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The purpose of this study was to compare the kinematic and kinetic parameters of treadmill running to those of overground running. Twenty healthy young subjects ran overground at their self-selected moderate running speed. Motion capture and ground reaction force (GRF) data for three strides of each limb were recorded and the subjects' average running speed was evaluated. The subjects then ran on an instrumented treadmill set to their average overground running speed while motion capture and GRF data were recorded. The kinematics (body segment orientations and joint angles) and kinetics (net joint moments and joint powers) for treadmill (15 consecutive gait cycles) and overground running (three cycles each limb) were calculated and compared. The features of the kinematic and kinetic trajectories of treadmill gait were similar to those of overground gait. Statistically significant differences in knee kinematics,the peak values of GRF, joint moment, and joint power trajectories were identified. Parameters measured with an adequate instrumented treadmill are comparable to but not directly equivalent to those measured for overground running. With such an instrument, it is possible to study the mechanics of running under well-controlled and reproducible conditions. Treadmill-based analysis of running mechanics can be generalized to overground running mechanics, provided the treadmill surface is sufficiently stiff and belt speed is adequately regulated.
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A Kinematics and Kinetic Comparison
of Overground and Treadmill Running
Department of Physical Medicine and Rehabilitation, University of Virginia, Charlottesville, VA;
Department of Biomedical Sciences, University of Sassari, Sassari, ITALY
RILEY, P. O., J. DICHARRY, J. FRANZ, U. D. CROCE, R. P. WILDER, and D. C. KERRIGAN. A Kinematics and Kinetic
Comparison of Overground and Treadmill Running. Med. Sci. Sports Exerc., Vol. 40, No. 6, pp. 1093–1100, 2008. Purpose: The
purpose of this study was to compare the kinematic and kinetic parameters of treadmill running to those of overground running.
Methods: Twenty healthy young subjects ran overground at their self-selected moderate running speed. Motion capture and ground
reaction force (GRF) data for three strides of each limb were recorded and the subjects_average running speed was evaluated. The
subjects then ran on an instrumented treadmill set to their average overground running speed while motion capture and GRF data were
recorded. The kinematics (body segment orientations and joint angles) and kinetics (net joint moments and joint powers) for treadmill
(15 consecutive gait cycles) and overground running (three cycles each limb) were calculated and compared. Results: The features of
the kinematic and kinetic trajectories of treadmill gait were similar to those of overground gait. Statistically significant differences in
knee kinematics, the peak values of GRF, joint moment, and joint power trajectories were identified. Discussion: Parameters measured
with an adequate instrumented treadmill are comparable to but not directly equivalent to those measured for overground running. With
such an instrument, it is possible to study the mechanics of running under well-controlled and reproducible conditions. Significance:
Treadmill-based analysis of running mechanics can be generalized to overground running mechanics, provided the treadmill surface is
sufficiently stiff and belt speed is adequately regulated. Key Words: BIOMECHANICS, GROUND REACTION FORCES, INVERSE
Although treadmills are often used for training, they
also can provide a means for a clinician or scientist
to evaluate the biomechanics of running under
controlled conditions. A new generation of instrumented
treadmills has been developed which permit ground re-
action force (GRF) to be measured. It is now possible to
analyze both the kinematics and kinetics of running on an
instrumented treadmill. Instrumented treadmills offer a
powerful tool to evaluate running biomechanics. Thus, un-
derstanding the kinematics and kinetics of running on an
instrumented treadmill as compared to overground running
is particularly important.
