@misc{MelznerIsmailRušavyetal., author = {Melzner, Maximilian and Ismail, Khaled and Rušav{\´y}, Zdeněk and Kališ, Vladim{\´i}r and S{\"u}ß, Franz and Dendorfer, Sebastian}, title = {Musculoskeletal Lower Back Load of Accoucheurs During Delivery}, series = {26th Congress of the European Society of Biomechanics, July 11-14, 2021, Milan, Italy}, journal = {26th Congress of the European Society of Biomechanics, July 11-14, 2021, Milan, Italy}, address = {Milan}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-20208}, abstract = {With the progress in modern medicine, it was possible to significantly reduce the risks of birth for mother and child. One aspect that has received less attention so far is the risk of injury to the accoucheurs (obstetricians and midwives) during the birth process. Indeed, studies indicate that 92\% of midwives suffer from musculoskeletal disorders, with the lower back being the main cause of complaints (72\%). The aim of this study was to investigate two commonly used postural techniques used by accoucheurs during childbirth and to analyze the resulting load on the lower back using the AnyBodyTM musculoskeletal simulation software.}, language = {en} } @misc{SuessMelznerDendorfer, author = {Suess, Franz and Melzner, Maximilian and Dendorfer, Sebastian}, title = {Towards Ergonomic working - machine learning algorithms and musculoskeletal modeling}, series = {RIM 2021, 13th International Scientific Conference on Manufacturing Engineering, 29 Sept. - 1 Oct 2021, Sarajevo, Bosnia and Herzegovina}, journal = {RIM 2021, 13th International Scientific Conference on Manufacturing Engineering, 29 Sept. - 1 Oct 2021, Sarajevo, Bosnia and Herzegovina}, language = {en} } @article{MelznerIsmailRušavyetal., author = {Melzner, Maximilian and Ismail, Khaled and Rušavy, Zdenek and Kališ, Vladim{\´i}r and S{\"u}ß, Franz and Dendorfer, Sebastian}, title = {Musculoskeletal lower back load of accoucheurs during childbirth - A pilot and feasibility study}, series = {European Journal of Obstetrics \& Gynecology and Reproductive Biology}, journal = {European Journal of Obstetrics \& Gynecology and Reproductive Biology}, number = {264}, publisher = {Elsevier}, doi = {10.1016/j.ejogrb.2021.07.042}, pages = {306 -- 313}, abstract = {Introduction: Back problems represent one of the leading causes of accouchers' work-related musculoskeletal morbidities. The correct execution of birth-related maneuvers including manual perineal protection is crucial not only for the mother and child but also for obstetricians and midwives to reduce any strain on their musculoskeletal system. Therefore, the overall aim of this study was to test the feasibility of determining the effect of different accouchers' postures (standing and kneeling) on their musculoskeletal system. Methods: The biomechanical analysis is based on musculoskeletal simulations that included motion recordings of real deliveries as well as deliveries conducted on a birthing simulator. These simulations were then used to determine individual joints' loads. Results: In the kneeling posture, both a low intra-operator variability and a lower average maximum load of the lower back was observed. For the standing position the spine load was reduced by pivoting the elbow on the accouchers' thigh, which in turn was associated with a significantly greater load on the shoulder joint. Conclusion: The study demonstrated the feasibility of our technique to assess joints loads. It also provided initial data indicating that a posture that reduces spinal flexion and tilt, achieved in this study by the kneeling, can significantly reduce the strain on the practitioner's musculoskeletal system.}, language = {en} } @misc{SaffertMelznerDendorfer, author = {Saffert, Anne-Sophia and Melzner, Maximilian and Dendorfer, Sebastian}, title = {Biomechanical Analysis of the Right Elevated Glenohumeral Joint in Violinists during Legato-Playing}, series = {Biomdlore 2021: 21-23 October 2021 Vilnius/Trakai, Lithuania}, journal = {Biomdlore 2021: 21-23 October 2021 Vilnius/Trakai, Lithuania}, doi = {10.3233/THC-219001}, abstract = {BACKGROUND: Many statistics reveal that violin players suffer most often from musculoskeletal disorders compared to musicians of other instrument groups. A common phenomenon, especially observed in violin beginners, is the tendency to elevate the right shoulder during playing the violin. This can probably lead to serious disorders in long-term practice with repetitive movements. OBJECTIVE: For this reason, this study investigated the relationship between the right shoulder elevation and the force in the right glenohumeral joint during violin playing. It was hypothesized that the forces in the right glenohumeral joint are higher during playing with the right shoulder raised compared to playing in normal posture. METHODS: Motion capture data from four experienced violinists was recorded and processed by means of musculoskeletal simulation to get the force and elevation angle while playing with raised shoulder and in normal position. RESULTS: The results indicate that the absolute values of the resulting force, as well as the forces in the mediolateral, inferosuperior, and anteroposterior directions, are higher in playing the violin with the shoulder raised than in a normal posture. CONCLUSIONS: Elevating the right shoulder while playing the violin may pose a potential problem.