|
|
|
|||
| Home Help Feedback Subscriptions Archive Search Table of Contents | ||||
First published online December 16, 2008
Journal of Experimental Biology 212, 21-31 (2009)
Published by The Company of Biologists 2009
doi: 10.1242/jeb.017269
Powered ankle exoskeletons reveal the metabolic cost of plantar flexor mechanical work during walking with longer steps at constant step frequency
Human Neuromechanics Laboratory, University of Michigan at Ann Arbor, Ann Arbor, MI 48109, USA
* Author for correspondence (e-mail: gsawicki{at}brown.edu)
Accepted 24 October 2008
| Summary |
|---|
|
|
|---|
25% more average positive
mechanical power (P=0.01; +0.20±0.02 W kg–1
to +0.25±0.02 W kg–1, respectively). The exoskeletons
reduced net metabolic power by more at longer step lengths (P=0.002;
–0.21±0.06 W kg–1 at 0.8 L* and
–0.70±0.12 W kg–1 at 1.4 L*). For
every 1 J of exoskeleton positive mechanical work subjects saved 0.72 J of
metabolic energy (`apparent efficiency'=1.39) at 0.8 L* and 2.6 J
of metabolic energy (`apparent efficiency'=0.38) at 1.4 L*.
Declining ankle muscle–tendon `apparent efficiency' suggests an increase
in ankle plantar flexor muscle work relative to Achilles' tendon elastic
energy recoil during walking with longer steps. However, previously stored
elastic energy in Achilles' tendon still probably contributes up to 34% of
ankle muscle–tendon positive work even at the longest step lengths we
tested. Across the range of step lengths we studied, the human ankle
muscle–tendon system performed 34–40% of the total lower-limb
positive mechanical work but accounted for only 7–26% of the net
metabolic cost of walking.
Key words: locomotion, walking, step length, metabolic cost, exoskeleton, ankle, human, inverse dynamics, joint power, efficiency
| INTRODUCTION |
|---|
|
|
|---|
Although a pre-emptive push-off can help reduce collision losses, the
trailing leg still must perform positive mechanical work during double
support. Trailing limb positive mechanical work constitutes
60–70%
of the total positive work performed over a stride and the ankle plantar
flexors provide the majority of that work
(Kuo et al., 2005
).
Theoretical analyses of simple bipedal walking models
(Kuo, 2002
;
Ruina et al., 2005
) and
empirical measurements on humans (Donelan
et al., 2002a
; Donelan et al.,
2002b
) both indicate that step-to-step transition positive
mechanical work increases with step length to the fourth power. Net metabolic
power during human walking also increases in proportion to the fourth power of
step length (Donelan et al.,
2002a
). These data indicate that the step-to-step transition
probably accounts for
60–70% of the total net metabolic power (W
kg–1) during walking
(Donelan et al., 2002a
;
Kuo et al., 2005
).
Although we know that plantar flexor muscle–tendons generate the
largest power burst during trailing limb push-off
(Eng and Winter, 1995
;
Gitter et al., 1991
;
Meinders et al., 1998
),
inverse dynamics cannot separate positive work performed by plantar flexor
muscles from positive work delivered by previously stored elastic energy in
the Achilles' tendon. Recent studies using ultrasound have directly examined
in vivo muscle–tendon behavior in walking humans. Results
indicate that the Achilles' tendon stores energy throughout stance and then
recoils rapidly contributing significantly to trailing limb ankle
muscle–tendon mechanical power output during the push-off phase of the
step-to-step transition (Fukunaga et al.,
2001
; Ishikawa et al.,
2005
; Ishikawa et al.,
2006
; Lichtwark et al.,
2007
; Lichtwark and Wilson,
2006
; Lichtwark and Wilson,
2007
). Ultrasound studies have not yet examined the effects of
increasing walking speed on plantar flexor–Achilles' muscle–tendon
mechanics and energetics. Indirect evidence, suggests that the contribution of
the Achilles' tendon to ankle muscle–tendon positive power may be highly
speed dependent (Hansen et al.,
2004
; Hof et al.,
2002
; Neptune et al.,
2008
).
In a previous study, we showed that bilateral robotic lower-limb
exoskeletons can be used to examine the metabolic cost of ankle
muscle–tendon mechanical work during human walking
(Sawicki and Ferris, 2008
). We
assumed that exoskeleton artificial pneumatic muscles directly replaced
plantar flexor muscle–tendon positive mechanical work. Reported values
of the `muscular efficiency' (
+muscle) of positive
work for mammalian skeletal muscle range from 0.10–0.34, with many
sources assuming an average of
0.25
(Gaesser and Brooks, 1975
;
Margaria, 1968
;
Ryschon et al., 1997
;
Smith et al., 2005
;
Whipp and Wasserman, 1969
).
Comparison of changes in net metabolic power and average mechanical power at
the ankle joint in our previous exoskeleton study yielded an `apparent
efficiency' of ankle muscle–tendon positive mechanical work of 0.61 for
walking at 1.25 m s–1. Our results were indicative of the
Achilles' tendon performing
59% of the plantar flexor muscle–tendon
positive work (assuming
+muscle=0.25)
(Sawicki and Ferris, 2008
). We
estimated that the plantar flexor muscle–tendons performed
35% of
the total lower limb positive mechanical work, but consumed only
19% of
the total metabolic energy during level walking at 1.25 m
s–1.
The purpose of the present study was to extend our previous exoskeleton
results to examine the metabolic cost of plantar flexor muscle–tendon
work at longer step lengths. Humans normally increase walking speed by
increasing both step length and step frequency. However, step-to-step
transition mechanical and metabolic energy expenditure depends most strongly
on step length (
step length4)
(Donelan et al., 2002a
;
Donelan et al., 2002b
). We
chose to have our subjects increase walking speed by increasing step length
only (i.e. while holding step frequency constant). This kept
frequency-dependent metabolic costs (e.g. leg swing) constant and resulted in
larger increases in step-to-step transition mechanical and metabolic power
requirements than would be expected for natural increases in speed (see
Materials and methods for more details). We hypothesized that the `apparent
efficiency' of plantar flexor muscle–tendon positive work would decrease
at longer step lengths. We based this hypothesis on the expectation that as
speed and step length increased, the plantar flexor muscle fibers would
deliver a larger fraction of the ankle muscle–tendon positive work than
elastic energy from the recoiling Achilles' tendon. An inherent assumption of
this study was that the exoskeleton mechanical work would replace ankle
muscle–tendon mechanical work rather than augment it. As such, we
expected triceps surae muscle activation to be less during walking with the
powered exoskeletons compared to walking without exoskeleton assistance for
all speed–step length conditions. To test these predictions, we compared
subjects' net metabolic power and electromyography amplitudes with ankle
exoskeletons powered versus unpowered during level, steady-speed
walking at various step lengths and a constant step frequency (i.e. preferred
at 1.25 m s–1).
| MATERIALS AND METHODS |
|---|
|
|
|---|
Exoskeletons
We custom built lightweight [mass=1.18±0.11 kg each (mean ±
s.d.)] bilateral, ankle-foot exoskeletons (i.e. orthoses) for each subject.