Before the advent of instrumented treadmills, a number
of researchers attempted to compare the kinematics of
treadmill and overground running. Elliot and Blanksby (3)
reported a shorter unsupported (flight) phase, decreased
stride length, and increased cadence in moderate speed (3.3
to 4.8 mIs
) running on a treadmill compared to over-
ground running. Frishberg (4) compared sprint kinematics
in five collegiate level sprinters overground (mean velocity
8.54 T0.09 mIs
) and on a treadmill (mean velocity 8.46 T
0.13 mIs
) and found no significant differences in stride
frequency, step length, support time, or flight time between
the two conditions. Frishberg did, however, report differ-
ences in segmental kinematics. The support thigh was
more erect at contact and moved with a slower angular
velocity, whereas the support shank was less erect at contact
and moved with a greater range of motion and angular
velocity while sprinting on a treadmill. Nigg et al. (13)
reported that runners on a treadmill consistently land with
Address for correspondence: Robert P. Wilder, M.D., University of Vir-
ginia, Department of Physical Medicine and Rehabilitation, 545 Ray C.
Hunt Dr, Suite 240, Box 801004, Charlottesville, VA 22908-1004; E-mail:
Submitted for publication December 2006.
Accepted for publication October 2007.
Copyright Ó2008 by the American College of Sports Medicine
DOI: 10.1249/MSS.0b013e3181677530
Copyright @ 200 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
a more flat foot than when running overground. In a re-
view of comparisons of treadmill and overground running
kinematics and time distance parameters, Williams (22)
concluded that the majority of comparisons showed no
significant differences and that significant differences
only occurred at speeds greater than 5.0 mIs
. Schache
et al. (18) reported similar lumbo-pelvic-hip complex three-
dimensional (3D) kinematics in treadmill and overground
running. Nigg et al. (13) noted that adaptations to treadmill
running differ from individual to individual and Lavanska
et al. (8) observed that familiarity with treadmill running
affects a runner_s biomechanics. A number of factors may
account for differences in treadmill and overground run-
ning: the size and nature of the running surface (6), the
procedures used to identify the events of initial contact
and toe-off, the treadmill running experience of the sub-
jects, the degree of treadmill accommodation and the tested
running speeds (18).
Although the kinematics of treadmill and overground
running have been reported to be similar or only slightly
different, some believe that the kinetics of treadmill run-
ning and overground running are fundamentally differ-
ent. Winter (23) had noted that the average velocity of
the center of mass when running on a treadmill was zero
and hypothesized that runners receive energy from the
treadmill at foot contact and impart energy to the belt at
toe-off. van Ingen Schenau (20), however, showed analyti-
cally that if treadmill belt speed is constant and a refer-
ence frame moving with the treadmill belt is employed,
the mechanics of treadmill and overground running
were identical (neglecting only wind resistance). Kram
et al. (7) developed a treadmill to measure the vertical and
anterior–posterior GRF while running on a treadmill, and a
single subject test found that the GRF components of
treadmill and overground running at the same speed were
very similar, suggesting that the underlying biomechanics
are similar.
Although various similarities and differences between
treadmill and overground running have been either reported
or suggested, there has never been, to our knowledge, a
study of joint kinetics, i.e., net joint moments and powers
at the hip, knee, and ankle, during treadmill running. Joint
kinetic parameters provide insights into the underlying
biomechanics of gait such that joint kinetics are now con-
sidered an essential component of clinical gait analysis. We
(16,17) have shown that, with an adequate instrumented
treadmill, it is possible to perform a full inverse dynamic
analysis of instrumented treadmill walking to provide
calculations of net joint moments and joint powers. The
purpose of this study is to present, for the first time, the
combined kinematics and kinetics (including joint kin-
etics) of running on an instrumented treadmill and to com-
pare this data to that collected while running overground.
Given the results of our comparison of instrumented tread-
mill and overground walking (17), we hypothesize that
the kinematics and kinetics of instrumented treadmill
running will be fundamentally similar to those of over-
ground running.
Subjects. Twenty healthy young runners/joggers
(10 female) were recruited from the local population. The
subjects were regular runners who ran/jogged at least 15
miles each week. Subjects were free of chronic
musculoskeletal pathology and had no running-related
injury within the last 6 months. The University of Virginia
School of Medicine Institutional Review Board approved
the testing protocol and written informed consent was
obtained from each subject before testing. The average
(T1 SD) subject was 25.2 T4.6 yr, had an average mass of
66.4 T11.2 kg, and was 1.75 T0.08 m in height.
Protocol. All testing was conducted in the Department
of Physical Medicine and Rehabilitation Gait and Motion
Laboratory. Overground running tests were conducted on
an approximately 15-m runway. Treadmill running tests
were performed on an instrumented treadmill (11,12).
