Reducing the energy cost of human walking using an unpowered exoskeleton

Abstract

With efficiencies derived from evolution, growth and learning, humans are very well-tuned for locomotion. Metabolic energy used during walking can be partly replaced by power input from an exoskeleton, but is it possible to reduce metabolic rate without providing an additional energy source? This would require an improvement in the efficiency of the human-machine system as a whole, and would be remarkable given the apparent optimality of human gait. Here we show that the metabolic rate of human walking can be reduced by an unpowered ankle exoskeleton. We built a lightweight elastic device that acts in parallel with the user's calf muscles, off-loading muscle force and thereby reducing the metabolic energy consumed in contractions. The device uses a mechanical clutch to hold a spring as it is stretched and relaxed by ankle movements when the foot is on the ground, helping to fulfil one function of the calf muscles and Achilles tendon. Unlike muscles, however, the clutch sustains force passively. The exoskeleton consumes no chemical or electrical energy and delivers no net positive mechanical work, yet reduces the metabolic cost of walking by 7.2 ± 2.6% for healthy human users under natural conditions, comparable to savings with powered devices. Improving upon walking economy in this way is analogous to altering the structure of the body such that it is more energy-effective at walking. While strong natural pressures have already shaped human locomotion, improvements in efficiency are still possible. Much remains to be learned about this seemingly simple behaviour.

Extended Data Figure 1. Energy diagrams for human-exoskeleton walking

Each diagram includes energy inputs, outputs, storage and transfers within the mechanical system, depicted for steady-state walking. In each case, all chemical or electrical energy input is eventually output as heat, since the mechanical energy of the system is constant on average and no useful work is performed on the body or the environment. Energy efficiency, strictly defined, is therefore zero in all cases, and so energy effectiveness or energy economy is instead characterized in terms of ‘cost of transport’, which is the energy used per unit weight per unit distance traveled. (a) Energy diagram for normal human walking. Muscles consume metabolic energy both to produce mechanical work and to absorb it (and to perform a variety of other functions, such as activating or producing force), and so metabolic energy flows only into the system. Energy loss in muscle manifests as heat. Inside the mechanical system, tendons exchange energy with both the muscle and the body, while kinetic and gravitational potential energy are exchanged within the body segments, all at high mechanical efficiency. Body segment mechanical energy is dissipated only in damping in soft tissues, e.g. during collisions, which is small (about 3% of the total metabolic energy input), and in friction from slipping of the feet against the ground, deformation of the ground, or air resistance, all of which are negligible under typical conditions. All of these mechanical losses manifest as heat. (b) Energy diagram for walking with a powered exoskeleton. An additional energy input is provided in the form of, e.g., electricity. The total energy input (and corresponding eventual dissipation) of the system can therefore increase, even if a smaller portion is borne by the human, resulting in poorer overall energy economy. This has been the case with the two powered devices that have reduced the metabolic energy cost of human walking^,. In theory, overall energy economy could still be improved with a powered device in three ways. First, positive mechanical work from muscles could be replaced by work done by a motor with higher efficiency. Second, negative mechanical work could be replaced by generation done by a motor with higher (than −120%) efficiency, thereby usefully recapturing energy that would otherwise be dissipated as heat. In fact, because muscle expends metabolic energy to absorb mechanical work, it is theoretically possible to simultaneously reduce metabolic rate and capture electrical energy with zero electrical input, although this has yet to be demonstrated in practice. Third, the powered device could approximate an unpowered device, with negligible amounts of electricity used only to control the timing of mechanical elements like clutches. (c) Energy diagram for walking with an unpowered exoskeleton. No additional energy supply is provided and so, unlike the powered case, the only way to decrease metabolic energy use is to reduce total system energy dissipation, or, equivalently, to improve the energy economy of the system as a whole. Note that the only difference from normal human walking, in terms of energy flow, is the addition of elements like springs that store and transfer mechanical energy within the system. In this sense, reducing metabolic rate with a passive exoskeleton is akin to changing the person’s morphology such that it is more energy-effective at locomotion.

