951
ORIGINAL ARTICLE
Metabolic and Biomechanical Effects of Velocity and Weight
Support Using a Lower-Body Positive Pressure Device
During Walking
Alena M. Grabowski, PhD
ABSTRACT. Grabowski AM. Metabolic and biomechanical
effects of velocity and weight support using a lower-body
positive pressure device during walking. Arch Phys Med Rehabil 2010;91:951-7.
Objectives: To determine how changes in velocity and
weight support affect metabolic power and ground reaction
forces (GRFs) during walking using a lower-body positive
pressure (LBPP) device. To find specific velocity and weight
combinations that require similar aerobic demands but different
peak GRFs.
Design: Repeated measures.
Setting: University research laboratory.
Participants: Healthy volunteer subjects (N⫽10).
Interventions: Subjects walked 1.00, 1.25, and 1.50m/s on a
force-measuring treadmill at normal weight (1.0 body weight
[BW]) and at several fractions of BW (.25, .50, .75, .85 BW). The
treadmill was enclosed within an LBPP apparatus that supported
BW.
Main Outcome Measures: Metabolic power, GRFs, and
stride kinematics.
Results: At faster velocities, peak GRFs and metabolic
demands were greater. In contrast, walking at lower fractions
of BW attenuated peak GRFs and reduced metabolic demand
compared with normal weight walking. Many combinations of
velocity and BW resulted in similar aerobic demands, yet
walking faster with weight support lowered peak GRFs compared with normal weight walking.
Conclusions: Manipulating velocity and weight using an
LBPP device during treadmill walking can reduce force yet
maintain cardiorespiratory demand. Thus, LBPP treadmill
training devices could be highly effective for rehabilitation
after orthopedic injury and/or orthopedic procedures.
Key Words: Biomechanics; Locomotion; Rehabilitation;
Weightlessness.
© 2010 by the American Congress of Rehabilitation
Medicine
OME PEOPLE MAY NOT be able to walk safely at their
S
full BW after orthopedic injury and/or surgery. Thus, BW
support treadmill training devices have been employed for
orthopedic rehabilitation.1-6 By supporting BW, these devices
From the Department of Integrative Physiology, University of Colorado,
Boulder, CO.
Supported by Alter-G, Inc.
No commercial party having a direct financial interest in the results of the research
supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated.
Reprint requests to Alena M. Grabowski, PhD, Massachusetts Institute of
Technology, Room E14-374M, 75 Amherst St, Cambridge, MA 02139, e-mail:
alenag@media.mit.edu.
0003-9993/10/9106-00808$36.00/0
doi:10.1016/j.apmr.2010.02.007
reduce biomechanical risks by decreasing the forces acting on the
musculoskeletal system so that walking movements can be safely
repeated and the quality of movement improved, potentially allowing patients to return to walking sooner after injury or surgery.
However, if patients walk at slow velocities using BW support,
their cardiovascular fitness may decline because of the lower
aerobic demands of the task. Thus, it is important to determine
how changes in either velocity or weight support affect metabolic
demand and GRFs during walking, and to determine combinations
of velocity and weight support that are safe, yet yield similar
aerobic demands to normal weight walking.
Many previous studies show that when humans walk at normal
weight, metabolic demand increases with velocity.7-9 The greater
metabolic demand of faster walking is likely attributed to
increases in stride frequency, increases in mechanical power,
and generation of greater GRF over shorter periods of ground
contact.10-12 Other studies have shown that when a portion of
BW is supported using a weight suspension system, less metabolic power is required to walk.13,14 The relationship between
metabolic power and BW is not directly proportional, however.
As BW is supported, there is only a subtle linear decrease in
metabolic power.13,14 The slight metabolic power reduction
while walking at a smaller fraction of BW likely results from
the attenuation of average and/or peak vertical GRF.13,15 More
specifically, the metabolic power required to generate force for
supporting BW comprises approximately 28% of the overall
metabolic power required to walk 1.25m/s.13 However, it is not
known whether BW support comprises the same percentage of
the overall metabolic power to walk at different velocities.
