TY - CHAP A1 - Melzner, Maximilian A1 - Engelhardt, Lucas A1 - Havelkova, Leonard A1 - Simon, Ulrich A1 - Dendorfer, Sebastian T1 - A new musculoskeletal AnyBody detailed hand model validated by electromyography T2 - 16th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE) 2019, New York City, USA N2 - The AnyBody™ Modeling System (AMS) [1], is an universally used musculoskeletal simulation software using inverse dynamics. Until now, no complete human hand model is known in the AMS. Also considering other musculoskeletal software platforms, just one detailed entire hand model is recently published [2] but is only based on one subject. The aim of this work is to implement a full detailed hand model for the AMS including all extrinsic and intrinsic muscles using data by the UWB gained through an anatomical study of ten cadaver hands. Y1 - 2019 UR - https://www.researchgate.net/publication/336944957_A_NEW_MUSCULOSKELETAL_ANYBODY_DETAILED_HAND_MODEL_VALIDATED_BY_ELECTROMYOGRAPHY ER - TY - GEN A1 - Auer, Simon A1 - Krutsch, Werner A1 - Renkawitz, Tobias A1 - Kubowitsch, Simone A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Effect of mental demand on leg loading in highly dynamic motion T2 - AnyBody online Webinar, Oct 2020 N2 - Football players have a high risk of leg muscle injuries, especially when exposed to mental stress. Injuries to muscles of the thigh are common in amateur and professional football, representing almost a third of all injuries. These injuries occur primarily in non-contact situations and from overuse. They can lead to a range of costs, including financial costs associated with treatment as well as those associated with long-term recovery, and absence from training and/or competition. Further, there is a high risk of injury recurrence and subsequent injury. Y1 - 2020 ER - TY - CHAP A1 - Süß, Franz A1 - Kubowitsch, Simone A1 - Rasmussen, John A1 - Verkerke, Gijsbertus Jacob A1 - Dendorfer, Sebastian T1 - The influence of cognitive stress on muscle activation and spinal disc load T2 - European Society of Biomechanics meeting 2019, Vienna, Austria Y1 - 2019 UR - https://owncloud.tuwien.ac.at/index.php/s/dovqqcj02VeZHze ER - TY - GEN A1 - Aurbach, Maximilian A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - The impact of the hill type muscle model on the glenohumeral joint reaction force T2 - 16th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE) 2019, New York City, USA Y1 - 2019 ER - TY - CHAP A1 - Aurbach, Maximilian A1 - Wagner, Kilian A1 - Süß, Franz A1 - Dendorfer, Sebastian ED - Badnjevic, Almir T1 - Implementation and Validation of Human Kinematics Measured Using IMUs for Musculoskeletal Simulations by the Evaluation of Joint Reaction Forces T2 - CMBEBIH 2017, Proceedings of the International Conference on Medical and Biological Engineering 2017, Sarajevo, Bosnia and Herzegovina N2 - The gold standard for the analysis of human kinematics and kinetics is a camera-based motion capture system in combination with force measurement platforms. Alternatively, inertial measurement units can be utilized to obtain human kinematics, while ground reaction forces are computed from full body dynamics. This setup represents a system independent from the spatial confinement of a gait laboratory. The aim of this study is the comparison of the two methods by the investigation of lower limb kinematics and the resulting joint reaction forces within the ankle-, knee- and hip joints. For this purpose, human motion during gait was captured simultaneously by both measurement techniques. 13 trials from 8 different test subjects were evaluated in total. IMU data was processed with a quaternion based Kalman Filter. The data sets were implemented into a musculoskeletal simulation program in order to drive a virtual human body model. Each sensor was aligned to the gravitational and magnetic field vectors of the earth. The angles of flexions, extensions and rotations were analyzed to determine kinematic differences. Joint reaction forces defined kinetic dissimilarities. The overall kinematic differences of both models yielded root mean square errors of 7.62°, 6.02°, 4.95°, 2.79°, 2.38° and 3.56° for ankle flexion, subtalar eversion, knee flexion, hip external rotation, hip abduction and hip flexion, respectively. The proximo-distal differences in force peaks between the models yielded overall for the ankle, 57.33 %Bodyweight(BW) ± 46.86 %BW (16.66 %(Maximum peak to peak) ± 13.62 %) for the knee 37.09 %BW ± 29.33 %BW (17.65 % ± 15.44 %) and 32.03 %BW ± 24.33 %BW (15.6 % ± 12.54 %) for the hip. The overall outcome of this work investigated an approach independent of the common setup of the gait laboratory, thus enabling a cheaper and more