@inproceedings{JungtaeublAurbachMelzneretal., author = {Jungt{\"a}ubl, Dominik and Aurbach, Maximilian and Melzner, Maximilian and Spicka, Jan and S{\"u}ß, Franz and Dendorfer, Sebastian}, title = {EMG-Based Validation of Musculoskeletal Models Considering Crosstalk}, series = {International Conference BIOMDLORE, June 28 - 30 2018, Białystok, Poland}, booktitle = {International Conference BIOMDLORE, June 28 - 30 2018, Białystok, Poland}, doi = {10.1109/BIOMDLORE.2018.8467211}, abstract = {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.}, language = {en} } @inproceedings{SeefriedAurbachWyssetal., author = {Seefried, C. and Aurbach, Maximilian and Wyss, C. and Dendorfer, Sebastian}, title = {Achilles tendon lengthening alters stresses in the growth plate}, series = {International Conference BIOMDLORE, June 28 - 30 2018, Białystok, Poland}, booktitle = {International Conference BIOMDLORE, June 28 - 30 2018, Białystok, Poland}, language = {en} } @inproceedings{AurbachWagnerSuessetal., author = {Aurbach, Maximilian and Wagner, Kilian and S{\"u}ß, Franz and Dendorfer, Sebastian}, title = {Implementation and Validation of Human Kinematics Measured Using IMUs for Musculoskeletal Simulations by the Evaluation of Joint Reaction Forces}, series = {CMBEBIH 2017, Proceedings of the International Conference on Medical and Biological Engineering 2017, Sarajevo, Bosnia and Herzegovina}, volume = {Vol. 62}, booktitle = {CMBEBIH 2017, Proceedings of the International Conference on Medical and Biological Engineering 2017, Sarajevo, Bosnia and Herzegovina}, editor = {Badnjevic, Almir}, publisher = {Springer}, address = {Singapore}, doi = {10.1007/978-981-10-4166-2_31}, pages = {205 -- 211}, abstract = {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.}, subject = {Bewegungsapparat}, language = {en} } @inproceedings{AurbachJungtaeublSpickaetal., author = {Aurbach, Maximilian and Jungt{\"a}ubl, Dominik and Spicka, Jan and Dendorfer, Sebastian}, title = {EMG-based validation of musculoskeletal models considering crosstalk}, series = {World Congress Biomechanics, 28-30 June 2018, Dublin}, booktitle = {World Congress Biomechanics, 28-30 June 2018, Dublin}, doi = {10.1109/BIOMDLORE.2018.8467211}, abstract = {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.}, language = {en} }