Although the separate effects of velocity and weight support
have been examined by prior studies, the combined effects of
velocity and weight support, specifically using an LBPP device, have not been systematically investigated.
Methods other than LBPP have been employed previously to
support BW during walking, including harness suspension systems and water immersion. Harness suspension systems are
beneficial because a purely vertical force can be applied to the
person, and the independent effects of supporting BW can be
addressed.13,15,16 However, harness suspension systems may
not be applicable for extended rehabilitation and training use
because they can cause discomfort and impede circulation.
Water immersion is commonly used as a rehabilitation tool.3-6
However, the drag forces experienced during water exercise act
in opposition to movement and cause significant changes in
walking velocity, gait timing, joint kinematics, joint kinetics,
and muscle activity compared with overground walking.17-20
List of Abbreviations
BW
GRF
LBPP
NMP
body weight
ground reaction force
lower-body positive pressure
net metabolic power
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EFFECTS OF VELOCITY AND WEIGHT SUPPORT DURING WALKING, Grabowski
Fig 1. (A) Schematic depiction of the LBPP device, (B) LBPP device.
LBPP devices do not apply drag forces to the legs and may be
advantageous because they allow kinematic gait patterns similar to normal weight overground walking,21 a normative range
of walking velocities, and a decrease in the forces transmitted
by the legs.21 Additionally, LBPP devices are comfortable, do
not impede circulation, can be used over extended periods, and
are adjustable. Thus, LBPP devices could be very effective for
orthopedic rehabilitation.
The purpose of this study was to quantify the separate and
combined effects of walking velocity and BW support on
metabolic power demand and peak vertical GRF using an
LBPP device. Based on results from previous studies, I expected metabolic power to increase with velocity and decrease
with the fraction of BW. Further, I expected peak vertical GRF
to increase with velocity but decrease with the fraction of BW.
Finally, compared with walking slowly at normal weight, I
predicted that combinations of faster walking velocities with
BW support would demand the same metabolic power but have
the benefit of lower peak vertical GRF.
METHODS
Subjects
Ten healthy subjects (5 men, 5 women; mean weight ⫾ SD,
66.4⫾12.1kg; mean age ⫾ SD, 32⫾7y) volunteered and gave
informed written consent according to the University of Colorado Human Research Committee approved protocol. All subjects had prior experience walking on a treadmill and completed all experimental trials at the University of Colorado,
Boulder, Locomotion Laboratory.
Protocol
Subjects walked on a force-measuring treadmill enclosed in
an LBPP devicea while I measured metabolic rates, stance
phase durations, and GRF. Each subject completed 17 trials
over 2 experimental sessions: 9 trials during session 1 and 8
trials during session 2. Each trial was 7 minutes long with at
least 3 minutes of rest between trials. The rest period and
low-to-moderate level of activity during walking trials were
adequate to prevent fatigue.13,22 Subjects began each session
Arch Phys Med Rehabil Vol 91, June 2010
with a standing trial at 1.0 BW. The order of the remaining
trials was randomly assigned so that subjects walked at 3 velocities (1.0, 1.25, 1.5m/s) and 5 fractions of BW (.25, .50, .75, .85,
1.0 BW).
BW Support
I used an LBPP devicea combined with a force-measuring
treadmill23 to support BW during walking (fig 1). The LBPP
device was provided by Alter-G, Inc, and is based on Alter-G’s
Anti-Gravity Treadmill,a previously called the G-trainer,22 and
on the research device designed by Whalen et al.24 The airtight
chamber of the LBPP device contained an aperture that surrounded the subject’s waist. Each subject wore neoprene shorts
that included a kayak-style spray skirt that zipped into the
aperture. This interface created an airtight seal near the subject’s waist. Thus, a small increase in air pressure within the
chamber (less than 10.3kPa) applied a lifting force to the user’s
entire lower body and could support up to 80% of BW.