Subjects were instructed to run overground trials across
the runway at their 10-km race pace. The subjects made
practice runs until they felt, and the researchers agreed, that
they had accommodated to running on the relatively short
runway. Kinematic and kinetic data were then acquired
until data for three complete strides of each lower limb were
obtained. Immediately after acquisition, a sample of the
overground running trials was processed using the standard
Vicon event detector and gait cycle parameter estimator to
determine the subject_s approximate average overground
running speed. The instrumented treadmill was then set to
the average overground running speed, and the subjects
practiced running on the treadmill at that speed for 3 to 5
min. All subjects verbally reported feeling comfortable
running on the treadmill at the set speed. Three to five
synchronized 30-s recordings of kinematic and kinetic data
were then captured. The third trial was used for analysis, the
fourth if there were problems with the kinematic data of the
third trial. Subjects ran in their personal running shoes.
The same laboratory technician placed all retroreflective
markers used for motion capture, and marker placement was
unchanged between the instrumented treadmill and over-
ground conditions. Markers on the seventh cervical (C7)
and tenth thoracic (T10) vertebrae, on the sternal notch and
ziphoid process, and on the left and right acromion pro-
cesses defined trunk motion. The lower body marker set
corresponded to the standard Vicon Plug-in-gait model and
is widely used in motion analysis (2,5). Markers on the left
and right anterior and posterior superior iliac processes
defined the motion of the pelvis. The motion of each
lower limb segment was tracked by markers on the lateral
femoral condyles, lateral malleoli, lateral midthighs, lateral
midshanks, heels, and second metatarsal heads. This set
of 22 retroreflective markers defined the 3D kinematics
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of the trunk and pelvis, and the left and right thighs, shanks,
and feet.
Measurements. Kinematic data were recorded using a
10-camera VICON 624 Motion Capture system operating at
120 Hz (Vicon Peak, Lake Forest, CA, USA). The modified
whole-body marker set allowed determination of the
position and orientation of the pelvis relative to global
coordinates. Reported pelvic kinematics are the movements
of the pelvis in the laboratory coordinate system. Spine
kinematics are movements of the trunk segment in the
pelvic coordinate system. Hip angles are rotations of the
thigh segments in the pelvis coordinate system, and the
remaining lower limb joint angles are rotations of the distal
segment in the coordinate system of the proximal segment.
Joint moments are reported as internal moments.
GRF data were acquired at the same frequency and in
synchrony with the motion capture data. Overground GRF
data were acquired using either one of the two in-ground
force plates or one of the instrumented treadmill sensors
functioning as static force plates. Both the in-ground and
instrumented treadmill force plates were produced by AMTI,
Watertown, MA, USA. We have previously reported on
the characteristics of the instrumented treadmill force
plates (16). The instrumented treadmill is an assembly of
three treadmill forceplates. Two smaller units (330 mm
1395 mm) sit side-by-side behind a larger unit (663 mm
1395 mm) providing a total running surface of 0.66 m
wide by 2.795 m long. Because the instrumented treadmill
force plates are somewhat larger than the fixed plates, they
have slightly lower vertical natural frequencies. The mea-
sured vertical resonant frequency of the small units is
slightly over 300 Hz and is 219 Hz for the large unit. The
nominal vertical resonant frequency of the fixed force plates
is 380 Hz. A brushless servomotor rated at 4.7 kW with a
200% 30-s overload capacity drives each treadmill unit. The
motors servo on speed and run in synchrony. The measured
belt speed variation at foot contact when running at 4 mIs
TABLE 1. Time–distance parameters for treadmill and overground running.