Extended Data Figure 2. Exoskeleton frame design

A rigid carbon fiber shank frame and foot frame were custom made for each participant. The shank section clamps onto the user’s lower leg just below the knee and connects to the foot frame through a rotary joint at the ankle. The foot frame includes a lever arm protruding to the rear of the heel, to which the parallel spring is connected. The clutch is mounted to the shank frame posterior to the calf muscles.

Extended Data Figure 3. Ankle moment contributions

(a) Total ankle moment, measured using a motion capture system. Average total ankle moment (b) during the entire stride and (c) during early and mid-stance, defined as 0–40% stride, and (d) peak ankle moment. All spring conditions increased average total joint moment slightly during early stance, but peak total joint moment was maintained across conditions. (e) Exoskeleton torque contribution, as measured using onboard sensors. Average exoskeleton torque (f) during the entire stride and (g) during early and mid-stance, defined as 0–40% stride, and (h) peak exoskeleton torque. Average and peak exoskeleton torque increased with increasing exoskeleton spring stiffness, except with the highest stiffness spring. (i) Biological contributions to ankle moment, calculated as the subtraction of the exoskeleton moment from the total moment. Average biological ankle moment (j) during the entire stride and (k) during early and mid-stance, defined as 0–40% stride, and (l) peak ankle moment. Ankle moments arising from muscle activity decreased with increasing exoskeleton spring stiffness, but with diminishing returns at high spring stiffness.

Extended Data Figure 4. Ankle muscle activity

(a) Activity in the soleus, a mono-articular muscle group that acts to plantarflex the ankle. Average soleus activity over (b) the whole stride, (c) early and mid-stance, defined as 0–40% stride, and (d) late stance, defined as 40–60% stride. Soleus activity decreased with increasing spring stiffness. (e) Activity in the gastrocnemius, a biarticular muscle group that acts to plantarflex the ankle and flex the knee. Average gastrocnemius activity over (f) the whole stride, (g) early and mid-stance, defined as 0–40% stride, and (h) late stance, defined as 40–60% stride. Gastrocnemius activity was reduced compared to the No Exoskeleton condition during early and mid-stance, but increased with increasing spring stiffness during late stance. (i) Activity in the tibialis anterior, a mono-articular muscle group that acts to dorsiflex the ankle. Average tibialis anterior activity over (j) the whole stride, (k) early and mid-stance, defined as 0–40% stride, and (l) late stance, defined as 40–60% stride. Tibialis anterior activity seemed to increase during early and mid-stance, and was unchanged during late stance. All values were measured using electromyography and normalized to maximum activity during normal walking.

Extended Data Figure 5. Ankle power contributions

(a) Mechanical power of the combined human-exoskeleton system, measured using a motion capture system, (b) average positive power, defined as positive work divided by stride time, (c) average negative power, defined as negative work divided by stride time, and (d) average net power, equivalent to average power, defined as the sum of positive and negative work divided by stride time. Total positive ankle joint power decreased with increasing stiffness, while net joint power increased. (e) Exoskeleton power, measured using onboard sensors for torque and motion capture for joint velocity, (f) average positive exoskeleton power, (g) average negative exoskeleton power, and (h) average net exoskeleton power. Net exoskeleton power was always negative. (i) Biological ankle power, defined as the subtraction of exoskeleton power from total ankle power, (j) average positive biological power, (k) average negative biological power, and (l) average net biological power. Net biological power increased with the exoskeleton compared to normal walking.

Extended Data Figure 6. Knee moment

(a) Knee moment in time as measured by motion capture, (b) average absolute knee moment over the entire stride, (c) average knee moment during early stance, defined as the positive impulse within approximately 10–30% stride divided by stride period, (d) average knee moment during late stance, defined as the negative impulse within approximately 30–50% stride divided by stride period. Average knee moment during late stance increased in magnitude with the highest stiffness springs. Positive values denote knee extension.