Before each trial, I adjusted the air pressure inside the
chamber to apply the appropriate lifting force to each subject.
During each trial, the air pressure in the chamber was constantly adjusted via a built-in pressure feedback system to
maintain a near-constant lifting force. Thus, by regulating air
pressure, the LBPP device accommodated center of mass
movements throughout each trial. The air pressure in the chamber (and thus the amount of weight support) fluctuated within
a stride by only 3%, 4%, 4%, and 5% of the mean air pressure
set for .25, .50, .75, and .85 BW trials, respectively.
Metabolic Rate
Rates of oxygen consumption and carbon dioxide production were recorded and averaged during minutes 4 to 6 of
each 7-minute trial using an open-circuit respirometry
system.11,13,22,b The trial length allowed me to capture steadystate metabolic rates. I calculated gross metabolic power in
watts per kilogram of normal body mass using a standard
equation.25 Then I determined net metabolic power by subtracting standing metabolic power from gross metabolic power
during walking. Respiratory exchange ratios were less than 1.0
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EFFECTS OF VELOCITY AND WEIGHT SUPPORT DURING WALKING, Grabowski
Table 1: GMP and NMP
Velocity (m/s)
BW (Fraction)
GMP (W/kg)
NMP (W/kg)
% NMP (100%⫽1.0 BW)
Stand
1.00
1.00
1.00⫾0.04
0.85⫾0.07*
0.72⫾0.03*
0.49⫾0.03*
0.27⫾0.04*
1.00⫾0.04
0.83⫾0.07*
0.73⫾0.02*
0.48⫾0.04*
0.26⫾0.05*
1.00⫾0.04
0.87⫾0.04*
0.73⫾0.05*
0.49⫾0.05*
0.27⫾0.05*
1.60⫾0.19
4.01⫾0.55
3.71⫾0.53*
3.67⫾0.30
3.34⫾0.56*
2.93⫾0.48*
4.58⫾0.38†
3.93⫾0.43*
4.29⫾0.53†
3.59⫾0.67*†
3.32⫾0.66*†
4.93⫾0.25†
4.72⫾0.74†
4.45⫾0.50*
4.10⫾0.75*†
3.57⫾0.74*
0
2.39⫾0.41
2.14⫾0.39*
2.08⫾0.28
1.73⫾0.42*
1.29⫾0.38*
2.94⫾0.36†
2.37⫾0.31*
2.68⫾0.45†
2.02⫾0.61*†
1.72⫾0.45*†
3.33⫾0.26†
3.13⫾0.70†
2.81⫾0.41*
2.51⫾0.61*†
1.97⫾0.59*
0
100
90.1⫾11.4*
88.8⫾17.8
75.6⫾19.3*
54.6⫾15.5*
100
81.9⫾17.1*
91.8⫾14.2
70.3⫾22.5*
59.1⫾15.2*
100
94.4⫾20.7
85.1⫾16.0*
76.1⫾20.9*
60.3⫾22.4*
1.25
1.50
NOTE. Gross metabolic power (GMP), NMP, and percentage of NMP compared with normal weight walking (% NMP) for all conditions of
velocity and BW. Values are mean ⫾ SD.
*Significant difference from 1.0 BW at the same velocity (P⬍.05).
†
Significant difference from the velocity .25m/s slower at the same fraction of BW (P⬍.05).
for all subjects during all trials, indicating that metabolic energy was primarily supplied by oxidative metabolism.
Force-Measuring Treadmill
A custom-made single-belt motorized force treadmill23,c was
used to measure GRF, and footswitchesd were used to detect
stance phases from each foot during all trials. Between minutes 4
to 5 of each trial, I simultaneously collected 15 seconds of GRF
and foot switch data at 1000Hz. All data were processed using
Matlab.e First, I filtered raw GRF and footswitch data with a
fourth-order recursive, zero phase-shift Butterworth low-pass filter
with a 15-Hz cutoff frequency. Using the filtered data from the
footswitches, I determined heel-strikes and toe-offs and used these
instances to compute foot contact time. Stride time was defined as
the time from heel-strike to subsequent heel-strike of the same
foot. Stride frequency was calculated as the inverse of stride time.
