@article{KomnikFunkenZachowetal.2024, author = {Komnik, Igor and Funken, Johannes and Zachow, Stefan and Schmidt-Wiethoff, R{\"u}diger and Ellermann, Andree and Potthast, Wolfgang}, title = {Surgical planning in HTO - Alternative approaches to the Fujisawa gold-standard}, journal = {Technology and Health Care}, doi = {10.1177/09287329241299568}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-98227}, year = {2024}, abstract = {BACKGROUND: Presurgical planning of the correction angle plays a decisive role in a high tibial osteotomy, affecting the loading situation in the knee affected by osteoarthritis. The planning approach by Fujisawa et al. aims to adjust the weight-bearing line to achieve an optimal knee joint load distribution. While this method is accessible, it may not fully consider the complexity of individual dynamic knee-loading profiles. This review aims to disclose existing alternative HTO planning methods that do not follow Fujisawa's standard. METHODS: PubMed, Web of Science and CENTRAL databases were screened, focusing on HTO research in combination with alternative planning approaches. RESULTS: Eight out of 828 studies were included, with seven simulation studies based on finite element analysis and multi-body dynamics. The planning approaches incorporated gradual degrees of realignment parameters (weight-bearing line shift, medial proximal tibial angle, hip- knee-ankle, knee joint line orientation), simulating their effect on knee kinematics, contact force/stress, Von Mises and shear stress. Two studies proposed implementing individual correction magnitudes derived from preoperatively predicted knee adduction moments. CONCLUSION: Most planning methods depend on static alignment assessments, neglecting an adequate loading-depending profile. They are confined to their conceptual phases, making the associated planning methods unviable for current clinical use.}, language = {en} } @article{SiqueiraRodriguesSchmidtIsraeletal.2024, author = {Siqueira Rodrigues, Lucas and Schmidt, Timo Torsten and Israel, Johann Habakuk and Nyakatura, John and Zachow, Stefan and Kosch, Thomas}, title = {Comparing the Effects of Visual, Haptic, and Visuohaptic Encoding on Memory Retention of Digital Objects in Virtual Reality}, journal = {NordiCHI '24: Proceedings of the 13th Nordic Conference on Human-Computer Interaction}, arxiv = {http://arxiv.org/abs/2406.14139}, doi = {10.1145/3679318.3685349}, pages = {1 -- 13}, year = {2024}, abstract = {Although Virtual Reality (VR) has undoubtedly improved human interaction with 3D data, users still face difficulties retaining important details of complex digital objects in preparation for physical tasks. To address this issue, we evaluated the potential of visuohaptic integration to improve the memorability of virtual objects in immersive visualizations. In a user study (N=20), participants performed a delayed match-to-sample task where they memorized stimuli of visual, haptic, or visuohaptic encoding conditions. We assessed performance differences between the conditions through error rates and response time. We found that visuohaptic encoding significantly improved memorization accuracy compared to unimodal visual and haptic conditions. Our analysis indicates that integrating haptics into immersive visualizations enhances the memorability of digital objects. We discuss its implications for the optimal encoding design in VR applications that assist professionals who need to memorize and recall virtual objects in their daily work.}, language = {en} } @article{SiqueiraRodriguesSchmidtNyakaturaetal.2024, author = {Siqueira Rodrigues, Lucas and Schmidt, Timo Torsten and Nyakatura, John and Zachow, Stefan and Israel, Johann Habakuk and Kosch, Thomas}, title = {Assessing the Effects of Sensory Modality Conditions on Object Retention across Virtual Reality and Projected Surface Display Environments}, volume = {8}, journal = {Proceedings of the ACM on Human-Computer Interaction}, number = {ISS}, doi = {10.1145/3698137}, pages = {255 -- 282}, year = {2024}, abstract = {Haptic feedback reportedly enhances human interaction with 3D data, particularly improving the retention of mental representations of digital objects in immersive settings. However, the effectiveness of visuohaptic integration in promoting object retention across different display environments remains underexplored. Our study extends previous research on the retention effects of haptics from virtual reality to a projected surface display to assess whether earlier findings generalize to 2D environments. Participants performed a delayed match-to-sample task incorporating visual, haptic, and visuohaptic sensory feedback within a projected surface display environment. We compared error rates and response times across these sensory modalities and display environments. Our results reveal that visuohaptic integration significantly enhances object retention on projected surfaces, benefiting task performance across display environments. Our findings suggest that haptics can improve object retention without requiring fully immersive setups, offering insights for the design of interactive systems that assist professionals who rely on precise mental representations of digital objects.