flexible technology as an alternative. However, kinematic and thus kinetic differences remain rather large. Future work aims to improve the contact criterion for the calculation of the ground reaction forces and the implementation of a full-body calibration algorithm for the IMU system in order to counteract magnetic field disturbances. KW - Inertial Measurement Units KW - Multibody Simulation KW - Musculoskeletal Simulation KW - AnyBody KW - Motion Capture KW - Bewegungsapparat KW - Biomechanik KW - Motion Capturing KW - Mehrkörpersimulation KW - Ground Reaction Force Prediction KW - Gait KW - IMU KW - Joint Reaction Forces Y1 - 2017 U6 - https://doi.org/10.1007/978-981-10-4166-2_31 VL - Vol. 62 SP - 205 EP - 211 PB - Springer CY - Singapore ER - TY - CHAP A1 - Hammer, Joachim A1 - Dendorfer, Sebastian T1 - Cyclic loading and microstructure of cancellous bone T2 - Journal of Biomechanics Y1 - 2008 U6 - https://doi.org/10.1016/S0021-9290(08)70409-3 VL - 41 IS - Suppl. 1, July 2008 SP - S410 ER - TY - CHAP A1 - Dendorfer, Sebastian T1 - Biomechanical evaluation and optimisation of countermeasure exercises T2 - ESA/ESTEC Bedrest Strategy Workshop, Noordwijk, NL, 2009 Y1 - 2009 ER - TY - GEN A1 - Adler, Ina A1 - Förstl, Nikolas A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Biomechanical exposition of the factors influencing the pelvic floor muscle activity T2 - ESB 2024, 29th Congress of the European Society of Biomechanics, 30 June-3 July 2024, Edinburgh, Scotland N2 - Introduction About 40 % of the women worldwide suffer from Pelvic Floor Dysfunctions [1]. In previous studies, musculoskeletal simulations helped to understand and facilitate the complex issues of musculoskeletal disorders in several different branches [2, 3]. A fundamental prerequisite for the generation of these models is to have a basic understanding of the stresses acting on the pelvic floor. The aim of this study is to investigate the biomechanical factors influencing the activity of the pelvic floor muscles by establishing a parameterised model. Methods To identify the factors that affect the pelvic floor muscles, the process is divided into several stages. The first step is to investigate the loads acting on the pelvic floor. For this, a simplified sagittal cross-sectional model of the upper body is analysed. The discretization of the abdominal cavity is presented with resulting force vectors representing the organs in the abdominal and pelvic region, the tensile force of the structures that fixate the organs as well as the intraabdominal pressure. A second step is the examination of the basic mechanics of the pelvic floor muscles. As the functional anatomy of these muscles demonstrate differences compared to other muscle groups [4], the understanding of how they differ is crucial for the construction of musculoskeletal models. After a static examination of loads on a simplified muscle model, an extended model including the physiological properties of a muscle must be involved in the considerations. Therefore, the influence of parameters such as the ideal muscle strength and fibre length, as well as elasticity or passive stiffness of the elements must be taken into account. The influencing factors of the variables can be analysed in a simplified pelvic floor muscle model by systematically changing the parameters. Results The process of analysing the factors influencing the activity of the pelvic floor muscles follows two main strategies. The review of the effects of the whole body identifies the forces acting on the pelvic floor muscles and effect their activity. With the examination of the basic mechanics of a simplified pelvic floor muscle model a better understanding is achieved of how the pelvic floor muscles absorb the loads acting in the body. Discussion This process results in the main influence factors on the activity of the pelvic floor. The consequent parameters form the basis for a biomechanically justified construction of musculoskeletal simulation models of the pelvic floor. Nevertheless, it must be considered, that these mechanical studies represent simplifications of the reality. References 1. Wang et al, Front Public Health, 10:975829, 2022. 