Overground Treadmill
Time Distance Parameters Mean SD Mean SD Pvalue
Cadence (1 min
) 170.27 15.77 175.05 11.01 0.0086
Walking speed (mIs
) 3.84 0.64 3.80 0.61 0.1161
Stride time (s) 0.71 0.06 0.69 0.04 0.0011
Toe off (% cycle) 33.52 2.91 33.26 3.53 0.6860
Stride length (m) 2.71 0.36 2.60 0.36 0.0001
Differences that were statistically significant are boldface.
FIGURE 1—3D angular kinematics for overground running (mean, solid black line;T1 SD, dotted black lines) and treadmill running (mean, gray
line). Angular displacements are in degrees. Arrows indicate peaks found to be significantly different (Table 2).
TREADMILL AND OVERGROUND RUNNING Medicine & Science in Sports & Exercise
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was less than 7% and was of brief duration because of the
fast response of the motor controllers. Only a single unit is
required for analysis of running.
Motion capture and GRF data were processed using
VICON Plug-in Gait. However, the instrumented treadmill
GRF data were preprocessed using in-house algorithms,
implemented in LabView (National Instruments, Austin,
TX, USA). The preprocessing software detected foot-strikes
and toe-offs using a threshold for the vertical component
of the force vector of GRF. A threshold setting of 60 N
(~10% body weight) (9) was used. However, in some cases,
drift exceeded this value for later cycles. We corrected for
drift, but only after we had defined the support and contact
phases. To get a uniform and adequate number of cycles
when drift was a problem, we increased the threshold, not
exceeding 150 N (~20%) of body weight. The preprocessor
corrected for drift using the flight-phase instrument output
as an offset to correct the following stance phase. Instru-
mented treadmill force plate data were low pass filtered at
30 Hz using a forward and reverse filtering technique
(second order Butterworth low-pass filter). An antialiasing
filter, also Butterworth, low-pass filtered the static force
plate data at 50 Hz. Because of mechanical and electrical
noise, somewhat more filtering was required for the instru-
mented treadmill data to achieve comparable signal to
noise characteristics (16). Plug-in-gait calculated the time–
distance parameters, pelvis, spinal (trunk relative to pelvis),
and lower limb kinematics, the net internal moments for
each lower limb joint and the associated joint powers.
Analysis. Individual and group mean parameters were
obtained using in-house algorithms developed using
LabView. For the overground runs, average time–distance
parameters and average plots of kinematic and kinetic
parameters were obtained from the six strides recorded
(three for each lower limb). For the instrumented treadmill
runs, we determined the maxima and minima using one to 30
strides for each subject and graphically examined the
stability of the mean as a function of the number of strides.
Ten to 12 strides were required to produce a stable estimate
of the mean. Results obtained from 15 strides of each lower
limb are reported. Maxima and minima of the kinematic and
kinetic parameters were extracted from each cycle evaluated
and the average over the cycles reported. A total of 30 kin-
ematic and 30 kinetic maximum and minimum parameters
were evaluated. For kinematic parameters, the curves for
the entire stride were considered. For kinetic parameters,
stance phase maxima and minima were determined. The sig-
nificance of group mean differences in the maxima and
minima were evaluated using a multiple repeated-measures
ANOVA (SPSS, Chicago, IL, USA). Gender and limb side
were between-subject variables in the analysis. Signifi-
cance was at alpha less than 0.05 and a Bonferroni adjust-
mentwasusedtocorrectfor multiple measurements
(effective alpha G0.00167).
Time–distance parameters. The average speed of
3.80 mIs
for instrumented treadmill running was similar
to the average overground running speed of 3.84 mIs
accordance with the protocol design. The slight difference
was because of the variability of overground running speed.
If the overground cycles in the analysis did not correspond
to the cycles sampled at the time of acquisition, a different
overground running speed was obtained. The cadence was
significantly higher and the stride time and stride length
were significantly shorter when running on an instrumented
treadmill (Table 1).
Kinematic parameters. Qualitatively, the kinematics
of instrumented treadmill and overground running were very
TABLE 2. Kinematic parameters that multiple repeated-measures ANOVA showed were
different (PG0.05) for treadmill and overground running.
