To address the occurrence of lumbar spine disease among labor workers who carry heavy objects, a passive energy storage based exoskeletal apparatus was designed to assist, using springs as energy storage elements and utilizing the change in energy that occurs when the human body is bent during the process of lifting objects. First, the mechanism of the exoskeleton was statically modeled; the spring stiffnesses and the locations of support points were used as design variables to optimize the model by optimizing the effective moment on the lumbar spine. Next, an optimized algorithm (Optdes-Sqp) based on the Newton method for solving quadratic programming subproblems was applied to optimize the stiffnesses of compression and extension springs and the positions of the upper support points of each spring. The accuracy of the simulated model was also verified using MATLAB software. Finally, the effect of optimization was verified, and the respiratory rates and heart rates of subjects before and after wearing the exoskeleton were analyzed. The experimental results show that the exoskeleton designed in this study assisted the subjects, and the results lay the foundation for follow-up designs and studies of exoskeletons.
Parameter Optimization and Experimental Analysis of Passive Energy Storage Power-Assisted Exoskeleton