Using both the vertical GRF and foot-switch data, I determined
the average fraction of BW and the first (P1) and second (P2) peak
vertical GRF for 10 strides a trial according to the procedure of
Davis and Cavanagh.26
The LBPP device’s positive air pressure provided a consistent and substantial lifting force to the subjects. The air pressure in the chamber was set and adjusted while subjects stood
in place on the force treadmill before each trial began, but as
subjects began walking, they settled into the neoprene short/
spray skirt interface. This slight shift in body position relative
to the pressurized chamber probably caused the small changes
in the actual fraction of BW support compared with the fraction
of BW support I set prior to each trial. Therefore, average BW
values were not precisely .25, .50, .75, and .85 for all conditions (tables 1 and 2). I have accounted for these small BW
changes and report the actual fractions of BW in my overall
results.
Table 2: Kinematic and Kinetic Variables
Velocity (m/s)
BW (fraction)
P1 (N)
P2 (N)
SF (Hz)
tc (s)
1.00
1.00⫾0.04
0.85⫾0.07*
0.72⫾0.03*
0.49⫾0.03*
0.27⫾0.04*
1.00⫾0.04
0.83⫾0.07*
0.73⫾0.02*
0.48⫾0.04*
0.26⫾0.05*
1.00⫾0.04
0.87⫾0.04*
0.73⫾0.05*
0.49⫾0.05*
0.27⫾0.05*
692.5⫾152.1
583.8⫾93.1*
506.6⫾90.1*
384.0⫾65.1*
237.5⫾59.8*
731.7⫾131.2†
613.0⫾124.2*
548.7⫾101.1*†
409.1⫾86.5*
279.6⫾68.8*
798.2⫾132.1†
709.5⫾134.3*†
615.5⫾113.6*†
457.4⫾108.1*†
344.5⫾72.3*†
731.9⫾175.4
627.3⫾122.1*
543.3⫾123.7*
378.0⫾92.5*
219.2⫾66.6*
741.9⫾169.3
617.3⫾134.0*
558.0⫾134.3*
368.2⫾99.5*
215.8⫾48.0*
736.3⫾168.4
642.8⫾147.7*
547.8⫾142.7*
377.6⫾108.9*
214.9⫾57.9*
0.86⫾0.05
0.87⫾0.05
0.86⫾0.06
0.83⫾0.05
0.80⫾0.04*
0.96⫾0.05†
0.96⫾0.05†
0.95⫾0.05†
0.91⫾0.06†
0.91⫾0.10†
1.03⫾0.05†
1.03⫾0.06†
1.01⫾0.09†
1.02⫾0.09†
0.96⫾0.08*†
0.73⫾0.05
0.71⫾0.04
0.70⫾0.05*
0.69⫾0.05*
0.68⫾0.04*
0.65⫾0.04†
0.63⫾0.04*†
0.63⫾0.04*†
0.64⫾0.04†
0.59⫾0.12
0.61⫾0.03†
0.59⫾0.03*†
0.60⫾0.06
0.58⫾0.04*†
0.54⫾0.10
1.25
1.50
NOTE. First (P1) and second (P2) peak vertical ground reaction forces, stride frequencies (SF), and contact times (tc) for all conditions of
velocity and BW. Values are mean ⫾ SD.
*Significant difference from 1.0 BW at the same velocity (P⬍.05).
†
Significant difference from the velocity .25m/s slower at the same fraction of BW (P⬍.05).