Extended Data Figure 7. Hip, knee and ankle joint mechanics

Joint angles, moments and powers are presented at the same scale to facilitate comparisons across joints. (a) Hip joint angle, (b) knee joint angle, and (c) ankle joint angle. Joint angle trajectories did not appear to change substantially across conditions. (d) Hip moment, (e) knee moment, and (f) biological component of ankle moment. Hip moment did not appear to change substantially across conditions, while knee moment and ankle moment showed trends detailed in Extended Data Figures 6 and 3, respectively. (g) Hip joint power, (h) knee joint power, and (i) the biological component of ankle joint power. Hip and knee power did not appear to change substantially across conditions, while biological ankle power showed trends detailed in Extended Data Figure 5. Positive values denote hip extension, knee extension and ankle plantarflexion with respect to standing posture.

Extended Data Figure 8. Center-of-mass mechanics

(a) The biological contribution to center-of-mass power for each individual limb, defined as the dot product of ground reaction force with center-of-mass velocity, both determined from force plate data, minus the ankle exoskeleton power. (b) Average collision power, defined as the negative work performed during the first half of stance divided by stride time. (c) Average rebound power, defined as the positive work performed during mid-stance divided by stride time. (d) Average preload power, defined as the negative work performed during mid-stance divided by stride time. (e) Average push-off power, defined as the positive work performed during late stance divided by stride time. With increasing spring stiffness, the human contribution to push-off work decreased, while the human contribution to rebound work increased substantially.

Figure 1. Unpowered exoskeleton design

(a) The exoskeleton comprises rigid sections attached to the human shank and foot and hinged at the ankle. A passive clutch mechanism and series spring act in parallel with the calf muscles and Achilles tendon. (b) Participant walking with the device. Load cells measured spring force. Photo by Stephen Thrift. (c) The passive clutch mechanism has no electronics, but instead uses a ratchet and pawl that mechanically engage the spring when the foot is on the ground and disengage it when the foot is in the air.

Figure 2. Mechanics and muscle activity

(a) Exoskeleton torque (normalized to body mass) in time (normalized to stride period) for each spring, averaged across participants. Bars at right are the average of these trajectories in time, with error bars denoting standard error and p-values indicating the results of ANOVA tests for an effect of spring stiffness. Exoskeleton torque increased with spring stiffness (except with the stiffest spring, which tended to be engaged later in stance). (b) Time course of the biological contributions to ankle moment, which decreased with increasing spring stiffness. (c) Time course of electrical activity in the soleus muscle, an ankle plantarflexor, which decreased with increasing spring stiffness. (d) Time course of ankle joint angle, which triggered passive clutch engagement and disengagement. The ratchet was engaged at heel strike, took up slack through foot flat, held the spring as it stretched and recoiled through mid and late stance, and disengaged to allow toe clearance during leg swing. The average stride period was 1.15 ± 0.08 s (mean ± s.d.).

Figure 3. Human metabolic rate

Spring stiffness affected metabolic rate [N = 9; ANOVA with second order model; p(stiffness) = 0.016, p(stiffness²) = 0.008]. Net metabolic rate, with the value for quiet standing subtracted out, was 7.2 ± 2.6% (mean ± s.e.m.) lower with the 180 N·m·rad⁻¹ spring (orange bar) than during normal walking (dark gray bar; paired two-sided t-test with correction for multiple comparisons; p = 0.023). The dashed line is a quadratic best fit to mean data from exoskeleton conditions (R² = 0.91, p = 0.029). Wearing the exoskeleton with the spring removed (light gray bar, k = 0) did not increase energy cost compared to normal walking (paired t-test; p = 0.9). Error bars depict standard error, dominated by inter-subject variability.