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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.
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.
Fragestellung
Es soll in dieser Computersimulationsstudie untersucht werden, wie der Osteosyntheseverbund Platte mit Schrauben im Verbund mit einer im mittleren Drittel gebrochenen Clavicula durch das Bewegungsausmaß
in vivo belastet ist. Was sind die grundlegenden Kräfte die auf Clavicula und Implantat wirken und welchen Einfl uss hat die Bruchform.
Methodik
Die Muskel- und Gelenkkräfte sowie die Belastung des Implantatverbundes wurden mit einer muskuloskelletalen
Simulationssoftware (AnyBody Technology, V.4) berechnet. Hierfür wurden mit einem komplexen Model des menschlichen Körpers folgende Bewegungen analysiert: eine Flexion von 160° und Abduktion 160° mit
einem Gewicht von 2 kg in der Hand. Aus CT-Patientendaten wurden zwei dreidimensionale Modelle des Clavicula-Implantat Verbundes gebildet, die sich in der Frakturform unterscheiden (Querfraktur und vertikale
Fraktur). In beiden Modellen wurde eine Claviculaosteosynthese in superiorer Position mit einer 6 Loch LCP mit 2 Schrauben pro Hauptfragment verwendet. Die Materialeigenschaften wurden aus der Dichte des Materials sowie aus Literaturdaten verwendet. Die Muskel- und Gelenkkräfte aus der muskuloskelletalen Berechnung wurden auf das Finite Elemente Modell übertragen und die Spannungen und Dehnungen des Implantat-Knochenverbundes
wurden berechnet.
Ergebnisse
Es zeigte sich, dass die simulierte in vivo Belastung stark abhängig vom Flexionswinkel ist. Das Implantat ist in der superioren Lage auf Biegung belastet, welche maximale Werte im Überschulterniveau erreicht. Die Bruchform mit anatomischer Reposition und Kontakt der Hauptfragmente zueinander führt zu einer deutlichen Entlastung des Osteosyntheseverbundes im Vergleich zu einer Bruchform mit vertikaler Fraktur.
Schlussfolgerung
Aus den Analysen ist eine Positionierung der Plattenosteosynthese für die im mittleren Drittel frakturierte Clavicula in anterior-superiorer Lage wünschenswert. Die anatomische Reposition entlastet den Osteosyntheseverbund und sollte möglichst erreicht werden. Die Nachbehandlung sollte ein Bewegungsausmaß für den Arm für 4 Wochen für einfache Bruchformen auf 70° Flexion und Abduktion limitieren und für komplexe Bruchformen diese Limitierung ausgedehnt werden.
Subject-specific Musculoskeletal Simulation of Hip Dislocation Risk in Activities of Daily Living
(2011)
On modelling spine curvature dependent on muscular and external forces in multibody dynamics system
(2011)
This paper presents a computational approach for investigating effect of muscular and external forces on curvature of the lumbar spine. Multibody dynamics system is used to compute the lumbar spine curvature using a force-dependent kinematics facility, e.g. this method allows releasing some degrees of freedom in order to be computed based on the current load configuration.
INTRODUCTION
Several clinical studies demonstrated long-term adjacent-level effects after implantation of spinal fusion devices[1]. These effects have been reported as adjacent joint degeneration and the development of new symptoms correlating with adjacent segment degeneration[2] and the trend has therefore gone to motion preservation devices; however, these effects have not been understood very well and have not been investigated thoroughly[3].
The aim of this study is to investigate the effect of varying the stiffness of spinal fusion devices on the adjacent vertebral levels. Disc forces, moments and facet joint forces were analyzed.
METHODS
The AnyBody Modeling System was used to compute the in-vivo muscle and joint reaction forces of a musculoskeletal model. The full body model used in this study consists of 188 muscle fascicles in the lumbar spine and more than 1000 individual muscle branches in total. The model has been proposed by de Zee et al.[3], validated by Rasmussen et al.[4] and by Galibarov et al.[5]. The new model[5] determines the individual motions between vertebrae based on the equilibrium between forces acting on the vertebrae from muscles and joints and the passive stiffness in disks and ligaments, figure 1a. An adult of 1.75 m and 75 kg with a spinal implant in L4L5 was modeled. This model was subjected to a flexion-extension motion using different elastic moduli to analyze and compare to a non-implanted scenario. The analyzed variables were vertebral motion, the disc reaction forces and moments, as well as facet joint forces in the treated and the adjacent levels: L2L3, L3L4, L4L5 and L5-Sacrum.
RESULTS
When introducing a spinal fusion device in the L4L5 joint the reaction forces and moments decreased in this joint with stiffer devices leading to lower joint loads. However, in the adjacent joints, L3L4 and L5Sacrum, an increase was observed when implanting stiffer devices. Similar trends could be found for the L2L3 joint. The loads in the facet joints showed the same trends. While introducing a spinal fusion device reduced the facet joint forces in the treated joint, the loads in the adjacent facet joints were increased according to the stiffness of the implanted device, figure 1b.
DISCUSSION
While the treated disc joint showed reduced motion and loads, the adjacent levels demonstrated a significant increase. In particular, the increased facet joint forces in the adjacent levels can lead to adjacent level facet pain or accelerated facet joint degeneration. Introducing a device resulted in preventing facet contact and therefore facet joint loads, even using the device with the lowest stiffness.
CONCLUSION
The presented model shows that clinical complications such as facet joint degeneration in adjacent levels after implantation of spinal fusion device are consistent with the change in the mechanical-stimulus distribution in the system.
Einführung in die Mechanik
(2013)
High loads can appear in the individual joints of the human foot while the driver uses the pedals, in particular, during breaking. Measuring these internal forces is very difficult or almost impossible; therefore, advanced models are necessary to perform musculoskeletal simulations. The objective of this investigation was to see what loads are acting in the individual foot joints from the phalanges to calcaneus and talus during different brake scenarios. The Glasgow-Maastricht AnyBody Foot Model with 26 separate segments, connected by joints, ligaments and muscles was used inside the AnyBody Modeling System to compute individual mid foot joint loads. The amount, the direction of the force and additionally also the load insertion point was varied for several simulations. Figure 1: Seated musculoskeletal body model with applied brake force and forces for the lateral, intermediate and medial cuneiform-navicular joint for two different brake forces. The simulation showed that for the different brake scenarios, different muscles will be activated in the human and therefore different loads are apply in the fore-and mid-foot, respectively. The torso of the subject was assumed to be fixed in the seat. Further studies are ongoing to simulate the seat as an elastic element that allows different H-point locations according to the different loadings in the foot from the brake pedal using a new inverse dynamics analysis method called force-dependent kinematics.
Navigated Femur First Total Hip Arthroplasty leads to improved Biomechanical Outcome after surgery
(2015)
Thoracolumbar spine model with articulated rigcage for the prediction of dynamic spinal loading
(2015)
The musculoskeletal load scenario of computer-assisted Femur-First THR up to one year after surgery
(2015)
Biomechanik des Alterns
(2016)