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Training Persons with Spinal Cord Injury to Ambulate Using a Powered Exoskeleton
Published on: June 16, 2016
Simulation-based biomechanical assessment of unpowered exoskeletons for running
Hamidreza Aftabi1, Rezvan Nasiri2, Majid Nili Ahmadabadi1
1Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Abstract:
Due to the complexity and high degrees of freedom, the detailed assessment of human biomechanics is necessary for the design and optimization of an effective exoskeleton. In this paper, we present full kinematics, dynamics, and biomechanics assessment of unpowered exoskeleton augmentation for human running gait. To do so, the considered case study is the assistive torque profile of I-RUN. Our approach is using some extensive data-driven OpenSim simulation results employing a generic lower limb model with 92-muscles and 29-DOF. In the simulation, it is observed that exoskeleton augmentation leads to [Formula: see text] metabolic rate reduction for the stiffness coefficient of [Formula: see text]. Moreover, this optimum stiffness coefficient minimizes the biological hip moment by [Formula: see text]. The optimum stiffness coefficient ([Formula: see text]) also reduces the average force of four major hip muscles, i.e., Psoas, Gluteus Maximus, Rectus Femoris, and Semimembranosus. The effect of assistive torque profile on the muscles' fatigue is also studied. Interestingly, it is observed that at [Formula: see text], both all 92 lower limb muscles' fatigue and two hip major mono-articular muscles' fatigue have the maximum reduction. This result re-confirm our hypothesis that "reducing the forces of two antagonistic mono-articular muscles is sufficient for involved muscles' total fatigue reduction." Finally, the relation between the amount of metabolic rate reduction and kinematics of hip joint is examined carefully where for the first time, we present a reliable kinematic index for prediction of the metabolic rate reduction by I-RUN augmentation. This index not only explains individual differences in metabolic rate reduction but also provides a quantitative measure for training the subjects to maximize their benefits from I-RUN.
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