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. We extended 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.

Optimal control simulation predicts effects of midsole materials on energy cost of running.

Testing sports equipment with athletes is costly, time-consuming, hazardous and sometimes impracticable. We propose a method for virtual testing of running shoes and predict how midsoles made of BOOSTTM affect energy cost of running. We contribute a visco-elastic contact model and identified model parameters based on load-displacement measurements. We propose a virtual study using optimal control simulation of musculoskeletal models. The predicted reduction in energy cost of ∼1% for BOOSTTM in comparison to conventional materials is consistent with experimental studies. This indicates that the proposed method is capable of replacing experimental studies in the future.

Evaluation of a Kinematically-Driven Finite Element Footstrike Model.

A dynamic finite element model of a shod running footstrike was developed and driven with 6 degree of freedom foot segment kinematics determined from a motion capture running trial. Quadratic tetrahedral elements were used to mesh the footwear components with material models determined from appropriate mechanical tests. Model outputs were compared with experimental high-speed video (HSV) footage, vertical ground reaction force (GRF), and center of pressure (COP) excursion to determine whether such an approach is appropriate for the development of athletic footwear. Although unquantified, good visual agreement to the HSV footage was observed but significant discrepancies were found between the model and experimental GRF and COP readings (9% and 61% of model readings outside of the mean experimental reading ± 2 standard deviations, respectively). Model output was also found to be highly sensitive to input kinematics with a 120% increase in maximum GRF observed when translating the force platform 2 mm vertically. While representing an alternative approach to existing dynamic finite element footstrike models, loading highly representative of an experimental trial was not found to be achievable when employing exclusively kinematic boundary conditions. This significantly limits the usefulness of employing such an approach in the footwear development process.

Inertial sensor based and shoe size independent gait analysis including heel and toe clearance estimation.

Falls are a major cause for morbidity and mortality in the ageing society. Inertial sensor based gait assessment including the analysis of the heel and toe clearance can be an indicator for the risk of falling. This paper presents a method for calculating the continuous heel and toe clearance without the knowledge of the shoe dimensions as well as the foot angle in the sagittal plane. These gait parameters were validated using an optical motion capture system. 20 healthy subjects from 3 different age groups (young, mid age, old) performed gait trials with different stride lengths and stride velocities. We obtained low mean absolute errors, low standard deviations and high Pearson correlations (0.91-0.99) for all gait parameters. In summary, we implemented a viable algorithm for the calculation of the heel and toe clearance without knowing the shoe dimensions as well as the foot angle in sagittal plane. We conclude that the given method is applicable for a mobile and unobtrusive gait assessment for healthy subjects from all age classes.

A wireless trigger for synchronization of wearable sensors to external systems during recording of human gait.

Mobile gait analysis focuses on the automatic extraction of gait parameters from wearable sensor data. However, development of algorithms for this task requires kinematic data with accurate and highly synchronous ground truth. In this paper we present a wireless trigger system which allows reliable synchronization of wearable sensors to external systems providing ground truth. To demonstrate the applicability of the system for mobile gait analysis, a Shimmer wireless sensor node with inertial sensors was mounted at the heel of a running shoe and synchronized with an external VICON motion capturing system using the wireless trigger system. Inertial sensor data were recorded during walking and running with the shoe, while kinematic and kinetic ground truth was acquired from the synchronized VICON system. Evaluation of delay and jitter of the system showed a mean delay of 2 ms and low jitter of 20 us. Recording was highly synchronous and the collected kinematics had a correlation of up to 0.99. In the future the proposed system will allow the creation of a database of inertial data from human gait with accurate ground truth synchronization.