}, language = {en} } @inproceedings{SiqueiraRodriguesNyakaturaZachowetal.2024, author = {Siqueira Rodrigues, Lucas and Nyakatura, John and Zachow, Stefan and Israel, Johann Habakuk and Kosch, Thomas}, title = {Evaluating Visuohaptic Integration on Memory Retention of Morphological Tomographic Images}, booktitle = {The 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry}, publisher = {ACM}, address = {New York, NY, USA}, doi = {10.1145/3703619.3706055}, pages = {1 -- 10}, year = {2024}, abstract = {Scientific visualization and tomographic imaging techniques have created unprecedented possibilities for non-destructive analyses of digital specimens in morphology. However, practitioners encounter difficulties retaining critical information from complex tomographic volumes in their workflows. In light of this challenge, we investigated the effectiveness of visuohaptic integration in enhancing memory retention of morphological data. In a within-subjects user study (N=18), participants completed a delayed match-to-sample task, where we compared error rates and response times across visual and visuohaptic sensory modality conditions. Our results indicate that visuohaptic encoding improves the retention of tomographic images, producing significantly reduced error rates and faster response times than its unimodal visual counterpart. Our findings suggest that integrating haptics into scientific visualization interfaces may support professionals in fields such as morphology, where accurate retention of complex spatial data is essential for efficient analysis and decision-making within virtual environments.}, language = {en} } @article{TrepczynskiKneifelHeylandetal.2024, author = {Trepczynski, Adam and Kneifel, Paul and Heyland, Mark and Leskovar, Marko and Moewis, Philippe and Damm, Philipp and Taylor, William R. and Zachow, Stefan and Duda, Georg}, title = {Impact of the External Knee Flexion Moment on Patello-Femoral Loading Derived from in vivo Loads and Kinematics}, volume = {12}, journal = {Frontiers in Bioengineering and Biotechnology}, doi = {10.3389/fbioe.2024.1473951}, year = {2024}, abstract = {Anterior knee pain and other patello-femoral (PF) complications frequently limit the success of total knee arthroplasty as the final treatment of end stage osteoarthritis. However, knowledge about the invivo loading conditions at the PF joint remains limited, as no direct measurements are available. We hypothesised that the external knee flexion moment (EFM) is highly predictive of the PF contact forces during activities with substantial flexion of the loaded knee.Six patients (65-80 years, 67-101 kg) with total knee arthroplasty (TKA) performed two activities of daily living: sit-stand-sit and squat. Tibio-femoral (TF) contact forces were measured in vivo using instrumented tibial components, while synchronously internal TF and PF kinematics were captured with mobile fluoroscopy. The measurements were used to compute PF contact forces using patient specific musculoskeletal models. The relationship between the EFM and the PF contact force was quantified using linear regression.Mean peak TF contact forces of 1.97 to 3.24 times body weight (BW) were found while peak PF forces reached 1.75 to 3.29 times body weight (BW). The peak EFM ranged from 3.2 to 5.9 \%BW times body height, and was a good predictor of the PF contact force (R^2 = 0.95 and 0.88 for sit-standsit and squat, respectively).The novel combination of in vivo TF contact forces and internal patellar kinematics enabled a reliable assessment of PF contact forces. The results of the regression analysis suggest that PF forces can be estimated based solely on the EFM from quantitative gait analysis. Our study also demonstrates the relevance of PF contact forces, which reach magnitudes similar to TF forces during activities of daily living.}, language = {en} } @article{AmiranashviliLuedkeLietal.2024, author = {Amiranashvili, Tamaz and L{\"u}dke, David and Li, Hongwei Bran and Zachow, Stefan and Menze, Bjoern}, title = {Learning continuous shape priors from sparse data with neural implicit functions}, volume = {94}, journal = {Medical Image Analysis}, doi = {10.1016/j.media.2024.103099}, pages = {103099}, year = {2024}, abstract = {Statistical shape models are an essential tool for various tasks in medical image analysis, including shape generation, reconstruction and classification. Shape models are learned from a population of example shapes, which are typically obtained through segmentation of volumetric medical images. In clinical practice, highly anisotropic volumetric scans with large slice distances are prevalent, e.g., to reduce radiation exposure in CT or image acquisition time in MR imaging. For existing shape modeling approaches, the resolution of the emerging model is limited to the resolution of the training shapes. Therefore, any missing information between slices prohibits existing methods from learning a high-resolution shape prior. We propose a novel shape modeling approach that can be trained on sparse, binary segmentation masks with large slice distances. This is achieved through employing continuous shape representations based on neural implicit functions. After training, our model can reconstruct shapes from various sparse inputs at high target resolutions beyond the resolution of individual training examples. We successfully reconstruct high-resolution shapes from as few as three orthogonal slices. Furthermore, our shape model allows us to embed various sparse segmentation masks into a common, low-dimensional latent space — independent of the acquisition direction, resolution, spacing, and field of view. We show that the emerging latent representation discriminates between healthy and pathological shapes, even when provided with sparse segmentation masks. Lastly, we qualitatively demonstrate that the emerging latent space is smooth and captures characteristic modes of shape variation. We evaluate our shape model on two anatomical structures: the lumbar vertebra and the distal femur, both from publicly available datasets.}, language = {en} }