Overground Treadmill
Kinematic Parameters Mean SD Mean SD Pvalue
Hip adduction (deg) 12.1 4.1 12.7 4.0 0.0410
Hip int rot (deg) 14.3 12.8 13.0 13.1 0.0455
Hip ext rot (deg) 15.0 12.4 13.2 12.4 0.0488
Knee flx max (deg) 110.1 18.4 103.5 12.2 0.0005
Knee flx min (deg) 8.3 6.0 10.2 5.4 0.0006
Ankle eversion (deg) 2.5 3.0 1.9 2.9 0.0057
Pelvic rot max (deg) 7.6 3.5 8.5 3.0 0.0186
Pvalues that are statistically significant with a Bonferroni correction (PG0.00167) are
TABLE 3. Kinetic parameters for which multiple repeated-measures ANOVA showed differences (PG0.05) for treadmill and overground running.
Overground Treadmill Repeated Measures
Kinetic Parameters Mean SD Mean SD Pvalue
Hip ext moment (NImIkg
) 1.74 0.73 1.30 0.88 0.0041
Hip abd moment (NImIkg
) 0.41 0.21 0.32 0.20 0.0250
Knee flex moment (NImIkg
) 2.33 0.81 1.70 0.51 G0.0001
Knee varus moment (NImIkg
) 1.90 0.57 1.54 0.53 0.0001
Ankle plantarflex moment (NImIkg
) 3.44 0.70 4.01 0.56 G0.0001
Hip power absorption (WIkg
) 6.93 3.81 4.46 3.57 0.0020
Knee power generation (WIkg
) 11.26 4.39 7.63 2.54 G0.0001
Knee power absorption (WIkg
) 12.12 4.28 9.47 3.40 0.0020
Ankle power absorption (WIkg
) 8.00 3.23 10.38 3.24 G0.0001
Anterior GRF (% body weight) 37.07 11.55 30.75 4.86 0.0008
Medial GRF (% body weight) 10.94 4.73 8.29 2.73 0.0003
Vertical GRF (% body weight) 263.43 45.20 249.34 21.83 0.0205
Again, Pvalues that are statistically significant with a Bonferroni correction (PGÈ0.0167) are boldface.
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similar (Fig. 1). Quantitatively, condition (instrumented
treadmill vs overground) had a significant effect on
kinematics (P= 0.022), as did gender (P= 0.046), whereas
side did not (P= 0.678). Of the 30 kinematic parameters
considered, seven showed differences for condition (PG
0.05), but after the Bonferroni correction only two, peak
knee flexion and extension, were statistically significantly
different (Table 2). Spine kinematics are not shown in Figure
1 as there were no significant differences found among these
angles. All average joint angle curves for instrumented
treadmill running were within one SD of the corresponding
overground joint angle curve (Fig. 1).
Ground reaction forces. The peak propulsive anterior
and peak medial GRF were significantly reduced in
instrumented treadmill running (Table 3). Because of the
low sampling rate (120 Hz) a well defined vertical force
impact peak was not demonstrated in either the
instrumented treadmill or overground running condition.
The average vertical force during the instrumented treadmill
trials was 99.5% of body weight.
Kinetic parameters. Qualitatively, the joint internal
moment and power curves were similar for instrumented
treadmill and overground running, with similar patterns and
timing of peaks and troughs (Fig. 3). Quantitatively,
condition had a significant effect on peak kinetic
parameters, including GRF (PG0.001), as did gender
(P= 0.009). Again, limb side had no significant effect
(P= 0.273). Of the 24 joint moment and power parameters
FIGURE 2—3D GRF in stance for overground and treadmill running. Forces are in percent body weight. Again, arrows indicate significantly
different peaks (Table 3).
FIGURE 3—3D moments and joint powers in stance for overground running (black) and treadmill running (gray). Internal moments are normalized
to body mass (NImIkg
) as are joint powers (WIkg
). Arrows indicate peaks found to be significantly different (Table 3).
