Modelling interaction forces at a curved physical human-exoskeleton interface

In virtual modelling of exoskeletons, the human-exoskeleton interface is often simplified by modelling the interface forces at a single point instead of contact forces due to the straps or cuffs. In the past, force-generating elements (FGEs) have been used to predict ground reaction forces. However, unlike the ground, which is a planar surface, the human-exoskeleton interface presents curved surfaces. This work discusses the modifications required for using the FGEs for predicting the curved human-exoskeleton interface forces of a passive lower-limb exoskeleton, the Chairless Chair. A pressure mat was positioned at the human-exoskeleton interface to measure the area of contact and the centre of pressure (CoP) in three different sitting conditions. The strength of the FGEs was analysed in detail and its optimization based on the model outputs is discussed. The strength affects the model assistance and the CoP, and these outputs could be used to identify the optimal value of the strength. The strength of the FGEs affects the biomechanical outputs from the model also. Therefore, it is crucial to select the correct value of the strength. The results of this work would be useful for the detailed modelling of the human-exoskeleton interface

Predicting the influence of hip and lumbar flexibility on lifting motions using optimal control

Computational models of the human body coupled with optimization can be used to predict the influence of variables that cannot be experimentally manipulated. Here, we present a study that predicts the motion of the human body while lifting a box, as a function of flexibility of the hip and lumbar joints in the sagittal plane. We modeled the human body in the sagittal plane with joints actuated by pairs of agonist-antagonist muscle torque generators, and a passive hamstring muscle. The characteristics of a stiff, average and flexible person were represented by co-varying the lumbar range-of-motion, lumbar passive extensor-torque and the hamstring passive muscle-force. We used optimal control to solve for motions that simulated lifting a 10 kg box from a 0.3 m height. The solution minimized the total sum of the normalized squared active and passive muscle torques and the normalized passive hamstring muscle forces, over the duration of the motion. The predicted motion of the average lifter agreed well with experimental data in the literature. The change in model flexibility affected the predicted joint angles, with the stiffer models flexing more at the hip and knee, and less at the lumbar joint, to complete the lift. Stiffer models produced similar passive lumbar torque and higher hamstring muscle force components than the more flexible models. The variation between the motion characteristics of the models suggest that flexibility may play an important role in determining lifting technique

Efficient Trajectory Optimization for Curved Running Using a 3D Musculoskeletal Model With Implicit Dynamics

Trajectory optimization with musculoskeletal models can be used to reconstruct measured movements and to predict changes in movements in response to environmental changes. It enables an exhaustive analysis of joint angles, joint moments, ground reaction forces, and muscle forces, among others. However, its application is still limited to simplified problems in two dimensional space or straight motions. The simulation of movements with directional changes, e.g. curved running, requires detailed three dimensional models which lead to a high-dimensional solution space. Weextended a full-body three dimensional musculoskeletal model to be specialized for running with directional changes. Model dynamics were implemented implicitly and trajectory optimization problems were solved with direct collocation to enable efficient computation. Standing, straight running, and curved running were simulated starting from a random initial guess to confirm the capabilities of our model and approach: efficacy, tracking and predictive power. Altogether the simulations required 1 h 17 min and corresponded well to the reference data. The prediction of curved running using straight running as tracking data revealed the necessity of avoiding interpenetration of body segments. In summary, the proposed formulation is able to efficiently predict a new motion task while preserving dynamic consistency. Hence, labor-intensive and thus costly experimental studies could be replaced by simulations for movement analysis and virtual product design

Modelling friction at the mechanical interface between the human and the exoskeleton

In virtual assessments of exoskeletons, often, friction is not modelled even though the actual interface consists of straps or moulded surfaces, where friction could play a significant role. In this work, the human-exoskeleton interaction during the use of a passive lower limb exoskeleton is modelled in three test cases through two different interface models. In particular, a model introducing friction at the human-exoskeleton interface is compared with a more conventional model that uses a kinematic joint to simulate the interface forces. Both the models show a good match between the empirical and predicted distribution of body weight between the subject and the exoskeleton. However, the results also show different trends of the moment required at the assisted joint by the different interface models, highlighting the importance of a realistic interface model to investigate the effectiveness of the exoskeleton in virtual assessments

Parameter optimization for passive spinal exoskeletons based on experimental data and optimal control

Designing an exoskeleton to reduce the risk of low-back injury and to alleviate low-back pain is challenging. Individualizing the support provided to each user is an additional challenge. Subject-specific models of the human body and the exoskeleton combined with movement analysis can support the design process. Here, we utilize experimental data of lifting motions of several subjects to optimize spring characteristics of a spinal exoskeleton. We create subject-specific models of the human body and kinematically couple them with models of spinal exoskeletons. An optimal control approach is used to fit the motion of this combined model to that recorded from experiments, with the exoskeleton spring characteristics as free parameters to be optimized. Our results indicate that the combined human-exoskeleton model is able to track the recorded motions well. Based on the individual lifting styles, the support provided by the exoskeleton as well as the optimal spring stiffness vary across subjects. The computed interaction forces and moments between the human and the exoskeleton, are high on the exoskeleton pelvis module, as well as in the normal direction on the thigh module. The exoskeleton with the optimized spring characteristics could also provide a reduction of the lumbar and hip moments. This framework can be taken as a basis for virtual design and testing of exoskeletons before prototyping, and may be applied to various robotic-assisted human motions

Modelling the Physical Human-Exoskeleton Interface

L'abstract è presente nell'allegato / the abstract is in the attachmen