2. Bulat et al., Curr Sports Med Rep, 18(6):210-216, 2019 3. Melzner et al., Eur J Obstet Gynecol Reprod Biol, 264:306-313, 2021 4. Ashton-Miller et al., Ann N Y Acad Sci, 1101:266-96, 2007 Y1 - 2024 ER - TY - VIDEO A1 - Auer, Simon A1 - Reinker, Lukas A1 - Süß, Franz A1 - Kubowitsch, Simone A1 - Krutsch, Werner A1 - Weber, Markus A1 - Renkawitz, Tobias A1 - Dendorfer, Sebastian T1 - Webcast: Effect of mental demand on leg loading in highly dynamic motion N2 - Football players have a high risk of leg muscle injuries, especially when exposed to mental stress. Injuries to muscles of the thigh are common in amateur and professional football, representing almost a third of all injuries. These injuries occur primarily in non-contact situations and from overuse. They can lead to a range of costs, including financial costs associated with treatment as well as those associated with long-term recovery, and absence from training and/or competition. Further, there is a high risk of injury recurrence and subsequent injury. KW - Webcast KW - AnyBody KW - Stress KW - Football KW - Speedcourt Y1 - 2020 UR - https://www.youtube.com/watch?v=uSc_9XlnkaA ER - TY - JOUR A1 - Visscher, Rosa A1 - Wyss, C. A1 - Singh, Navrag B. A1 - Taylor, William R. A1 - Dendorfer, Sebastian A1 - Rutz, E. A1 - Brunner, Reinald T1 - Influence of TAL-TATS surgery on energy production of Tricepts Surae - A musculoskeletal modeling evaluation JF - Gait & Posture Y1 - 2020 U6 - https://doi.org/10.1016/j.gaitpost.2020.08.090 VL - 81 IS - Suppl. 1 SP - 381 EP - 382 PB - Elsevier ER - TY - GEN A1 - Gschoßmann, Lukas A1 - Stein, Leonhard A1 - Dendorfer, Sebastian T1 - Subject Specific Scaling Of Muscle Strengths In The Lower Extremity For Musculoskeletal Models T2 - ESB 2024, 29th Congress of the European Society of Biomechanics, 30 June-3 July 2024, Edinburgh, Scotland Y1 - 2024 ER - TY - CHAP A1 - Suess, Franz A1 - Melzner, Maximilian A1 - Dendorfer, Sebastian T1 - Towards ergonomics working - machine learning algorithms and musculoskeletal modeling T2 - IOP Conference Series: Materials Science and Engineering N2 - Ergonomic workplaces lead to fewer work-related musculoskeletal disorders and thus fewer sick days. There are various guidelines to help avoid harmful situations. However, these recommendations are often rather crude and often neglect the complex interaction of biomechanical loading and psychological stress. This study investigates whether machine learning algorithms can be used to predict mechanical and stress-related muscle activity for a standardized motion. For this purpose, experimental data were collected for trunk movement with and without additional psychological stress. Two different algorithms (XGBoost and TensorFlow) were used to model the experimental data. XGBoost in particular predicted the results very well. By combining it with musculoskeletal models, the method shown here can be used for workplace analysis but also for the development of real-time feedback systems in real workplace environments. Y1 - 2021 U6 - https://doi.org/10.1088/1757-899X/1208/1/012001 SN - 1757-899X N1 - Corresponding author: Sebastian Dendorfer VL - 1208 PB - IOP Publishing ER - TY - CHAP A1 - Aurbach, Maximilian A1 - Jungtäubl, Dominik A1 - Spicka, Jan A1 - Dendorfer, Sebastian T1 - EMG-based validation of musculoskeletal models considering crosstalk T2 - World Congress Biomechanics, 28-30 June 2018, Dublin N2 - BACKGROUND: Validation and verification of multibody musculoskeletal models sEMG is a difficult process because of the reliability of sEMG data and the complex relationship of muscle force and sEMG. OBJECTIVE: This work aims at comparing experimentally recorded and simulated muscle activities considering a numerical model for crosstalk. METHODS: For providing an experimentally derived reference data set, subjects were performing elevations of the arm, where the activities of the contemplated muscle groups were measured by sEMG sensors. Computed muscle activities were further processed and transformed into an artificial electromyographical signal, which includes a numerical crosstalk model. In order to determine whether the crosstalk model provides a better agreement with the measured muscle activities, the Pearson correlation coefficient has been computed as a qualitative way of assessing the curve progression of the data sets. RESULTS: The results show an improvement in the correlation coefficient between the experimental data and the simulated muscle activities when taking crosstalk into account. CONCLUSIONS: Although the correlation coefficient increased when the crosstalk model was utilized, it is questionable if the discretization of both, the crosstalk and the musculoskeletal model, is accurate enough. Y1 - 2018 U6 - https://doi.org/10.1109/BIOMDLORE.2018.8467211 ER - TY - GEN A1 - Suess, Franz A1 - Melzner, Maximilian A1 - Dendorfer, Sebastian T1 - Towards Ergonomic working - machine learning algorithms and musculoskeletal modeling T2 - RIM 2021, 13th International Scientific Conference on Manufacturing Engineering, 29 Sept. - 1 Oct 2021, Sarajevo, Bosnia and Herzegovina Y1 - 2021 ER - TY - CHAP A1 - Dendorfer, Sebastian A1 - Englert, Carsten T1 - Forces on a clavicles midshaft fracture