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considered, nine showed instrumented treadmill-overground
differences (PG0.05) and seven of these were significantly
different when the Bonferroni correction was applied
(Table 3). The instrumented treadmill moment and power
curves lie within one SD of corresponding overground
curves. However, for six of the seven moment and power
parameters that were significantly different, there was no
overlap of the 95% confidence intervals of the peak values.
Effect of cadence change. It is possible that the
significant differences in the peak kinetic parameters
occurred simply because the subjects chose to run at a
higher cadence and lower stride length on the instrumented
treadmill. To test this idea, the subjects were sorted into two
equal groups. The high cadence change group ran at a 14 T
7 stepsImin
higher cadence on the instrumented treadmill,
whereas the low cadence change group ran at only 3 T2
faster on the instrumented treadmill. For these
two groups, the parameters significantly different among all
subjects were compared using paired t-test between
conditions. Overall, fewer parameters were significantly
different (PG0.05) because of the smaller number of
subjects and the lower precision of the t-test. However,
most of the kinetic parameter differences were still present
in both groups (Table 4).
The mean kinematic and kinetic parameter curves of
instrumented treadmill running were within one SD of the
corresponding overground curves, indicating that instru-
mented treadmill and overground gait are similar. Compar-
isons using repeated-measures ANOVA did reveal
significant differences between the two running conditions,
particularly with regard to the kinetics. The differences in
stride length and cadence that we found have been reported
in other studies (3,18,21). Our protocol precluded determin-
ing if subjects had a different preferred speed for instru-
mented treadmill running compared to overground running.
The speed of instrumented treadmill running was slightly
slower that that of overground running, but the difference
was not statistically significant. With the exception of
sagittal plane peak knee angles, we found similarity of
angular kinematics consistent with previous studies (18,22).
A comparison of overground and instrumented treadmill
running, based on the inverse-dynamics approach to
determine joint kinetics (here, to estimate net joint moments
and joint powers during running), has not been previously
reported. Novacheck (15) studied overground running using
a similar marker set, kinematic model, and kinetic analysis.
Novacheck_s group ran at an average of 3.2 mIs
somewhat slower than our group (3.8 mIs
). Our sagittal
plane kinematics and kinetics are similar to those reported
by Novacheck. The major exception was ankle plantarflex-
ion moment which appears to differ from both our instru-
mented treadmill and overground results. This difference
may be because of the differences in the subject population
(Novacheck_s group were all heel-toe runners whereas ours
included midfoot and fore-foot strikers. Also, some of our
runners reached speeds that Novacheck would have
classified as sprinting (93.9 mIs
Among the kinematic parameters, only the differences
in peak knee sagittal plane angles for instrumented tread-
mill and overground running were statistically significant.
Matsas et al. (10) observed a similar difference in knee
kinematics between treadmill and overground walking, but
reported that the difference vanished after sufficient famil-
iarization with treadmill ambulation. All of our subjects had
some experience with treadmill running and were allowed to
accommodate to treadmill running for several minutes, until
TABLE 4. Reanalysis of the statistically significant parameters from Tables 2 and 3 for two groups of subjects, those with only a small increase in cadence when running on the
treadmill and those with a large increase in cadence.
