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We present a passive (unpowered) exoskeleton that assists the back during lifting. Our exoskeleton uses carbon fiber beams as the sole means to store energy and return it to the wearer. To motivate the design, we present general requirements for the design of a lifting exoskeleton, including calculating the required torque to support the torso for people of different weights and heights. We compare a number of methods of energy storage for exoskeletons in terms of mass, volume, hysteresis, and cycle life. We then discuss the design of our exoskeleton, and show how the torso assembly leads to balanced forces. We characterize the energy storage in the exoskeleton and the torque it provides during testing with human subjects. Ten participants performed freestyle, stoop, and squat lifts. Custom image processing software was used to extract the curvature of the carbon fiber beams in the exoskeleton to determine the stored energy. During freestyle lifting, it stores an average of 59.3 J and provides a peak torque of 71.7 Nm.

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Despite several attempts to quantify the metabolic savings resulting from the use of passive back-support exoskeletons (BSEs), no study has modeled the metabolic change while wearing an exoskeleton during lifting. The objectives of this study were to: 1) quantify the metabolic reductions due to the VT-Lowe's exoskeleton during lifting; and 2) provide a comprehensive model to estimate the metabolic reductions from using a passive BSE. In this study, 15 healthy adults (13M, 2F) of ages 20 to 34 years (mean=25.33, SD=4.43) performed repeated freestyle lifting and lowering of an empty box and a box with 20% of their bodyweight. Oxygen consumption and metabolic expenditure data were collected. A model for metabolic expenditure was developed and fitted with the experimental data of two prior studies and the without-exoskeleton experimental results. The metabolic cost model was then modified to reflect the effect of the exoskeleton. The experimental results revealed that VT-Lowe's exoskeleton significantly lowered the oxygen consumption by ~9% for an empty box and 8% for a 20% bodyweight box, which corresponds to a net metabolic cost reduction of ~12% and ~9%, respectively. The mean metabolic difference (i.e., without-exo minus with-exo) and the 95% confidence interval were 0.36 and (0.2-0.52) [Watts/kg] for 0% bodyweight, and 0.43 and (0.18-0.69) [Watts/kg] for 20% bodyweight. Our modeling predictions for with-exoskeleton conditions were precise, with absolute freestyle prediction errors of <2.1%. The model developed in this study can be modified based on different study designs, and can assist researchers in enhancing designs of future lifting exoskeletons.