and influence of fracture type T2 - AO Symposium, Regensburg, 2009 Y1 - 2009 ER - TY - JOUR A1 - Förstl, Nikolas A1 - Süß, Franz A1 - Englert, Carsten A1 - Dendorfer, Sebastian T1 - Design of a reverse shoulder implant to measure shoulder stiffness during implant component positioning JF - Medical Engineering & Physics N2 - To avoid dislocation of the shoulder joint after reverse total shoulder arthroplasty, it is important to achieve sufficient shoulder stability when placing the implant components during surgery. One parameter for assessing shoulder stability can be shoulder stiffness. The aim of this research was to develop a temporary reverse shoulder implant prototype that would allow intraoperative measurement of shoulder stiffness while varying the position of the implant components. Joint angle and torque measurement techniques were developed to determine shoulder stiffness. Hall sensors were used to measure the joint angles by converting the magnetic flux densities into angles. The accuracy of the joint angle measurements was tested using a test bench. Torques were determined by using thin-film pressure sensors. Various mechanical mechanisms for variable positioning of the implant components were integrated into the prototype. The results of the joint angle measurements showed measurement errors of less than 5° in a deflection range of ±15° adduction/abduction combined with ±45° flexion/extension. The proposed design provides a first approach for intra-operative assessment of shoulder stiffness. The findings can be used as a technological basis for further developments. Y1 - 2023 U6 - https://doi.org/10.1016/j.medengphy.2023.104059 N1 - Corresponding author: Sebstian Dendorfer VL - 121 PB - Elsevier ET - Journal Pre-proof ER - TY - CHAP A1 - Muehling, M. A1 - Englert, Carsten A1 - Dendorfer, Sebastian T1 - Influence of biceps tenotomy and tenodesis on post-operative shoulder strength T2 - Jahrestagung der Deutschen Gesellschaft für Biomechanik, March 2017, Hannover, Germany Y1 - 2017 ER - TY - JOUR A1 - Pfeifer, Christian A1 - Müller, Michael A1 - Prantl, Lukas A1 - Berner, Arne A1 - Dendorfer, Sebastian A1 - Englert, Carsten T1 - Cartilage labelling for mechanical testing in T-peel configuration JF - International Orthopaedics N2 - PURPOSE: The purpose of this study was to find a suitable method of labelling cartilage samples for the measurement of distraction distances in biomechanical testing. METHODS: Samples of bovine cartilage were labelled using five different methods: hydroquinone and silver nitrate (AgNO3), potassium permanganate (KMnO4) with sodium thiosulphate (Na2S2O3), India ink, heat, and laser energy. After the labelling, we analysed the cartilage samples with regard to cytotoxity by histochemical staining with ethidiumbromide homodimer (EthD-1) and calcein AM. Furthermore, we tested cartilages labelled with India ink and heat in a T-peel test configuration to analyse possible changes in the mechanical behaviour between marked and unlabelled samples. RESULTS: Only the labelling methods with Indian ink or a heated needle showed acceptable results in the cytotoxity test with regard to labelling persistence, accuracy, and the influence on consistency and viability of the chondrocytes. In the biomechanical T-peel configuration, heat-labelled samples collapsed significantly earlier than unlabelled samples. CONCLUSION: Labelling bovine cartilage samples with Indian ink in biomechanical testing is a reliable, accurate, inexpensive, and easy-to-perform method. This labelling method influenced neither the biomechanical behaviour nor the viability of the tissue compared to untreated bovine cartilage. KW - Bovine cartilage KW - Cartilage samples KW - Indian ink KW - T-peel configuration KW - Method labeling KW - Knorpel KW - Rind KW - Kennzeichnung KW - Tinte KW - Biomechanik KW - Prüfung Y1 - 2012 U6 - https://doi.org/10.1007/s00264-011-1468-3 VL - 36 IS - 7 SP - 1493 EP - 1499 PB - Springer ER - TY - JOUR A1 - Förstl, Nikolas A1 - Adler, Ina A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Technologies for Evaluation of Pelvic Floor Functionality: A Systematic Review JF - Sensors N2 - Pelvic floor dysfunction is a common problem in women and has a negative impact on their quality of life. The aim of this review was to provide a general overview of the current state of technology used to assess pelvic floor functionality. It also provides literature research of the physiological and anatomical factors that correlate with pelvic floor health. This systematic review was conducted according to the PRISMA guidelines. The PubMed, ScienceDirect, Cochrane Library, and IEEE databases were searched for publications on sensor technology