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Full-Text Articles in Mechanical Engineering

Use Of Pressure-Measuring Insoles To Characterize Gait Parameters In Simulated Reduced-Gravity Conditions, Christian Ison, Connor Neilsen, Jessica Deberardinis, Mohamed B. Trabia, Janet S. Dufek Sep 2021

Use Of Pressure-Measuring Insoles To Characterize Gait Parameters In Simulated Reduced-Gravity Conditions, Christian Ison, Connor Neilsen, Jessica Deberardinis, Mohamed B. Trabia, Janet S. Dufek

Mechanical Engineering Faculty Research

Prior researchers have observed the effect of simulated reduced-gravity exercise. However, the extent to which lower-body positive-pressure treadmill (LBPPT) walking alters kinematic gait characteristics is not well understood. The purpose of the study was to investigate the effect of LBPPT walking on selected gait parameters in simulated reduced-gravity conditions. Twenty-nine college-aged volunteers participated in this cross-sectional study. Participants wore pressure-measuring insoles (Medilogic GmBH, Schönefeld, Germany) and completed three 3.5-min walking trials on the LBPPT (AlterG, Inc., Fremont, CA, USA) at 100% (normal gravity) as well as reduced-gravity conditions of 40% and 20% body weight (BW). The resulting insole data were …


Cnn-Based Estimation Of Sagittal Plane Walking And Running Biomechanics From Measured And Simulated Inertial Sensor Data, Eva Dorschky, Marlies Nitschke, Christine F. Martindale, Antonie J. Van Den Bogert, Anne D. Koelewijn, Bjoern M. Eskofier Jan 2020

Cnn-Based Estimation Of Sagittal Plane Walking And Running Biomechanics From Measured And Simulated Inertial Sensor Data, Eva Dorschky, Marlies Nitschke, Christine F. Martindale, Antonie J. Van Den Bogert, Anne D. Koelewijn, Bjoern M. Eskofier

Mechanical Engineering Faculty Publications

Machine learning is a promising approach to evaluate human movement based on wearable sensor data. A representative dataset for training data-driven models is crucial to ensure that the model generalizes well to unseen data. However, the acquisition of sufficient data is time-consuming and often infeasible. We present a method to create realistic inertial sensor data with corresponding biomechanical variables by 2D walking and running simulations. We augmented a measured inertial sensor dataset with simulated data for the training of convolutional neural networks to estimate sagittal plane joint angles, joint moments, and ground reaction forces (GRFs) of walking and running. When …


A Weighted Least-Squares Method For Inverse Dynamic Analysis, Antonie J. Van Den Bogert, Anne Su Feb 2008

A Weighted Least-Squares Method For Inverse Dynamic Analysis, Antonie J. Van Den Bogert, Anne Su

Mechanical Engineering Faculty Publications

Internal forces in the human body can be estimated from measured movements and external forces using inverse dynamic analysis. Here we present a general method of analysis which makes optimal use of all available data, and allows the use of inverse dynamic analysis in cases where external force data is incomplete. The method was evaluated for the analysis of running on a partially instrumented treadmill. It was found that results correlate well with those of a conventional analysis where all external forces are known.