The exoskeletons allowed free rotation about the ankle plantar/dorsiflexion
axis. We used a metal hinge joint to connect a carbon fiber shank to a
polypropylene foot section. We used two stainless steel brackets to attach a
single artificial pneumatic muscle (length=45.6±2.2 cm; moment
arm=10.6±0.9 cm) along the posterior shank of each exoskeleton. We used
a physiologically inspired controller to command the exoskeleton plantar
flexor torque assistance with timing and amplitude derived from the user's own
soleus electromyography (i.e. proportional myoelectric control)
(Gordon and Ferris, 2007
;
Sawicki and Ferris, 2008
).
Specific details on the design and performance of the exoskeletons are
documented elsewhere (Ferris et al.,
2005
; Ferris et al.,
2006
; Gordon et al.,
2006
; Sawicki and Ferris,
2008
; Sawicki et al.,
2005
).
Protocol
Experienced (>90 min walking with powered exoskeletons) subjects walked
on a motorized treadmill with bilateral ankle exoskeletons unpowered then
powered at four different speeds/step lengths [0.8x, 1.0x,
1.2x and 1.4x preferred step length (L*) for unpowered
walking at 1.25 m s–1]
(Donelan et al., 2002a
;
Donelan et al., 2002b
)
(Fig. 1; supplementary material
Movie 1). Our previous research demonstrated no further reductions in net
metabolic power (W kg–1) after 90 min of powered walking
practice (Sawicki and Ferris,
2008
). We determined subjects' preferred step period (seconds)
using a stopwatch to record the mean time of three 100-step intervals during
unpowered treadmill walking at 1.25 m s–1. We took the
reciprocal of the mean step period to get the preferred step frequency (steps
s–1) at 1.25 m s–1. Then we divided the
treadmill belt speed (m s–1) by the step frequency (steps
s–1) to get the preferred step length (m
step–1) at 1.25 m s–1 (1.0 L*).
We used a metronome to enforce subjects' preferred step frequency at 1.25 m
s–1 for all conditions. We adjusted the treadmill belt speed
to constrain subjects' step lengths. The 0.8 L*, 1.0 L*,
1.2 L* and 1.4 L*, step-length conditions corresponded
to
1.00, 1.25, 1.50 and 1.75 m s–1 treadmill belt
speeds, respectively. We could have studied the step-to-step transition
allowing subjects to increase walking speed naturally by choosing their
preferred step length and step frequency. Instead, we chose to constrain step
frequency and vary step length, for two reasons. First, this protocol allowed
us to enforce step-to-step transition center of mass mechanical and net
metabolic power to follow a known strong proportional relationship with the
step length (
step length4)
(Donelan et al., 2002a
;
Donelan et al., 2002b
) in all
walking conditions. This helped limit potential confounding effects of
frequency-dependent changes in metabolic cost between powered and unpowered
walking conditions (e.g. swing leg costs). Some estimates of swing leg
metabolic cost are as high as 33% of the total metabolic cost
(Doke et al., 2005
). Second,
manipulating step length at a fixed step frequency in order to alter speed
increased the range of mechanical and net metabolic power requirements
considerably beyond what could be studied if subjects chose their preferred
step frequency at each speed. We estimate the percentage difference in step
lengths we studied compared to preferred step lengths are –12%, 0%,
+14%, and +19% for 1.0, 1.25, 1.5 and 1.75 m s–1,
respectively.
|
Data collection and analysis
We recorded subjects' ankle, knee and hip joint kinematics, whole-body gait
kinematics, ankle dorsiflexor and plantar flexor electromyography, and
exoskeleton artificial muscle forces. For kinematic, electromyographic and
artificial muscle force data we acquired 10 s trials (i.e.
7–9
walking strides) at the beginning of minutes 4, 5 and 6 during each of the
eight (unpowered mode and powered mode for each of four speeds/step lengths) 7
min trials. We measured O2 consumption and CO2
production during a single 7 min quiet standing trial of metabolic data for
each subject before walking trials commenced. Metabolic data were collected
continuously during each of the 7 min speed/step-length conditions.
In addition, on a separate day of testing, we recorded metabolic data while subjects completed each of the speed/step-length conditions on the treadmill without (without) wearing powered exoskeletons. In the same session, we also recorded simultaneous joint kinematics and ground reaction force data for overground walking with unpowered exoskeletons (seven trials for each speed/step-length condition).
Specific details on procedures for analysis of the metabolic cost,
kinematics, joint mechanics, exoskeleton mechanics and electromyography data
are identical to those in our previous research
(Sawicki and Ferris,
2008
).