High Cadence Change group (14 T7 stepsImin
) Low Cadence Change Group (3 T2 stepsImin
Overground Treadmill Paired t-test Overground Treadmill Paired t-test
Parameters Mean SD Mean SD Pvalue Mean SD Mean SD Pvalue
Hip adduction (deg) 10.9 3.2 10.5 3.4 0.5021 13.4 3.1 13.4 3.0 0.9676
Hip int rot (deg) 16.9 9.1 13.6 10.8 0.0094 11.7 14.1 10.6 13.8 0.2757
Hip ext rot (deg) 13.3 11.9 11.6 11.5 0.3361 16.6 10.9 12.9 9.1 0.0116
Knee flx max (deg) 117.9 17.7 105.5 13.9 0.0025 102.2 16.0 100.1 11.0 0.4531
Knee flx min (deg) 10.3 5.9 13.3 3.9 0.0111 6.2 4.8 8.0 4.5 0.0083
Ankle eversion (deg) 2.2 2.5 0.8 1.8 0.0052 2.9 2.8 2.5 2.8 0.2147
Pelvic rot max (deg) 7.2 2.7 6.0 2.7 0.0153 8.7 2.7 8.4 2.0 0.5683
Hip ext moment (NImIkg
) 1.6 0.7 1.1 0.4 0.0131 1.9 0.6 1.2 0.3 0.0086
Hip abd moment (NImIkg
) 0.4 0.2 0.3 0.1 0.0240 0.4 0.2 0.3 0.1 0.0527
Knee flex moment (NImIkg
) 2.3 0.8 1.6 0.4 0.0023 2.3 0.5 1.7 0.5 0.0004
Knee varus moment (NImIkg
) 1.9 0.5 1.5 0.4 0.0311 1.9 0.5 1.5 0.5 0.0015
Ankle plantarflex moment (NImIkg
) 3.8 0.6 4.2 0.6 0.0049 3.1 0.4 3.7 0.4 G0.0001
Hip power absorption (WIkg
) 6.5 3.2 3.9 2.2 0.0033 7.3 3.7 3.3 1.2 0.0059
Knee power generation (WIkg
) 11.4 4.2 7.4 2.0 0.0033 11.1 3.4 7.9 2.7 0.0022
Knee power absorption (WIkg
) 12.2 4.5 8.6 2.2 0.0277 12.0 2.4 8.4 2.1 0.0005
Ankle power absorption (WIkg
) 9.7 3.0 11.6 3.0 0.0289 6.3 1.7 9.0 1.9 0.0005
Anterior GRF (% body weight) 40.9 11.6 32.0 4.7 0.0276 33.3 6.4 31.3 5.2 0.0625
Medial GRF (% body weight) 12.2 4.1 8.3 2.2 0.0163 9.7 3.5 7.6 2.2 0.0678
Vertical GRF (% body weight) 275.6 43.0 254.5 28.4 0.0917 251.2 19.2 243.3 13.1 0.0285
Paired t-tests were used to identify between condition differences in the subgroup data.
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they reported and appeared to be comfortable. However,
they did not all have the 6- to 14-min familiarization period
recommended by Matsas et al. (10).
The kinetic parameters exhibit several significant differ-
ences. The peak propulsive force and peak medial force are
reduced. The reduced knee moments are consistent with the
reduction in GRF components but the increased ankle
dorsiflexion moment is not. This apparent inconsistency
may be because of the subtle differences in foot kinematics
previously reported by Nigg (13). Overall, our hypothesis
that the kinetics of instrumented treadmill and overground
running are similar is not entirely supported. The higher
ankle moments and preserved power observed in instru-
mented treadmill running, however, should put to rest the
notion that treadmill running lacks push-off. Preservation of
push-off was also observed in our comparison of instru-
mented treadmill and overground walking (17).
There were several limitations to this study. Although
the number of subjects tested was reasonable, there was
variability in running style and running speed among the
subjects. The self-selected running speeds of our sub-
jects varied from jogging to sprinting and there were mid-
foot and fore-foot contactors in the group. Speed and
contact style can affect the kinematics and kinetics of
running. The subjects wore their own shoes, which varied in
style and condition. Shoes may have an effect on running
dynamics (1,11,12,14,19). However, repeated-measures
analyses were used; the subjects used the same shoes and
running style on the instrumented treadmill as when run-
ning overground.
The data from the overground portion of the protocol
were affected by a number of inconsistencies, some specific
to our laboratory and protocol, some inherent to overground
testing. Because of the relatively short runway, we could
not be certain that overground running parameters were
measured at a steady-state condition, whereas near steady-
state conditions (Ta small amount of drift) were assured
for measures on the instrumented treadmill. Trials in which
the subject was observed to be accelerating or slowing
down were rejected, as were trials with asymmetric braking
and propulsive AP GRF data. However, the subjects had
been accelerating a stride or two before being analyzed and
would be decelerating in a stride or two. Thus, overground
data are not a steady state but the apogee of a dynamic
trajectory. This is true for overground data acquired on a
track as well as on a straight runway because on a track the
subject is coming out of and entering into a curve, possibly
with a banked surface, before and after data acquisition.
