - TY - GEN A1 - Förstl, Nikolas A1 - Adler, Ina A1 - Süß, Franz A1 - Jansová, Magdalena A1 - Vychytil, Jan A1 - Dendorfer, Sebastian T1 - Evaluating the loads on the female pelvic floor during full-body activities using computational models N2 - This work investigated the loads on the female pelvic floor during various full-body movements using computational models to calculate abdominal pressure and organ dynamic loads. While high-impact exercises resulted in higher loads, other movements showed lower loads, potentially indicating, which movements may be performed without risking pelvic floor overload and subsequent dysfunctions. Y1 - 2025 ER - TY - GEN A1 - Barthel, Mareike A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Predicting intra-abdominal pressure during walking and running T2 - ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27-31. July 2025, Stockholm N2 - Intra-abdominal pressure (IAP) is an important physiological parameter, which is difficult to measure during physical activity. In this study, motion capture, musculoskeletal modeling and a transformer encoder model are used to predict IAP during walking and running. The model showed promising results with an overall mean percentage error of 13.5% and a Pearson correlation coefficient of 0.85. Minor challenges included the lower accuracy for fast walking and running and the limited amount of data. All in all, the prediction of IAP was successful, which opens up prospects for further applications. KW - Intra-abdominal pressure; machine learning; motion capture; musculoskeletal modeling; transformer encoder Y1 - 2025 ER - TY - INPR A1 - Rückert, Tobias A1 - Rauber, David A1 - Maerkl, Raphaela A1 - Klausmann, Leonard A1 - Yildiran, Suemeyye R. A1 - Gutbrod, Max A1 - Nunes, Danilo Weber A1 - Moreno, Alvaro Fernandez A1 - Luengo, Imanol A1 - Stoyanov, Danail A1 - Toussaint, Nicolas A1 - Cho, Enki A1 - Kim, Hyeon Bae A1 - Choo, Oh Sung A1 - Kim, Ka Young A1 - Kim, Seong Tae A1 - Arantes, Gonçalo A1 - Song, Kehan A1 - Zhu, Jianjun A1 - Xiong, Junchen A1 - Lin, Tingyi A1 - Kikuchi, Shunsuke A1 - Matsuzaki, Hiroki A1 - Kouno, Atsushi A1 - Manesco, João Renato Ribeiro A1 - Papa, João Paulo A1 - Choi, Tae-Min A1 - Jeong, Tae Kyeong A1 - Park, Juyoun A1 - Alabi, Oluwatosin A1 - Wei, Meng A1 - Vercauteren, Tom A1 - Wu, Runzhi A1 - Xu, Mengya A1 - an Wang, A1 - Bai, Long A1 - Ren, Hongliang A1 - Yamlahi, Amine A1 - Hennighausen, Jakob A1 - Maier-Hein, Lena A1 - Kondo, Satoshi A1 - Kasai, Satoshi A1 - Hirasawa, Kousuke A1 - Yang, Shu A1 - Wang, Yihui A1 - Chen, Hao A1 - Rodríguez, Santiago A1 - Aparicio, Nicolás A1 - Manrique, Leonardo A1 - Lyons, Juan Camilo A1 - Hosie, Olivia A1 - Ayobi, Nicolás A1 - Arbeláez, Pablo A1 - Li, Yiping A1 - Khalil, Yasmina Al A1 - Nasirihaghighi, Sahar A1 - Speidel, Stefanie A1 - Rückert, Daniel A1 - Feussner, Hubertus A1 - Wilhelm, Dirk A1 - Palm, Christoph T1 - Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge N2 - Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context - such as the current procedural phase - has emerged as a promising strategy to improve robustness and interpretability. To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures. We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding. Y1 - 2025 N1 - Der Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/start/0/rows/10/sortfield/score/sortorder/desc/searchtype/simple/query/10.1016%2Fj.media.2026.103945/docId/8846 ER - TY - GEN A1 - Adler, Ina A1 - Förstl, Nikolas A1 - Čechová, Hana A1 - Nováček, Vít A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Mechanistic analysis of pelvic floor functionality using musculoskeletal simulation T2 - ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27-31 July 2025, Stockholm N2 - There