Ankle joint muscle–tendon `apparent efficiency' via exoskeleton performance index
By combining measures of mechanical and metabolic power (W
kg–1), we computed the exoskeleton performance index and
ankle joint muscle–tendon `apparent efficiency'
(
+ankle). First, we subtracted the net metabolic
power during unpowered walking from the net metabolic power during powered
walking for each speed/step length to obtain the metabolic power savings
resulting from the exoskeleton assistance. Muscles perform positive mechanical
work with a `muscular efficiency' (
+muscle) of, on
average,
0.25 (ranging from 0.10–0.34)
(Gaesser and Brooks, 1975
;
Margaria, 1968
;
Ryschon et al., 1997
;
Smith et al., 2005
;
Whipp and Wasserman, 1969
) and
we assumed that changes in net metabolic power would reflect the cost of the
underlying plantar flexor muscle positive mechanical work replaced by the
powered exoskeletons. Therefore, we multiplied changes in net metabolic power
by
+muscle=0.25 to yield the expected amount of
average positive mechanical power (W kg–1) delivered by the
exoskeletons for a given change in net metabolic power. Then we divided the
measured by the expected average positive mechanical power delivered by the
exoskeletons to yield the exoskeleton performance index (i.e. ankle muscle
work fraction; Eqn 1):
![]() | (1) |
We inverted and scaled the performance index by
+muscle to obtain the `apparent efficiency'
(Asmussen and Bonde-Petersen,
1974
) (Eqn 2). For
example, with
+muscle=0.25, performance index=1.0
yields `apparent efficiency'=0.25 and would indicate that each joule of
exoskeleton positive mechanical work results in a 4 joule reduction in net
metabolic cost. In this case, all of the underlying ankle muscle–tendon
positive work is performed by active plantar flexor fiber shortening (muscle
work fraction=1.0) and none by previously stored elastic energy returned by
the Achilles' tendon:
![]() | (2) |
+muscle (i.e. muscle work
fraction <
+muscle). In fact, if all of the ankle
muscle–tendon positive work was performed by Achilles' tendon recoil
with small metabolic cost, the performance index would approach zero and the
`apparent efficiency' would approach infinity. More details on this approach
can be found in our previous publication
(Sawicki and Ferris,
2008
|
In the first two analyses, we assessed the effect of speed/step length (0.8 L*, 1.0 L*, 1.2 L*, 1.4 L*) on net metabolic power, exoskeleton mechanics, stance phase root mean square electromyography (r.m.s. EMG) and gait kinematics metrics [one-way ANOVA (step length)] for powered and unpowered data grouped together (except powered data only for exoskeleton mechanics and without, unpowered and powered data grouped for net metabolic power).
In the other four ANOVA analyses (one for 0.8 L*, 1.0 L*, 1.2 L* and 1.4 L*), we assessed the effect of exoskeleton mode (without, unpowered, powered), on net metabolic power (without versus unpowered versus powered), stance phase r.m.s. EMG and gait kinematics (unpowered versus powered) metrics [one-way ANOVA (mode)].
| RESULTS |
|---|
|
|
|---|
The knee and hip joint angles over the stride were nearly identical during powered versus unpowered walking for all speed/step-length conditions. Ankle joint kinematics, however, were slightly altered by exoskeleton mechanical assistance during powered walking for all speed/step-length conditions (Fig. 2).
|
+16°.
During powered 1.4 L* the ankle joint angle peaked slightly earlier
in the stride cycle and reached
+18°
(Fig. 2). For all speeds/step
lengths, swing phase ankle joint angle was similar during powered and
unpowered walking.
Exoskeleton mechanics
The exoskeletons produced only small amounts of torque about the ankle
during unpowered walking and delivered near zero mechanical power to the user
over the stride (Fig. 3).
During powered walking, exoskeletons produced similar peak torque
(
0.40–0.42 Nm kg–1) at all speeds/step lengths.
For walking at preferred step length (1.0 L*) peak exoskeleton
torque was
32% of the overground peak ankle joint moment during unpowered
walking (Fig. 3).
During powered walking, as speed/step length increased, the peak ankle
joint angular velocity increased sharply and occurred earlier in the stride.
Peak ankle joint angular velocity was
154 deg. s–1 (at
58% of the stride) during powered 0.8 L* and increased to
218
deg. s–1 (at 53% of the stride) during powered 1.4
L* (Fig. 3).
As a result of increases in ankle joint angular velocity, the peak
exoskeleton mechanical power at push-off increased with speed/step length from
0.8 W kg–1 during powered 0.8 L* to
1.2
W kg–1 during powered 1.4 L*
(Fig. 3). The exoskeleton peak
mechanical power was 49% of the overground peak ankle joint mechanical power
for walking at the shortest step lengths (0.8 L*) and decreased to
31% of the overground peak ankle joint mechanical power for walking at the
longest step lengths (1.4 L*;
Fig. 3).
|
25% to
0.25±0.02 W kg–1 during powered 1.4 L*.
When powered, exoskeletons absorbed very little mechanical energy. Exoskeleton
average negative mechanical power (–0.03 W kg–1) over
the stride was not different for powered walking at different step lengths
(P=0.27; Fig. 5B).
|
During overground walking with unpowered exoskeletons, the hip and ankle produced most of the positive mechanical power at all speeds/step lengths. The hip average positive mechanical power over the stride was 0.39±0.04 W kg–1 at unpowered 0.8 L*, 0.47±0.05 W kg–1 at unpowered 1.0 L*, 0.51±0.04 W kg–1 at unpowered 1.2 L*, and 0.60±0.04 W kg–1 at unpowered 1.4 L*. The ankle average positive mechanical power over the stride was 0.28±0.03 W kg–1 at unpowered 0.8 L*, 0.38±0.03 W kg–1 at unpowered 1.0 L*, 0.52±0.03 W kg–1 at unpowered 1.2 L*, and 0.63±0.04 W kg–1 at unpowered 1.4 L*.
The ankle muscle–tendon system contributed a larger percentage of the summed lower-limb muscle–tendon (ankle + knee + hip) average positive mechanical power over the stride as speed/step length increased (34% at 0.8 L* and 39% at 1.4 L*; Fig. 4). However, the exoskeletons contributed a smaller percentage of the ankle muscle–tendon positive mechanical power with increasing step length [70% at the shortest steps (0.8 L*) and only 40% at the longest steps (1.4 L*)] (Fig. 4). As a result, the exoskeletons delivered less of the average lower-limb positive mechanical power over the stride during powered 1.4 L* (16%) when compared to powered 0.8 L* (24%; Fig. 4).
Metabolic cost
Subjects' net metabolic power increased consistently with increasing
speed/step length (P<0.0001). In addition, net metabolic power was
significantly lower during powered versus unpowered walking for
speeds/step lengths equal to or longer than preferred 1.0 L*
(Table 1).
|
Probably as a result of added exoskeleton mass, the net metabolic power was
significantly higher (by
8–15%) during walking with unpowered
exoskeletons compared with walking without exoskeletons for all speeds/step
lengths except the longest 1.4 L*
(Table 1). The net metabolic
power during powered exoskeleton walking (6.19±0.29 W
kg–1) was significantly lower than for walking without
wearing exoskeletons (7.18±0.50 W kg–1) for the
longest step-length condition (Table
1).
The absolute reduction in net metabolic power in powered versus
unpowered walking increased with increasing speed/step length
(P=0.002, THSD; 1.4 L*<0.8 L*, 1.2
L*<0.8 L*; Fig.
