Session: MSNDC-10-01: Nonlinear and Computational Dynamics Aspects in Biomechanics

Paper Number: 112425

112425 - Parametric Musculoskeletal Model for Human-Robot Interaction Simulation in Warfield Rescue: A Pilot Study 

A novel physics-based human-robot interaction method is proposed and applied to drag the wounded warfighter in the overhead direction in this study. This method predicts the rescue motion using a full-body skeletal model and forward dynamics in OpenSim. The ground reaction force (GRF) is calculated by the contact models in OpenSim, and external forces are applied to the skeletal model. The predicted motion data and a full-body musculoskeletal model are the input for inverse dynamics and static optimization, and the output is joint torques. The simulation results are validated by a kinematic and a joint torque range verification. The proposed model can analyze the rescue scenarios almost in real time and predicts the potential risk of injuries during rescue motion.

This work is a pilot study for developing full-body musculoskeletal and skeletal models to perform rescue tasks. We will analyze two rescue task scenarios using the full-body human models. The first task is a flat dragging motion in which the subject is lying down and both knees are extended. Another task is right knee-folded dragging, which includes an impact phase between the right knee and the ground. The skeletal model is used to predict the dragging motion by forward dynamics. The musculoskeletal model can assess the joint torques and muscle activation levels with the predicted motion.

Presenting Author: Seunghun Lee Texas Tech University

Presenting Author Biography: Seunghun Lee is a Ph.D. Candidate at the Department of Mechanical Engineering, Texas Tech University.

Authors:

Seunghun Lee Texas Tech University
Zhiqing Cheng Innovision LLC
James Yang Texas Tech University