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EFFECTS OF VELOCITY AND WEIGHT SUPPORT DURING WALKING, Grabowski
Statistics
I performed repeated-measures analysis of variance and Tukey
honestly significant difference follow-up tests when warranted to
compare gross metabolic power, net metabolic power, percent of
net metabolic power, contact time, stride frequency, and peak
vertical GRF (P⬍.05). A priori, power calculations showed that
10 subjects would provide greater than 90% statistical power to
detect a 5% difference with alpha equal to .05 in all variables
based on previous metabolic, kinematic, and kinetic data from
normal weight walking.13,27 Linear least-squares regression
equations were used to compare separately velocity and BW
with net metabolic power, percent of net metabolic power, and
peak vertical GRF. Then, multiple linear regressions were used
to determine the combined effects of velocity and BW on net
metabolic power and peak vertical GRF. All statistical analyses
were performed using JMP statistical software.f
RESULTS
As subjects walked faster and BW was kept the same, they
incurred greater metabolic demands (fig 2; see table 1). When
subjects walked at the same velocity and BW was reduced,
metabolic power was reduced (see fig 3; see table 1). At each
velocity, net metabolic power decreased linearly but in less
than direct proportion to BW (see fig 3; see table 1). The linear
least-squares regression equations showing the relationship
between NMP and BW for each velocity are listed in the figure
3 legend. The multiple linear regression equation describing
NMP as a combined function of velocity (v) and BW was
NMP ⫽ (1.59 ⫻ v) ⫹ (1.59 ⫻ BW) ⫺ 0.72 (R2 ⫽ .57)
where NMP is in watts per kilogram, v is in meters per second,
and BW is the fraction of body weight (fig 4). For example,
while walking at 1.0 BW, a 20% decrease in velocity from 1.50
to 1.20m/s decreases net metabolic power by approximately
14.7%. While walking at 1.50m/s, a 20% decrease in BW from
1.0 to 0.80 BW decreases net metabolic power by approximately 9.8%.
Fig 2. Net metabolic power for 1.00, 1.25, and 1.50m/s at different
fractions of BW. Values are mean ⴞ SEM. Abbreviation: SEM, standard error of the mean.
Arch Phys Med Rehabil Vol 91, June 2010
Fig 3. Net metabolic power for 1.00, 1.25, and 1.50m/s at different
fractions of BW. Values are mean ⴞ SEM. The linear regression
equations that describe NMP in terms of BW at each velocity are as
follows: 1.00m/s: NMPⴝ(1.36 ⴛ BW)ⴙ.996, (R2ⴝ.46); 1.25m/s:
NMPⴝ(1.58 ⴛ BW)ⴙ1.28, (R 2 ⴝ.47); 1.50m/s: NMPⴝ(1.74 ⴛ
BW)ⴙ1.56, (R2ⴝ.43). Abbreviation: SEM, standard error of the mean.
At all fractions of BW, as subjects walked faster, the first
peak vertical GRF (P1) increased, but P2 did not change (fig 5;
see table 2). Subjects achieved faster velocities at all fractions
of BW by increasing stride frequency and stride length (see
table 2). At all velocities, both P1 and P2 decreased linearly
and proportionally with BW (see fig 5; see table 2). The linear
least-squares regression equations showing how P1 and P2
changed with BW for each velocity are listed in the figure 5
legend. There were no significant changes in stride frequency
during weight-supported compared with normal weight walking (P⬎.05) with the exception of 0.25 BW at 1.0 and 1.5m/s.
Contact time was only slightly shorter at smaller fractions of
BW (see table 2). The multiple linear regression equation
describing P1 as a combined function of v and BW was
Fig 4. Contour plot of NMP in W/kg as a function of v and the
fraction of BW. The plot represents mean NMP described by the
multiple linear regression equation NMPⴝ(1.59 ⴛ v) ⴙ (1.59 ⴛ
BW) – .72.
EFFECTS OF VELOCITY AND WEIGHT SUPPORT DURING WALKING, Grabowski
955
Fig 5. (A) First (P1) and (B) second (P2) peak vertical GRFs for 1.00, 1.25, and 1.50m/s at different fractions of BW. Values are mean ⴞ SEM.