5A). At the shortest step lengths (0.8 L*), net
metabolic power was 0.21±0.06 W kg–1 less during
powered versus unpowered walking. At 1.4 L* the reduction
in net metabolic power resulting from mechanical assistance was
0.70±0.12 W kg–1 (
233% more than for shortest
steps). Although reductions in net metabolic power during powered walking were
larger for walking with faster speeds/longer steps, relative changes in net
metabolic power were similar between speeds/step lengths (8–12%
reduction comparing powered to unpowered;
Fig. 5A).
Exoskeleton performance index and ankle joint muscle–tendon `apparent efficiency'
Exoskeleton performance index (i.e. ankle muscle work fraction) increased
with increasing speed/step length (P=0.01, THSD; 1.4
L*>0.8 L*; Fig.
5C). Performance index increased 261% from 0.18±0.12 (ankle
joint muscle–tendon `apparent efficiency'=1.39) during powered 0.8
L* to 0.65±0.10 (ankle joint muscle–tendon `apparent
efficiency'=0.38) during powered 1.4 L*. For powered 1.0
L* and powered 1.2 L* the performance index was
0.41±0.06 (ankle joint muscle–tendon `apparent efficiency'=0.61)
and 0.56±0.10 (ankle joint muscle–tendon `apparent
efficiency'=0.45), respectively.
|
42% greater during unpowered and
56% greater during
powered walking at 1.4 L* when compared with walking at 0.8
L* (P<0.0001; Fig.
6). Medial and lateral gastrocnemius stance phase r.m.s. EMG both
increased (by
47% and 144%, respectively) as step length increased from
0.8 L* to 1.4 L* during unpowered walking
(Fig. 6). For powered walking,
medial gastrocnemius stance phase r.m.s. EMG increased by
36% and lateral
gastrocnemius stance phase r.m.s. EMG increased
135% as speed/step length
increased from 0.8 L* to 1.4 L* (P<0.0001;
Fig. 6).
Subjects altered soleus muscle activation amplitude but not timing during
the stance phase of powered walking when compared to unpowered walking in all
speed/step length conditions. For slow walking with short steps (0.8
L*) soleus stance phase r.m.s. EMG was only
11% lower during
powered versus unpowered walking and the difference was not
significant (0.8 L*, P=0.28;
Fig. 6). At faster speeds with
longer steps, reductions in soleus stance r.m.s. EMG in the powered
versus unpowered mode were larger (
17–20%; 1.0
L*, P=0.002; 1.2 L* and 1.4 L*,
P<0.0001; Fig.
6).
Reductions in both medial and lateral gastrocnemius stance phase r.m.s. EMG
amplitudes during powered versus unpowered walking were smaller
(ranging from
6–15%) than in soleus. For medial gastrocnemius,
stance phase r.m.s. EMG was reduced in powered versus unpowered
walking only at the longest step-length conditions (1.2 L*,
P=0.009; 1.4 L*, P=0.002). In the longest
step-length condition, lateral gastrocnemius stance phase r.m.s. EMG was
reduced during powered walking (1.4 L*, P=0.006;
Fig. 6).
Tibialis anterior muscle recruitment increased with increasing speed/step length (P<0.0001) but was not significantly altered when exoskeletons were powered, except during walking at 1.2 L* (P=0.003; Fig. 6).
Gait kinematics
As expected, step length increased significantly from condition to
condition (P<0.0001) and step period was the same for all
step-length conditions (P=0.13;
Table 2). In addition, subjects
took wider steps (P<0.002) and spent less time in double support
(P<0.0001) as speed/step length increased (P<0.002;
Table 2).
|
There were no significant differences in step period (P>0.47),
step width (P>0.37), or double support time (P>0.27),
between powered and unpowered walking at any step length. Step length was
shorter by
1% during powered walking at 1.0 L*
(P=0.04; Table 2).
| DISCUSSION |
|---|
|
|
|---|
With powered ankle exoskeletons, subjects saved more than three times the
absolute net metabolic power (W kg–1) in the longest (1.4
L*) compared with the shortest (0.8 L*) step-length
condition, but relative reductions in metabolic cost were similar across
speeds/step lengths (8–12%; Fig.
5A). This was because exoskeletons performed a progressively
smaller percentage of ankle muscle–tendon (and total lower-limb
muscle–tendon) average positive mechanical power at faster speeds with
longer step lengths (Figs 3 and
4). Normally the human ankle
muscle–tendon system generates more positive mechanical power during
push-off as walking speed increases by increasing the magnitudes of both the
ankle joint plantar flexor moment and the ankle joint plantar flexor angular
velocity (Craik and Oatis,
1995
; Winter,
1984
). In the present study, although the ankle joint angular
velocity increased near push-off with increasing walking speed/step length,
the peak torque generated by the exoskeletons was very similar across
speeds/step lengths. Increases in exoskeleton average mechanical power were
due almost entirely to increases in ankle joint angular velocity. Exoskeletons
delivered more average mechanical power over the stride with increasing
speed/step length, but they could not match the magnitude of the increases in
the biological ankle joint moment with speed/step length.
The validity of our estimates for both the relative metabolic cost (% of total cost of walking) and the `apparent efficiency' of ankle muscle–tendon positive work depends on a key assumption. We based our calculations on the expectation that changes in subjects' net metabolic power could be attributed to powered exoskeleton mechanical work directly replacing a portion of the ankle muscle–tendon positive mechanical work during push-off. There are a number of factors that could have influenced the validity of this assumption.
Subjects could have increased their total average external mechanical power
in response to exoskeleton mechanical assistance. A higher average external
mechanical power during powered versus unpowered walking would
indicate that subjects used exoskeleton energy to augment rather than replace
biological muscle–tendon positive mechanical work. This would make it
difficult to attribute changes in subjects' net metabolic power to exoskeleton
assistance isolated at the ankle joint rather than to differences in overall
gait characteristics. Net metabolic power during walking increases with
increasing speed/step length (Donelan et
al., 2002a
), step frequency
(Bertram and Ruina, 2001
), and
step width (Donelan et al.,
2001
). We held step frequency constant (using a metronome) and
used treadmill belt speed to vary the step length
(Table 2). Keeping step length
and step frequency constant highly constrains the average external mechanical
power to be similar for unpowered and powered walking. We also measured step
width and found no differences between unpowered and powered walking during
any step-length condition (Table
2).
