The Only Way Is Up: Active Knee Exoskeleton Reduces Muscular Effort in Quadriceps During Weighted Stair Ascent

Abstract

Firefighters consistently rank stair ascent with gear, which can weigh over 35 kg, as their most demanding activity. Weighted stair climbing requires dynamic motions and large knee torques, which can cause exhaustion in the short term, and overuse injuries in the long term. An active knee exoskeleton could potentially alleviate the burden on the wearer by injecting positive energy at key phases of the gait cycle. Similar devices have reduced the metabolic cost for various locomotion activities in previous studies. However, no information is available on the effect of active knee exoskeletons on muscular effort during prolonged weighted stair ascent. Here we show that our knee exoskeletons reduce the net muscular effort in the lower limbs when ascending several flights of stairs while wearing additional weight. In a task analogous to part of the physical fitness test for firefighters in the US, eight participants climbed stairs for three minutes at a constant pace while wearing a 9.1 kg vest. We compared lower limb muscle activation required to perform the task with and without two bilaterally worn Utah Knee Exoskeletons. We found that bilateral knee assistance reduced average peak quadriceps muscle activation measured through surface electromyography by 32% while reducing overall muscle activity at the quadriceps by 29%. These results suggest that an active knee exoskeleton can lower the overall muscular effort required to ascend stairs while weighted. In turn, this could aid firefighters by preserving energy for fighting fires and reducing overexertion injuries.

Keywords: EMG; Wearable robotics; physically assistive devices; prosthetics and exoskeletons; stairs.

Fig. 1.

A picture of the Utah Knee Exoskeleton, including covers and physical interfaces. A total of eight physically adjustable settings are present to improve fitting for a wider range of wearers.

Fig. 2

Left, a participant on the step mill with the active knee exoskeletons worn bilaterally while walking up the stairs with a 9.1 kg weighted vest. Right, the placement of Xsens (kinematic) sensors and Delsys (surface electromyography) to gather biomechanical data.

Fig. 3.

Block diagram of the stair ascent controller. A finite state machine determines if the wearer is in flexion or extension. During extension, a position-based torque profile is employed, while no assistance is given in flexion. Additional impedance compensation torque is provided based on the motion of the motor and passive variable transmission. The (desired) feed-forward current is computed using the instantaneous transmission ratio of the drive train.

Fig. 4.

Mean bodyweight normalized exoskeleton torque (top), power (middle) and energy generated per stride (bottom) on the left (left column) and right (right column) side for each participant. Extension is defined as positive. The gait cycle is segmented based on the maximum angle of the thigh per stride.

Fig. 5.

(a) The mean kinematics of the lower limb joints plotted over the gait cycle. (b) The minimum hip flexion angle (above) and peak knee extension speed (below). (c) The mean trunk kinematics plotted over the gait cycle (above) and the mean trunk angle (below). Trunk kinematics are segmented based on the strides of the left leg. In line plots, the colored shading indicates a range of one standard deviation above and below the mean. In bar plots, colored dots represent individual subjects. Crosses above the bar plots indicate statistically significant differences between the two testing conditions (p < 0.05).

Fig. 6.

Muscle activation of the rectus femoris (RF), vastus medialis (VM), vastus lateralis (VL), and gastrocnemius medialis (GM). (a) The mean muscle activation across the gait cycle. The colored shading indicates a range of one standard deviation above and below the mean. (b) The change in the mean muscle activation integrated over the stride. (c) The change in the mean peak muscle activation per stride. EMG data is normalized by the mean peak activation during the no-exoskeleton trial. The bar graphs indicate the percentage change between the no-exoskeleton trial and the exoskeleton trial, averaged over both legs. The grey bars represent the average of all participants, with crosses indicating statistical significance (p < 0.05).