TY - GEN A1 - Scheppach, Markus W. A1 - Nunes, Danilo Weber A1 - Arizi, X. A1 - Rauber, David A1 - Probst, Andreas A1 - Nagl, Sandra A1 - Römmele, Christoph A1 - Meinikheim, Michael A1 - Palm, Christoph A1 - Messmann, Helmut A1 - Ebigbo, Alanna T1 - Procedural phase recognition in endoscopic submucosal dissection (ESD) using artificial intelligence (AI) T2 - Endoscopy N2 - Aims Recent evidence suggests the possibility of intraprocedural phase recognition in surgical operations as well as endoscopic interventions such as peroral endoscopic myotomy and endoscopic submucosal dissection (ESD) by AI-algorithms. The intricate measurement of intraprocedural phase distribution may deepen the understanding of the procedure. Furthermore, real-time quality assessment as well as automation of reporting may become possible. Therefore, we aimed to develop an AI-algorithm for intraprocedural phase recognition during ESD. Methods A training dataset of 364385 single images from 9 full-length ESD videos was compiled. Each frame was classified into one procedural phase. Phases included scope manipulation, marking, injection, application of electrical current and bleeding. Allocation of each frame was only possible to one category. This training dataset was used to train a Video Swin transformer to recognize the phases. Temporal information was included via logarithmic frame sampling. Validation was performed using two separate ESD videos with 29801 single frames. Results The validation yielded sensitivities of 97.81%, 97.83%, 95.53%, 85.01% and 87.55% for scope manipulation, marking, injection, electric application and bleeding, respectively. Specificities of 77.78%, 90.91%, 95.91%, 93.65% and 84.76% were measured for the same parameters. Conclusions The developed algorithm was able to classify full-length ESD videos on a frame-by-frame basis into the predefined classes with high sensitivities and specificities. Future research will aim at the development of quality metrics based on single-operator phase distribution. Y1 - 2024 U6 - https://doi.org/10.1055/s-0044-1783804 VL - 56 IS - S 02 SP - S439 PB - Thieme CY - Stuttgart ER - TY - GEN A1 - Scheppach, Markus W. A1 - Weber Nunes, Danilo A1 - Arizi, X. A1 - Rauber, David A1 - Probst, Andreas A1 - Nagl, Sandra A1 - Römmele, Christoph A1 - Palm, Christoph A1 - Messmann, Helmut A1 - Ebigbo, Alanna T1 - Single frame workflow recognition during endoscopic submucosal dissection (ESD) using artificial intelligence (AI) T2 - Endoscopy N2 - Aims  Precise surgical phase recognition and evaluation may improve our understanding of complex endoscopic procedures. Furthermore, quality control measurements and endoscopy training could benefit from objective descriptions of surgical phase distributions. Therefore, we aimed to develop an artificial intelligence algorithm for frame-by-frame operational phase recognition during endoscopic submucosal dissection (ESD). Methods  Full length ESD-videos from 31 patients comprising 6.297.782 single images were collected retrospectively. Videos were annotated on a frame-by-frame basis for the operational macro-phases diagnostics, marking, injection, dissection and bleeding. Further subphases were the application of electrical current, visible injection of fluid into the submucosal space and scope manipulation, leading to 11 phases in total. 4.975.699 frames (21 patients) were used for training of a video swin transformer using uniform frame sampling for temporal information. Hyperparameter tuning was performed with 897.325 further frames (6 patients), while 424.758 frames (4 patients) were used for validation. Results  The overall F1 scores on the test dataset for the macro-phases and all 11 phases were 0.96 and 0.90, respectively. The recall values for diagnostics, marking, injection, dissection and bleeding were 1.00, 1.00, 0.95, 0.96 and 0.93, respectively. Conclusions  The algorithm classified operational phases during ESD with high accuracy. A precise evaluation of phase distribution may allow for the development of objective quality metrics for quality control and training. Y1 - 2025 U6 - https://doi.org/10.1055/s-0045-1806324 VL - 57 IS - S 02 SP - S511 PB - Thieme CY - Stuttgart 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 - Gschoßmann, Lukas A1 - Schedel, Valentin A1 - Süß, Franz A1 - Weber, Markus A1 - Pfingsten, Andrea A1 - Dendorfer, Sebastian T1 - Comparing kinematic and kinetic demands on the knee joint during selected physiotherapy exercises and activities of daily living JF - Technology and health care ; Special issue: BIOMDLORE N2 - Background: The knee is one of the most common areas to suffer injuries or be affected by surgery. Physiotherapy rehabilitation was shown to support recovery, but evidence guiding optimal rehabilitation practices is limited. To recommend appropriate exercises, it is essential to understand the musculoskeletal requirements involved in both physiotherapy and activities of daily living (ADLs).ObjectiveThis study aimed to evaluate and compare the knee joint kinematics, joint forces and muscle activity in knee flexors and extensors during selected rehabilitation exercises and ADLs.MethodsKinematic and kinetic data from 30 healthy participants were collected during 20 different tasks. Full-body musculoskeletal simulations were performed to estimate peak knee joint angles, angular velocities, joint reaction forces, and muscle activity of the knee flexors and extensors.ResultsComparatively high requirements were observed for lunges, squats, stair walking and gait. Medium requirements were observed for sitting down and rising from a chair. Low requirements were observed for balance shifts and variations of the single leg stand.ConclusionOverall, ADLs like gait and stair walking show surprisingly high requirements compared to many exercises employed in physiotherapy. These findings are a step towards biomechanically informed exercise selection and the development of personalized rehabilitation programs. Y1 - 2026 U6 - https://doi.org/10.1177/09287329251413413 N1 - Corresponding author der OTH Regensburg: Lukas Gschoßmann PB - Sage ER -