Even with nearly constant external average mechanical power, subjects still
could have altered the distribution of mechanical power across the joints
between unpowered and powered walking. For example, during powered walking,
increased ankle muscle–tendon positive mechanical power could have been
offset by compensatory muscle–tendon mechanical power at the knee or
hip. In this study, subjects were limited to walking on a motorized treadmill
during powered conditions because of the tethered pneumatic hoses connecting
exoskeleton artificial pneumatic muscles to a pressurized air source. Since
our treadmill was not instrumented with force platforms, we could not compare
joint powers using inverse dynamics for unpowered and powered walking to rule
out redistribution of mechanical power. However, recent results from our lab
indicate no difference in total ankle joint moment patterns when comparing
powered and unpowered exoskeleton walking
(Lewis et al., 2008
).
Our joint kinematic and electromyography data provide good evidence that subjects did not redistribute joint mechanical power as a result of mechanical assistance from the exoskeletons. During powered walking, the ankle joint was slightly more plantar flexed during stance, but the knee and hip joint kinematics were nearly identical for powered and unpowered walking (Fig. 2). Furthermore, in the current study during powered walking, the exoskeletons delivered 32% of the peak ankle muscle–tendon moment and 48% of the peak ankle muscle–tendon mechanical power observed during overground unpowered walking trials. In response, subjects significantly decreased muscle activity in their ankle plantar flexors. Reductions in plantar flexor r.m.s. EMG provides additional support for the idea that the total ankle joint moment (and presumably mechanical power) was maintained between unpowered and powered conditions.
Reductions in soleus r.m.s. EMG (maximum of 20%) were larger than in medial
gastrocnemius (maximum of 13%) and lateral gastrocnemius (maximum of 15%;
Fig. 6). The larger reductions
in soleus are consistent with our previous research using powered exoskeletons
(20–30% reductions) (Cain et al.,
2007
; Gordon and Ferris,
2007
; Sawicki and Ferris,
2008
). It is possible that reductions in the biarticular
gastrocnemius muscles due to powered assistance were smaller than in soleus
because of their functional role in assisting with swing leg initiation
(Meinders et al., 1998
;
Neptune et al., 2001
) or in
transferring mechanical energy from proximal muscle–tendons
(Zajac et al., 2002
). Another
possibility is that the neural mechanism behind soleus muscle activation is
fundamentally different than for medial gastrocnemius and lateral
gastrocnemius (e.g. feedback versus feedforward dominated). Recent
evidence indicates that positive force feedback via type Ib afferents
contributes significantly to soleus muscle activity
(Grey et al., 2007
) and
suggests that reductions in soleus muscle activity during powered
versus unpowered walking may reflect reduced positive force feedback
due to partial unloading of the Achilles' tendon.
Subjects could also have responded to added ankle joint mechanical power by
increasing dorsiflexor activation. Muscle co-activation is an indicator of
simultaneous positive and negative muscle–tendon work and can
significantly increase the metabolic cost of walking
(Winter, 1990
). To address
this possibility, we recorded tibialis anterior (the major ankle dorsiflexor)
surface electromyography, for both unpowered and powered walking at each
speed/step length (Fig. 6).
Tibialis anterior r.m.s. EMG was not elevated during powered walking at any of
the speeds/step lengths we tested. Although we did not measure EMG to check
for co-activation at more proximal joints, our previous research has indicated
no differences in the vastii, rectus femoris, and medial hamstrings between
powered and unpowered ankle exoskeleton walking
(Gordon and Ferris, 2007
).
Finally, we also assumed that mechanical work performed by the net ankle
muscle–tendon moment is an accurate estimate of the underlying
mechanical work performed by the ankle plantar flexor muscles and Achilles'
tendon recoil during the push-off phase of walking. The biarticular
gastrocnemius muscles can theoretically transfer mechanical energy to and from
the ankle joint via the knee and/or hip
(Neptune et al., 2004a
;
Zajac et al., 2002
). However,
according to a computer simulation analysis, during the stance phase of
walking the energy transfers between the knee and ankle do not significantly
confound the accuracy of muscle work estimates based on net moment work
(Prilutsky et al., 1996
). In
addition, co-activation of antagonist muscles could have confounded estimates
of plantar flexor muscle work that are based on net ankle joint mechanical
power. This possibility is unlikely at the ankle joint during the step-to-step
transition of walking. During this phase, medial gastrocnemius and lateral
gastrocnemius each perform positive work at both the ankle and knee while
soleus performs positive work only at the ankle. But because there is no
simultaneous negative work by ankle dorsiflexors (i.e. tibialis anterior)
occurring, the positive mechanical work delivered at the ankle joint by the
triceps surae (soleus, medial and lateral gastrocnemius) is all accounted for
by integrating the net ankle joint mechanical power.
Given the validity of our aforementioned assumptions, our results indicate
that the ankle muscle–tendon system performs positive mechanical work
during walking with remarkably high `apparent efficiency', even when
increasing speed with longer step lengths. Studies indicate that actively
shortening mammalian muscle fibers perform mechanical work with a `muscular
efficiency', on average,
0.25 (0.10–0.34)
(Gaesser and Brooks, 1975
;
Margaria, 1968
;
Ryschon et al., 1997
;
Smith et al., 2005
;
Whipp and Wasserman, 1969
). In
the current study, as walking speed/step length increased, the ankle
muscle–tendon system performed positive mechanical work with lower
`apparent efficiency' (Fig.
5C). But even in the longest step-length condition (1.4
L*), the ankle was more efficient (
0.38) than muscle in
isolation. These results suggest that the Achilles' tendon contributes a
significant portion of the positive work performed by the ankle
muscle–tendon system during walking, at all speeds/step lengths we
studied.
Assuming muscle positive work is performed with
+muscle=0.25 and accounts for the whole metabolic
cost of ankle muscle–tendon work, we can compute an estimate of the
upper limit on the fraction of ankle muscle–tendon positive work
performed by muscles (i.e. exoskeleton performance index=ankle muscle work
fraction=
+muscle/
+ankle)
(Sawicki and Ferris, 2008
).
For walking at 0.8 L* (
1.00 m s–1), we
estimate that plantar flexor muscles perform at most 18% (i.e.
0.25/1.39x100) of the total ankle muscle–tendon positive work. The
Achilles' tendon, therefore, must perform the remaining 82% of the ankle
muscle–tendon positive work by returning previously stored elastic
energy during push-off. Similarly, for walking at 1.4 L* (
1.75
m s–1), we estimate that plantar flexors perform at most 66%
and the Achilles' tendon at least 34% of the total ankle muscle–tendon
positive work.