for the assessment of pelvic floor functionality. Anatomical and physiological parameters were identified through a manual search. In the systematic review, 114 publications were included. Twelve different sensor technologies were identified. Information on the obtained parameters, sensor position, test activities, and subject characteristics was prepared in tabular form from each publication. A total of 16 anatomical and physiological parameters influencing pelvic floor health were identified in 17 published studies and ranked for their statistical significance. Taken together, this review could serve as a basis for the development of novel sensors which could allow for quantifiable prevention and diagnosis, as well as particularized documentation of rehabilitation processes related to pelvic floor dysfunctions. Y1 - 2024 U6 - https://doi.org/10.3390/s24124001 N1 - Die Preprint-Version ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/7306 VL - 24 IS - 12 PB - MDPI ER - TY - GEN A1 - Förstl, Nikolas A1 - Adler, Ina A1 - Suess, Franz A1 - Čechová, Hana A1 - Jansová, Magdalena A1 - Cimrman, Robert A1 - Vychytil, Jan A1 - Dendorfer, Sebastian T1 - Workflow for the development of a non-invasive feedback device to assess pelvic floor contractions T2 - ESB 2024, 29th Congress of the European Society of Biomechanics, 30 June-3 July 2024, Edinburgh, Scotland N2 - Introduction Pelvic floor disorders affect about 40% of women worldwide [1]. Pelvic floor muscle (PFM) training is both a preventive and a therapeutic intervention. Current PFM training devices are invasive and have little scientific evidence. The idea is to develop a noninvasive feedback device to assess adequate PFM contraction. Therefore, evidence-based female musculoskeletal models, non-invasive data acquisition, sensor technology and artificial intelligence (AI) will be combined. This work presents the workflow to achieve such a feedback device and describes the interaction of the technologies used. Methods Exercises that induce PFM contractions have been evaluated and defined. Motion capture of these exercises will provide input for female musculoskeletal models. A combination of biomechanical rigid body and FEM simulations will be used to estimate PFM contractions. In addition, a non-invasive sensor will measure pelvic floor activity. The simulated and measured data will be used to develop an AI model that provides feedback on PFM contractions based on non-invasive data collection. Results The AMMR (AnyBody Managed Model Repository) of the AnyBody modelling system (AMS, Aalborg, Denmark) serves as the initial model for performing inverse dynamic simulations of the exercises. To calculate the PFM forces, the full-body model must be supplemented with the relevant pelvic floor structures and a mass model of the internal organs. A modified abdominal pressure model must also be incorporated. The AMS calculates the PFM activities caused by the internal organ loads and the generated abdominal pressure during the exercises. The muscle activities are transferred to a FEM model of the female pelvic floor (SfePy, simple finite elements in Python). The identical pelvic floor structures were integrated into the FEM model as in the AMS. Active PFM contractions can be simulated using the FEM model. Movement of the coccyx due to PFM contractions has been reported in the literature [2,3]. Therefore, a noninvasive coccyx motion sensor will be developed to provide additional information on PFM contractions. The measured data (coccyx motion sensor, motion capture) and the simulation results of the models will be combined to create an AI feedback model using Python. The final feedback device will consist of the AI model and the developed coccyx motion sensor, which can reproduce the resulting PFM contractions based on the sensor data and simplified motion tracking. Discussion The creation of the AMS and the FEM model is a prerequisite for the development of the feedback device. The relevant structures in the models are located inside the body. This limits the ability to observe the structures during the exercises, which can lead to difficulties in model validation. The development of a user-friendly sensor with sufficient measuring accuracy of the coccyx motion is another challenge. Nevertheless, the workflow represents a promising approach to develop a noninvasive feedback system to assess PFM contraction. References 1. Wang et al, Front Public Health, 10:975829, 2022. 2. Bø et al, Neurourol Urodyn, 20:167–174, 2001. 3. Fujisaki et al, J Phys Ther Sci, 30:544–548, 2018. Acknowledgements This work was supported by the project no. BYCZ01-014 of the Program INTERREG Bavaria – Czechia 2021–2027. Y1 - 2024 ER -