}, language = {en} } @article{MelznerSuessDendorfer, author = {Melzner, Maximilian and Suess, Franz and Dendorfer, Sebastian}, title = {The impact of anatomical uncertainties on the predictions of a musculoskeletal hand model - a sensitivity study}, series = {Computer Methods in Biomechanics and Biomedical Engineering}, volume = {25}, journal = {Computer Methods in Biomechanics and Biomedical Engineering}, number = {2}, publisher = {Taylor \& Francis}, issn = {1476-8259}, doi = {10.1080/10255842.2021.1940974}, pages = {156 -- 164}, abstract = {Outputs of musculoskeletal models should be considered probabilistic rather than deterministic as they are affected by inaccuracies and estimations associated with the development of the model. One of these uncertainties being critical for modeling arises from the determination of the muscles' line of action and the physiological cross-sectional area. Therefore, the aim of this study was to evaluate the outcome sensitivity of model predictions from a musculoskeletal hand model in comparison to the uncertainty of these input parameters. For this purpose, the kinematics and muscle activities of different hand movements (abduction of the fingers, abduction of the thumb, and flexion of the thumb) were recorded. One thousand simulations were calculated for each movement using the Latin hypercube sampling method with a corresponding variation of the muscle origin/insertion points and the cross-sectional area. Comparing the standard hand to simulations incorporating uncertainties of input parameters shows no major deviations in on- and off-set time point of muscle activities. About 60\% of simulations are located within a ± 30\% interval around the standard model concerning joint reaction forces. The comparison with the variation of the input data leads to the conclusion that the standard hand model is able to provide not over-scattered outcomes and, therefore, can be considered relatively stable. These results are of practical importance to the personalization of a musculoskeletal model with subject-specific bone geometries and hence changed muscle line of action.}, subject = {Biomechanik}, language = {en} } @article{MelznerEngelhardtSimonetal., author = {Melzner, Maximilian and Engelhardt, Lucas and Simon, Ulrich and Dendorfer, Sebastian}, title = {Electromyography-Based Validation of a Musculoskeletal Hand Model}, series = {Journal of Biomechanical Engineering}, volume = {144}, journal = {Journal of Biomechanical Engineering}, number = {2}, publisher = {American Society of Mechanical Engineers, ASME}, doi = {10.1115/1.4052115}, pages = {8}, abstract = {Regarding the prevention of injuries and rehabilitation of the human hand, musculoskeletal simulations using an inverse dynamics approach allow for insights of the muscle recruitment and thus acting forces on the hand. Currently, several hand models from various research groups are in use, which are mainly validated by the comparison of numerical and anatomical moment arms. In contrast to this validation and model-building technique by cadaver studies, the aim of this study is to further validate a recently published hand model [1] by analyzing numerically calculated muscle activities in comparison to experimentally measured electromyographical signals of the muscles. Therefore, the electromyographical signals of 10 hand muscles of five test subjects performing seven different hand movements were measured. The kinematics of these tasks were used as input for the hand model, and the numerical muscle activities were computed. To analyze the relationship between simulated and measured activities, the time difference of the muscle on- and off-set points was calculated, which resulted in a mean on- and off-set time difference of 0.58 s between the experimental data and the model. The largest differences were detected for movements that mainly addressed the wrist. One major issue comparing simulated and measured muscle activities of the hand is cross-talk. Nevertheless, the results show that the hand model fits the experiment quite accurately despite some limitations and is a further step toward patient-specific modeling of the upper extremity.}, subject = {Elektromyographie}, language = {en} } @inproceedings{SuessMelznerDendorfer, author = {Suess, Franz and Melzner, Maximilian and Dendorfer, Sebastian}, title = {Towards ergonomics working - machine learning algorithms and musculoskeletal modeling}, series = {IOP Conference Series: Materials Science and Engineering}, volume = {1208}, booktitle = {IOP Conference Series: Materials Science and Engineering}, publisher = {IOP Publishing}, issn = {1757-899X}, doi = {10.1088/1757-899X/1208/1/012001}, abstract = {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.}, language = {en} }