Our suggestion that Achilles' tendon elastic energy storage and return is
significant during walking is consistent with recent in vivo
ultrasound data from humans (Fukunaga et
al., 2001
; Ishikawa et al.,
2005
; Ishikawa et al.,
2006
; Lichtwark and Wilson,
2006
). Ishikawa et al. showed that during walking at 1.4 m
s–1, the soleus and medial gastrocnemius act nearly
isometrically to support a `catapult action' in the Achilles' tendon
(Ishikawa et al., 2005
).
Negative work is stored in the triceps surae–Achilles' tendon unit over
the first 70% and then released rapidly over the final 30% of the stance phase
(i.e. in the push-off phase of the step-to-step transition). Rough integration
of the reported mechanical power curves for the muscle–tendon unit, and
the tendon only, suggests that the vast majority (>80%) of the positive
work performed by the muscle–tendon during push-off is delivered by the
recoiling Achilles' tendon (Ishikawa et
al., 2005
). Our data from similar walking speeds (1.0
L* and 1.2 L* are
1.25 and
1.5 m
s–1) suggest that the Achilles' tendon performs at least
44–59% of the total ankle muscle–tendon work.
In vivo ultrasound experiments have not examined whether ankle
muscle–tendon dynamics are altered with increasing walking step length
or speed. Hof et al. used indirect methods (force platform and kinematics) to
demonstrate that as walking speed (Hof et
al., 2002
) and step length
(Hof et al., 1983
) increase,
soleus and gastrocnemius muscles perform a larger fraction of the ankle
muscle–tendon work. We estimate from Hof's data that muscles perform
50% of the ankle muscle–tendon positive work at
1.13 m
s–1 and
90% at
1.96 m s–1
(Hof et al., 1983
). These
increases are consistent with our calculations that the maximum ankle
muscle–tendon muscle work fraction increase significantly (from
18%
to
65%) as speed/step length increases from 0.8 L* (
1.00
m s–1) to 1.4 L* (
1.75 m
s–1). Studies using forward dynamics computer simulations of
walking also indicate that that Achilles' tendon supplies a significant amount
of energy during walking and that its relative contribution is lower at higher
speeds (Neptune et al., 2008
;
Neptune et al., 2004b
;
Sasaki and Neptune, 2006
).
Sasaki et al. showed that as simulated walking speed increases from 1.6 m
s–1 to 2.4 m s–1 the fraction of positive
mechanical work performed by soleus muscle fibers increases from
50% to
65% of the total ankle muscle–tendon positive mechanical work
(Sasaki and Neptune,
2006
).
Our results suggest that the relative metabolic cost of ankle muscle–tendon mechanical work increases with speed/step length during walking. The ankle muscle–tendon system provides a significant fraction of the total positive lower-limb muscle–tendon mechanical work that increases slightly with speed/step length (from 34% to 40%; Fig. 4). In addition, ankle plantar flexor muscles perform a larger fraction of the total ankle muscle–tendon positive work at faster speeds/longer step lengths, driving down the `apparent efficiency' of ankle muscle–tendon positive work (from 1.39 to 0.38; Fig. 5C). In short, as speed/step length increases, the ankle muscle–tendon system performs a larger fraction of the total lower-limb muscle–tendon mechanical work with lower `apparent efficiency'. Therefore, the fraction of the total net metabolic cost (W kg–1) of walking due to ankle muscle–tendon positive mechanical work increases at faster speeds/longer step lengths.
As step length increases from 80% to 140% of preferred, we estimate that
the ankle muscle–tendon system consumes
18% more of the total net
metabolic power (W kg–1) during walking. For example, at 0.8
L* the percentage of the summed lower-limb muscle–tendon
(ankle + knee + hip) average positive mechanical power that is delivered by
the ankle muscle–tendon system is 34%. The `apparent efficiency'
lower-limb muscle–tendon positive mechanical work at 0.8 L*
is 0.29 [i.e. lower-limb muscle–tendon average positive mechanical power
(0.83 W kg–1)/net metabolic power (2.86 W
kg–1)=0.29]. The `apparent efficiency' of only the ankle
muscle–tendon positive mechanical work is 1.39. Thus, the percentage of
the total net metabolic power (W kg–1) due to ankle
muscle–tendon positive work is 34%x0.29/1.39=7%. Similar
calculations can be carried out for the other speed/step-length conditions.
The percentage of muscle–tendon average positive mechanical power from
the ankle is 36%, 40% and 39% for the 1.0 L*–1.4
L* step-length conditions. Over the same range of step lengths, the
`apparent efficiency' of total lower-limb muscle–tendon positive
mechanical work is 0.31, 0.29 and 0.23 and the ankle muscle–tendon
`apparent efficiency' is 0.61, 0.45 and 0.38. Thus, we estimate the ankle
muscle–tendon system consumes 18%, 26% and 24% of the total net
metabolic power (W kg–1) for walking as speed/step length
increases from preferred (1.25 m s–1) to 140% preferred (1.75
m s–1).
The metabolic cost of walking may be dominated by positive muscle work at
the proximal joints (i.e. hip and knee). Our results suggest that humans can
save a significant amount of metabolic energy at the distal ankle joint by
using previously stored Achilles' tendon elastic energy to partially power
push-off during the step-to-step transition. As a result, in the worst case
(i.e. 1.2 L*), the ankle muscle–tendon system consumes 26% of
the total net metabolic energy but produces 40% of the total positive
mechanical work during walking. So where is the remaining 74% of the metabolic
energy spent? Keeping along the lines of lower-limb muscle–tendon work,
we feel that the hip joint muscle–tendon system might consume a large
portion of unaccounted metabolic energy. The hip supplies positive mechanical
work on par with the ankle (
30–40% of the total lower-limb
muscle–tendon positive work). But the morphology (i.e. long muscle
fibers and short or no tendons) of the human hip may significantly reduce its
`apparent efficiency' to perform positive mechanical work. It is likely that
the positive work supplied by the hip muscle–tendon system is performed
almost exclusively by active muscle shortening rather than passive tendon
recoil. At the preferred step length, if the combined knee/hip positive
mechanical work (64% of the total) accounts for the remaining 82% of the
metabolic cost of walking then we estimate the combined knee/hip
muscle–tendon `apparent efficiency' is
0.24.
