Autonomous exoskeleton reduces metabolic cost of human walking during load carriage

Abstract

Background: Many soldiers are expected to carry heavy loads over extended distances, often resulting in physical and mental fatigue. In this study, the design and testing of an autonomous leg exoskeleton is presented. The aim of the device is to reduce the energetic cost of loaded walking. In addition, we present the Augmentation Factor, a general framework of exoskeletal performance that unifies our results with the varying abilities of previously developed exoskeletons.

Methods: We developed an autonomous battery powered exoskeleton that is capable of providing substantial levels of positive mechanical power to the ankle during the push-off region of stance phase. We measured the metabolic energy consumption of seven subjects walking on a level treadmill at 1.5 m/s, while wearing a 23 kg vest.

Results: During the push-off portion of the stance phase, the exoskeleton applied positive mechanical power with an average across the gait cycle equal to 23 ± 2 W (11.5 W per ankle). Use of the autonomous leg exoskeleton significantly reduced the metabolic cost of walking by 36 ± 12 W, which was an improvement of 8 ± 3% (p = 0.025) relative to the control condition of not wearing the exoskeleton.

Conclusions: In the design of leg exoskeletons, the results of this study highlight the importance of minimizing exoskeletal power dissipation and added limb mass, while providing substantial positive power during the walking gait cycle.

Figure 1

Autonomous leg exoskeleton. (A) The autonomous exoskeleton applies torque about the human ankle joint during walking, adding positive mechanical power to the wearer during the push-off portion of stance phase. During the swing phase, the device applies negligible forces on the wearer by allowing small amounts of slack into the cord. The mechanism consists of a winch actuator and fiberglass struts that directly apply a resultant torque about the ankle. (B) The winch actuator provides a torque on the ankle by winding the cord around the spool. As the cord is tightened, a force is applied to the struts on either side of the leg. The winch actuator’s brushless motor applies the torque to the ankle joint through a transmission that consists of the belt transmission stage in series with the geometric transmission stage comprising spool, idler roller and strut.

Figure 2

Calculation of negative net-power dissipation term, p^dis. Various power profiles are shown with the corresponding positive and dissipative powers. Note that when mean positive power is greater than the mean negative power, the dissipative term is zero.

Figure 3

Mechanical and metabolic results of wearing the autonomous exoskeleton. (A) Inter-subject mean exoskeletal ankle power provided by only the exoskeleton is shown (blue) throughout a single gait cycle, while carrying load. Power is normalized by body mass with standard deviation shown in translucent. For comparison, the mechanical power provided by only the biological ankle joint is shown (dashed red) in the case of fast walking without a load or exoskeleton, acquired from a reference dataset [33]. The normalized maximum mechanical power produced by the ankle while walking with a 20 kg load has been shown to increase to over 6 W/kg [23]. (B) Inter-subject mean change in mechanical and metabolic power is shown when using the exoskeleton is compared to not using the exoskeleton, with error bars denoting standard error. The increase in exoskeletal mechanical power demonstrates how much positive mechanical power is provided to the wearer by the exoskeleton. The decrease in metabolic power demonstrates the reduction in the rate of metabolic energy consumed while wearing the exoskeleton.

Figure 4

Augmentation Factor (AF). The AF was calculated for six devices and compared to the measured metabolic impact for each device [9,10,12,20,22]. Triangle markers are previously published autonomous devices, square markers are previously published tethered devices, and the circle marker is the presented autonomous exoskeleton of this study. The equation estimated by linear regression is y = 1.1x – 4 with an R² equal to 0.98. In the AF equation, the p⁺ term is calculated by taking the positive work done by an exoskeleton during the gait cycle and dividing by the gait cycle duration. If the net-work done by the exoskeleton is negative, then p^dis is equal to this negative net-work divided by the gait cycle duration, otherwise, p^dis is zero.