is consensus that knowledge about the fundamentals of the pelvic floor remains incomplete, particularly regarding the sensitivity of individual pelvic floor muscles to posture variations. This study aimed to investigate the effects of variations in pelvic tilt and the point of force application induced by changes in posture on pelvic floor activity using musculoskeletal simulation. A parameter study analysed various loading cases, highlighting the coherent response of individual pelvic floor muscles to loads. Muscle activities and forces were compared across different force application points and pelvic tilt angles. A key finding was identifying peak muscle activity conditions that could help better understand the causes of pelvic floor disorders. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-87294 ER - TY - GEN A1 - Gschoßmann, Lukas A1 - Schedel, Valentin A1 - Süß, Franz A1 - Weber, Markus A1 - Pfingsten, Andrea A1 - Dendorfer, Sebastian T1 - Evaluating Knee Joint Loads Across Exercises and Activities of Daily Living to Personalize TKA Rehabilitation T2 - ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27.-31. July 2025, Stockholm N2 - This study assessed knee joint loading during various physiotherapy exercises and activities of daily living in 30 healthy subjects. Results showed that lunges and squats caused the highest joint forces, while gait and stair activities also imposed substantial loads. These findings support datadriven exercise selection for personalized rehabilitation after total knee arthroplasty. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-87252 ER - TY - JOUR A1 - Rueckert, Tobias A1 - Rauber, David A1 - Maerkl, Raphaela A1 - Klausmann, Leonard A1 - Yildiran, Suemeyye R. A1 - Gutbrod, Max A1 - Nunes, Danilo Weber A1 - Moreno, Alvaro Fernandez A1 - Luengo, Imanol A1 - Stoyanov, Danail A1 - Toussaint, Nicolas A1 - Cho, Enki A1 - Kim, Hyeon Bae A1 - Choo, Oh Sung A1 - Kim, Ka Young A1 - Kim, Seong Tae A1 - Arantes, Gonçalo A1 - Song, Kehan A1 - Zhu, Jianjun A1 - Xiong, Junchen A1 - Lin, Tingyi A1 - Kikuchi, Shunsuke A1 - Matsuzaki, Hiroki A1 - Kouno, Atsushi A1 - Manesco, João Renato Ribeiro A1 - Papa, João Paulo A1 - Choi, Tae-Min A1 - Jeong, Tae Kyeong A1 - Park, Juyoun A1 - Alabi, Oluwatosin A1 - Wei, Meng A1 - Vercauteren, Tom A1 - Wu, Runzhi A1 - Xu, Mengya A1 - Wang, An A1 - Bai, Long A1 - Ren, Hongliang A1 - Yamlahi, Amine A1 - Hennighausen, Jakob A1 - Maier-Hein, Lena A1 - Kondo, Satoshi A1 - Kasai, Satoshi A1 - Hirasawa, Kousuke A1 - Yang, Shu A1 - Wang, Yihui A1 - Chen, Hao A1 - Rodríguez, Santiago A1 - Aparicio, Nicolás A1 - Manrique, Leonardo A1 - Palm, Christoph A1 - Wilhelm, Dirk A1 - Feussner, Hubertus A1 - Rueckert, Daniel A1 - Speidel, Stefanie A1 - Nasirihaghighi, Sahar A1 - Al Khalil, Yasmina A1 - Li, Yiping A1 - Arbeláez, Pablo A1 - Ayobi, Nicolás A1 - Hosie, Olivia A1 - Lyons, Juan Camilo T1 - Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge JF - Medical Image Analysis N2 - Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context – such as the current procedural phase – has emerged as a promising strategy to improve robustness and interpretability. To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures. We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding. KW - Surgical phase recognition KW - Instrument keypoint estimation KW - Instrument instance segmentation KW - Robot-assisted surgery Y1 - 2026 U6 - https://doi.org/10.1016/j.media.2026.103945 SN - 1361-8415 N1 - Corresponding author der OTH Regensburg: Tobias Rueckert Die Preprint-Version ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/solrsearch/index/search/start/0/rows/10/sortfield/score/sortorder/desc/searchtype/simple/query/2507.16559 VL - 109 PB - Elsevier ER -