Inset shows a typical GRF trace during the stance phase with P1 and P2 indicated. The linear regression equations that describe the peak
vertical GRFs in terms of BW at each velocity are as follows: 1.00m/s: P1ⴝ(610 ⴛ BW)ⴙ62, (R2ⴝ.76), P2ⴝ(697 ⴛ BW)ⴙ21, (R2ⴝ.72); 1.25m/s:
P1ⴝ(608 · BW)ⴙ107, (R2ⴝ.74), P2ⴝ(717 ⴛ BW)ⴙ18, (R2ⴝ.74); 1.50m/s: P1ⴝ(632 ⴛ BW)ⴙ153, (R2ⴝ.73), P2ⴝ(706 ⴛ BW)ⴙ22, (R2ⴝ.70).
Abbreviation: SEM, standard error of the mean.
P1 ⫽ (202.9 ⫻ v) ⫹ (619.5 ⫻ BW) ⫺ 145.9 (R2 ⫽ .57)
where P1 is in newtons, v is in meters per second, and BW is
the fraction of body weight (fig 6).
Many velocity and BW combinations required the same
metabolic power, yet walking faster with lower BW resulted in
reduced peak vertical GRF. To determine equivalent metabolic
demands, I used the multiple linear regression equation for net
metabolic power. For example, while walking 1.25m/s at 1.0
BW, net metabolic power equals 2.85W/kg. The same metabolic power is required when walking 1.50m/s at 0.79 BW. I
calculated P1 and P2 using the linear regression equations that
describe peak vertical GRF as a function of BW for each
Fig 6. Contour plot of the first peak vertical ground reaction force
(P1) in N as a function of v and the fraction of BW. The plot
represents mean P1 force described by the multiple linear regression equation P1ⴝ(202.9 ⴛ v)ⴙ(619.5 ⴛ BW)–145.9, (R2ⴝ.75).
velocity (see fig 5 legend). Walking 1.25m/s at 1.0 BW results
in P1 and P2 equal to 715N and 735N, respectively, and
walking 1.5m/s at .79 BW results in P1 and P2 equal to 627N
and 552N, respectively. Thus, compared with normal weight
walking, walking faster with BW support incurs the same metabolic demand, yet decreases P1 by ⬃12% and P2 by ⬃25%.
DISCUSSION
The reductions in metabolic power caused by LBPP differ
from previous results that have used harness suspension systems to support BW.13,14 For example, Farley and McMahon14
found that compared with walking 1.0m/s at normal BW, net
metabolic power was 33% lower while walking 1.0m/s at 0.25
BW, whereas with the present system, net metabolic power was
45% lower (see table 1). Grabowski et al,13 using a slightly
different harness suspension system, found that compared with
walking 1.25m/s at normal BW, net metabolic power was 21%
lower at 0.25 BW, whereas in the present study, net metabolic
power was 41% lower (see table 1). These metabolic disparities are likely a result of differences between the weight
support devices. Although the LBPP device primarily provides vertical support, it inevitably provides a small amount of
horizontal and lateral support.22
During walking, a horizontal assistive force of only 10%
BW could reduce metabolic power by as much as 50%,28 and
a lateral stabilizing force of 10% BW could reduce metabolic
power by 3% to 4%.29 To walk at a steady velocity in normative conditions (ie, no LBPP), the horizontal braking and propulsive GRF impulses (time integrals of force) must be equal.
Thus, if the LBPP device applied an assistive horizontal force
to the subject, the average horizontal GRF would be biased. To
estimate the horizontal force applied by the LBPP device
during walking, I determined the average horizontal GRF from
both legs over 10 strides per trial. I found that average horiArch Phys Med Rehabil Vol 91, June 2010
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EFFECTS OF VELOCITY AND WEIGHT SUPPORT DURING WALKING, Grabowski
zontal GRFs were –12.0, –9.8, –13.4, and –14.3N for .85, .75,
.50, and .25 BW, respectively, across all walking velocities.