Implications and future research
From a basic science perspective, our long-term goal is to establish a
joint-based relationship between the mechanics and energetics of human
locomotion. We hope to be able to approximately explain the metabolic cost of
human walking as the sum of the metabolic cost of muscle–tendons
performing positive work at each of the lower-limb joints (ankle + knee +
hip). With measurements of average positive mechanical power and the `apparent
efficiency' of positive mechanical work for muscle–tendons spanning each
joint this should be possible. Therefore, future studies should examine the
`apparent efficiency' of the hip and knee muscle–tendons under various
walking conditions.
The importance of elastic energy storage and return in the Achilles' tendon
during walking sheds light on an alternative way to view ankle exoskeleton
mechanical assistance. Even if ankle plantar flexors perform little muscular
work during human walking, they must still act like struts, producing the
forces necessary to support body weight and series tendon elastic energy
storage and return (Griffin et al.,
2003
; Pontzer,
2005
). This may be a useful perspective to take when trying to
understand changes in net metabolic power that result from powering lower-limb
joints where elastic energy cycling is important (i.e. the ankle). For
example, regardless of the work that exoskeleton artificial muscles perform,
the torque that they develop about the ankle reduces the forces required from
biological ankle plantar flexors. Although we did not use net ankle joint
muscle–tendon moment data to estimate reductions in muscle forces, it
should be possible to calculate an `apparent economy' of ankle plantar flexor
force production to gain insight into the relative metabolic costs of
generating muscle force versus performing muscle work during human
walking.
Considerable effort has been placed on developing assistive devices (i.e.
exoskeletons and prostheses) designed to reduce the metabolic cost of walking
(Guizzo and Goldstein, 2005
).
From an applied science perspective, our results suggest that metabolic energy
savings are likely to be much more modest than expected when using an
exoskeleton to supplant muscle–tendon work at distal, compliant joints.
Instead, powering joints where active muscle rather than recoiling tendon
performs most of the positive mechanical work (i.e. powering the less
efficient joints) may lead to larger reductions in metabolic cost
(Ferris et al., 2007
).
Furthermore, passive devices designed to reduce isometric muscle forces during
periods of tendon stretch and recoil could also be useful at relatively
elastic joints (i.e. ankle).
LIST OF ABBREVIATIONS
+ankle
+muscle
| Footnotes |
|---|
Supplementary material available online at http://jeb.biologists.org/cgi/content/full/212/1/21/DC1
| References |
|---|
|
|
|---|
Asmussen, E. and Bonde-Petersen, F. (1974). Apparent efficiency and storage of elastic energy in human muscles during exercise. Acta Physiol. Scand. 92,537 -545.[Medline]
Bertram, J. E. and Ruina, A. (2001). Multiple walking speed-frequency relations are predicted by constrained optimization. J. Theor. Biol. 209,445 -453.[CrossRef][Medline]
Cain, S. M., Gordon, K. E. and Ferris, D. P. (2007). Locomotor adaptation to a powered ankle-foot orthosis depends on control method. J. Neuroeng. Rehabil. 4, 48.[CrossRef][Medline]
Craik, R. L. and Oatis, C. A. (1995). Gait Analysis: Theory and Application. St Louis, MO: Mosby.
Doke, J., Donelan, J. M. and Kuo, A. D. (2005).
Mechanics and energetics of swinging the human leg. J. Exp.
Biol. 208,439
-445.
Donelan, J. M., Kram, R. and Kuo, A. D. (2001).
Mechanical and metabolic determinants of the preferred step width in human
walking. Proc. R. Soc. Lond., B, Biol. Sci.
268,1985
-1992.
Donelan, J. M., Kram, R. and Kuo, A. D.
(2002a). Mechanical work for step-to-step transitions is a major
determinant of the metabolic cost of human walking. J. Exp.
Biol. 205,3717
-3727.
Donelan, J. M., Kram, R. and Kuo, A. D. (2002b). Simultaneous positive and negative external mechanical work in human walking. J. Biomech. 35,117 -124.[CrossRef][Medline]
Eng, J. J. and Winter, D. A. (1995). Kinetic analysis of the lower limbs during walking: what information can be gained from a three-dimensional model? J. Biomech. 28,753 -758.[CrossRef][Medline]
Ferris, D. P., Czerniecki, J. M. and Hannaford, B. (2005). An ankle-foot orthosis powered by artificial pneumatic muscles. J. Appl. Biomech. 21,189 -197.[Medline]
Ferris, D. P., Gordon, K. E., Sawicki, G. S. and Peethambaran, A. (2006). An improved powered ankle-foot orthosis using proportional myoelectric control. Gait Posture 23,425 -428.[CrossRef][Medline]
Ferris, D. P., Sawicki, G. S. and Daley, M. A. (2007). A physiologist's perspective on robotic exoskeletons for human locomotion. Int. J. HR 4, 507-528.[Medline]
Fukunaga, T., Kubo, K., Kawakami, Y., Fukashiro, S., Kanehisa,
H. and Maganaris, C. N. (2001). In vivo behaviour of
human muscle tendon during walking. Proc. R. Soc. Lond., B, Biol.
Sci. 268,229
-233.
Gaesser, G. A. and Brooks, G. A. (1975).
Muscular efficiency during steady-rate exercise: effects of speed and work
rate. J. Appl. Physiol.
38,1132
-1139.
Gitter, A., Czerniecki, J. M. and DeGroot, D. M. (1991). Biomechanical analysis of the influence of prosthetic feet on below-knee amputee walking. Am. J. Phys. Med. Rehabil. 70,142 -148.[CrossRef][Medline]
Gordon, K. E. and Ferris, D. P. (2007). Learning to walk with a robotic ankle exoskeleton. J. Biomech. 40,2636 -2644.[CrossRef][Medline]
Gordon, K. E., Sawicki, G. S. and Ferris, D. P. (2006). Mechanical performance of artificial pneumatic muscles to power an ankle-foot orthosis. J. Biomech. 39,1832 -1841.[CrossRef][Medline]
Grey, M. J., Nielsen, J. B., Mazzaro, N. and Sinkjaer, T.
(2007). Positive force feedback in human walking. J.
Physiol. 581,99
-105.
Griffin, T. M., Roberts, T. J. and Kram, R.
(2003). Metabolic cost of generating muscular force in human
walking: insights from load-carrying and speed experiments. J.
Appl. Physiol. 95,172
-183.
Guizzo, E. and Goldstein, H. (2005). The rise of the body bots. IEEE Spectrum 42, 50-56.