These greater biases toward horizontal braking GRF clearly
indicate that subjects leaned back into the LBPP device, getting
an assistive force and thereby decreasing their metabolic power
demand. Future research is needed to measure the actual horizontal and lateral forces applied by the LBPP device. Also,
combining a dual-belt force-measuring treadmill23,30 with the
LBPP device would allow a better understanding of how LBPP
affects each individual leg’s horizontal and lateral GRF.
When subjects walked 1.25m/s at 0.83 BW, metabolic power
was lower than expected and did not follow the overall linear
trends shown in all other conditions (see fig 3; see table 1). At
this velocity and BW, there were no unexpected changes in peak
vertical GRF or in stride kinematics (see fig 5; see table 2). Based
on my results, there is no clear explanation for this relatively
lower metabolic demand. Although the relationship between
muscle activity and weight support has been measured previously,31-33 additional studies are necessary to determine how
LBPP affects muscle activity during walking over a broader
BW range, specifically including .85 BW.
During human walking, muscles generate force to support
body weight and perform work to transition the center of mass
from step to step.34 The relative metabolic power attributable to
each of these tasks could change with velocity; however, I
found that this was not the case for LBPP BW support. I
estimated the percentage of metabolic power required for BW
support from the slopes of the linear least-squares regression
equations relating %NMP (% of net metabolic power relative to
walking at 1.0 BW or 100% NMP) and BW.13 At 1.00m/s:
%NMP⫽(56.01 ⫻ BW)⫹43.34 (R2⫽.50), 1.25m/s: %NMP⫽
(53.24 ⫻ BW)⫹44.78 (R2⫽.46), and 1.50m/s: %NMP⫽(50.80
⫻ BW)⫹48.48 (R2⫽.37). Thus, the percentage of metabolic
power required for BW support was approximately 56%, 54%,
and 51%, at 1.00, 1.25, and 1.50m/s, respectively. These percentages were not significantly different (P⬎.05). Thus it
seems that for walking 1.0 to 1.5m/s, the relative metabolic
power required for BW support does not change. However, a
broader range of velocities may have revealed significant
changes in metabolic power. Also, because the LBPP device
applied horizontal and lateral support to the center of mass as
well as vertical weight support, the independent effects of
generating force to support BW were not isolated.
The net metabolic power data were represented well by a
multiple linear regression equation (R2⫽.57) (see fig 4). I
assumed linear relationships between net metabolic power and
velocity and between net metabolic power and BW to calculate
the multiple linear regression equation. However, previous
studies have shown a curvilinear relationship between net
metabolic power and velocity over a wider range of speeds.35,36
I chose a linear fit to describe my data because walking speeds
were moderate and the difference between a linear and curvilinear fit was small.
The use of LBPP devices during treadmill walking may
assist in orthopedic rehabilitation by allowing safely repeatable
gait patterns and decreasing potentially detrimental peak vertical GRF. Similar to previous results,10,12 I found that P1 was
greater when walking faster, but P2 did not significantly
change with velocity. Also, similar to previous research examining peak vertical GRFs with changes in BW,15 I found that
both P1 and P2 decreased proportionally with BW (see figs 5
and 6).
CONCLUSIONS
The use of an LBPP treadmill-training device, such as the
Anti-Gravity Treadmill,a can reduce the forces acting on the
Arch Phys Med Rehabil Vol 91, June 2010
musculoskeletal system while maintaining metabolic demand
and kinematic timing patterns during walking. Thus, LBPP
treadmill training could be especially useful for orthopedic
rehabilitation because by walking at faster velocities with BW
support, peak vertical GRF can be attenuated while aerobic and
neuromuscular stimuli that are similar to normal weight walking are maintained. Future studies are needed to determine
specific LBPP orthopedic rehabilitation prescriptions.
Acknowledgments. I thank Eileen Purdy, MEd, for her help with
data collection and Rodger Kram, PhD, for his insightful comments
and suggestions.
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e. The MathWorks, 3 Apple Dr, Natick, MA 01760.
f. JMP, SAS Software, Campus Dr, Building S, Cary, NC 27513.
Arch Phys Med Rehabil Vol 91, June 2010