Hansen, A. H., Childress, D. S., Miff, S. C., Gard, S. A. and Mesplay, K. P. (2004). The human ankle during walking: implications for design of biomimetic ankle prostheses. J. Biomech. 37,1467 -1474.[CrossRef][Medline]
Hof, A. L., Geelen, B. A. and Van den Berg, J. (1983). Calf muscle moment, work and efficiency in level walking: role of series elasticity. J. Biomech. 16,523 -537.[CrossRef][Medline]
Hof, A. L., Van Zandwijk, J. P. and Bobbert, M. F. (2002). Mechanics of human triceps surae muscle in walking, running and jumping. Acta Physiol. Scand. 174, 17-30.[CrossRef][Medline]
Ishikawa, M., Komi, P. V., Grey, M. J., Lepola, V. and
Bruggemann, G. P. (2005). Muscle-tendon interaction and
elastic energy usage in human walking. J. Appl.
Physiol. 99,603
-608.
Ishikawa, M., Pakaslahti, J. and Komi, P. V. (2006). Medial gastrocnemius muscle behavior during human running and walking. Gait Posture. 25,380 -384.[CrossRef][Medline]
Kuo, A. D. (2002). Energetics of actively powered locomotion using the simplest walking model. J. Biomech. Eng. 124,113 -120.[CrossRef][Medline]
Kuo, A. D., Donelan, J. M. and Ruina, A. (2005). Energetic consequences of walking like an inverted pendulum: step-to-step transitions. Exerc. Sport Sci. Rev. 33,88 -97.[CrossRef][Medline]
Lewis, C., Kao, P. and Ferris, D. P. (2008). Invariant ankle joint moment patterns with plantar flexor assistance from a powered ankle orthosis. North American Conference on Biomechanics, August 5-9, Ann Arbor, Michigan, USA.
Lichtwark, G. A. and Wilson, A. M. (2006).
Interactions between the human gastrocnemius muscle and the Achilles tendon
during incline, level and decline locomotion. J. Exp.
Biol. 209,4379
-4388.
Lichtwark, G. A. and Wilson, A. M. (2007). Is Achilles tendon compliance optimised for maximum muscle efficiency during locomotion? J. Biomech. 40,1768 -1775.[CrossRef][Medline]
Lichtwark, G. A., Bougoulias, K. and Wilson, A. M. (2007). Muscle fascicle and series elastic element length changes along the length of the human gastrocnemius during walking and running. J. Biomech. 40,157 -164.[CrossRef][Medline]
Margaria, R. (1968). Positive and negative work performances and their efficiencies in human locomotion. Int. Z. Angew. Physiol. 25,339 -351.[Medline]
Meinders, M., Gitter, A. and Czerniecki, J. M. (1998). The role of ankle plantar flexor muscle work during walking. Scand. J. Rehabil. Med. 30, 39-46.[CrossRef][Medline]
Neptune, R. R., Kautz, S. A. and Zajac, F. E. (2001). Contributions of the individual ankle plantar flexors to support, forward progression and swing initiation during walking. J. Biomech. 34,1387 -1398.[CrossRef][Medline]
Neptune, R. R., Zajac, F. E. and Kautz, S. A. (2004a). Muscle force redistributes segmental power for body progression during walking. Gait Posture 19,194 -205.[CrossRef][Medline]
Neptune, R. R., Zajac, F. E. and Kautz, S. A. (2004b). Muscle mechanical work requirements during normal walking: the energetic cost of raising the body's center-of-mass is significant. J. Biomech. 37,817 -825.[CrossRef][Medline]
Neptune, R. R., Sasaki, K. and Kautz, S. A. (2008). The effect of walking speed on muscle function and mechanical energetics. Gait Posture 28,135 -143.[CrossRef][Medline]
Pontzer, H. (2005). A new model predicting
locomotor cost from limb length via force production. J. Exp.
Biol. 208,1513
-1524.
Prilutsky, B. I., Petrova, L. N. and Raitsin, L. M. (1996). Comparison of mechanical energy expenditure of joint moments and muscle forces during human locomotion. J. Biomech. 29,405 -415.[CrossRef][Medline]
Ruina, A., Bertram, J. E. and Srinivasan, M. (2005). A collisional model of the energetic cost of support work qualitatively explains leg sequencing in walking and galloping, pseudo-elastic leg behavior in running and the walk-to-run transition. J. Theor. Biol. 237,170 -192.[CrossRef][Medline]
Ryschon, T. W., Fowler, M. D., Wysong, R. E., Anthony, A. and
Balaban, R. S. (1997). Efficiency of human skeletal muscle in
vivo: comparison of isometric, concentric, and eccentric muscle action.
J. Appl. Physiol. 83,867
-874.
Sasaki, K. and Neptune, R. R. (2006). Muscle mechanical work and elastic energy utilization during walking and running near the preferred gait transition speed. Gait Posture 23,383 -390.[CrossRef][Medline]
Sawicki, G. S. and Ferris, D. P. (2008).
Mechanics and energetics of level walking with powered ankle exoskeletons.
J. Exp. Biol. 211,1402
-1413.
Sawicki, G. S., Gordon, K. E. and Ferris, D. P. (2005). Powered lower limb orthoses: applications in motor adaptation and rehabilitation. In IEEE International Conference on Rehabilitation Robotics. Chicago, IL: IEEE.
Smith, N. P., Barclay, C. J. and Loiselle, D. S. (2005). The efficiency of muscle contraction. Prog. Biophys. Mol. Biol. 88,1 -58.[CrossRef][Medline]
Whipp, B. J. and Wasserman, K. (1969).
Efficiency of muscular work. J. Appl. Physiol.
26,644
-648.
Winter, D. A. (1984). Kinematic and kinetic patterns in human gait: variability and compensating effects. Hum. Mov. Sci. 3,51 -76.[CrossRef]
Winter, D. A. (1990). Biomechanics and Motor Control of Human Movement. New York: John Wiley.
Zajac, F. E., Neptune, R. R. and Kautz, S. A. (2002). Biomechanics and muscle coordination of human walking. Part I: introduction to concepts, power transfer, dynamics and simulations. Gait Posture 16,215 -232.[CrossRef][Medline]
![]()
CiteULike
Complore
Connotea
Del.icio.us
Digg
Reddit
Technorati
Twitter What's this?
This article has been cited by other articles:
![]() |
G. S. Sawicki and D. P. Ferris Mechanics and energetics of incline walking with robotic ankle exoskeletons J. Exp. Biol., January 1, 2009; 212(1): 32 - 41. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||