Also, the speed of each subject_s overground running trials
varied slightly, with the average reported. Instrumented
treadmill speed was matched to each subject_s overground
speed and constant (again Ta small amount of drift) for all
analyzed data. Because of mechanical and electrical noise,
a higher vertical GRF threshold was used to detect foot
contact on the instrumented treadmill. However, a variety of
techniques used to determine foot contact in overground
data is perhaps more problematic. Vertical GRF thresholds
are used for clean force plate strikes, computer matching of
foot marker trajectories was used in the absence of force
plate data, and visual analysis of the kinematics was used
to resolve inconsistencies. Three cycles per limb were used
to determine the characteristics of overground running,
while fifteen were used for instrumented treadmill run-
ning. Qualitative analysis of the stability of the mean for
instrumented treadmill data indicated that using 10 to 12
cycles or more was desirable. Although it would have been
possible to obtain more cycles of overground data, it is
certainly more convenient to obtain many cycles on an
instrumented treadmill. All foot contacts in the instru-
mented treadmill data set were with the same surface with
the same rigidity. In overground running, the subjects con-
tacted a walkway and in-ground force plates covered with
the same thin carpet material, but with somewhat different
stiffness, and the instrumented treadmill force plates,
covered by smooth belts with rigidity similar to, but slightly
different from, the in-ground force plates. In overground
trials, slip did not appear to be a problem either with the
instrumented treadmill forceplate belts or the in-ground
forceplate covering.
What factors contribute to the differences? Van Ingen
Schenau (20) established the requirement for constant
instrumented treadmill belt speed, which is not strictly met
by our device nor likely by any other. Speed variations
can be minimized by using a robust motor and belt drive
and careful maintenance, but cannot be completely elimi-
nated. However, the speed variations we were able to mea-
sure were small and very brief, one or two sample times.
Speed variations occurred around the time one would ex-
pect the impact peak. Had we seen an impact peak in the
overground data, but not in the instrumented treadmill data,
this would have been the likely cause. However, neither
data set evidenced a well-defined impact peak. The kinetic
differences occurred at times when belt speed was well
controlled. Any effect of speed variation would have been
indirect because of the subject_s adaptation to the treadmill,
for example.
We did not provide as much accommodation time for
treadmill running as Matsas et al. (10) recommended, but
our analyses are based on the third or, in some cases, the
fourth 30-s instrumented treadmill trial for each subject.
Because each trial took a bit more than a minute, (30 s for
the actual data acquisition and 30+ s for data processing
and storage), it is fair to say that all subjects had 5 min to
accommodate to instrumented treadmill running before the
analyzed data were acquired. Accommodation to running
on a short runway was also an issue. Each subject made
several practice runs and several runs were made to ob-
tain three complete cycles with clean force plate data for
each limb. There are indications that, beyond the need for
accommodation, there is simply a tendency to adapt a
slightly different running pattern on a treadmill. The fact
that half of our subjects ran at the same stride length and
TREADMILL AND OVERGROUND RUNNING Medicine & Science in Sports & Exercise
Copyright @ 200 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
cadence as well as speed on the instrumented treadmill
indicates that it is biomechanically possible to do so. The
fact that half of our subjects ran with a very different stride
length and cadence indicates that it is equally possible to
adopt a different strategy. Just as people may adopt a
different running pattern on a treadmill, so also do they tend
to adopt different running patterns when bare foot or in
various shoes, when running on a compliant track or on
hard pavement, or when running straight or on a curve. In
studying the biomechanics of running, the question is not
which running pattern is normal; all are normal for their
condition. The concerns are: (1) is the condition represen-
tative of the overall task? (2) Can the conditions be con-
trolled and reproduced within and between subjects? With
a well-designed, built, and maintained instrumented tread-
mill, the answer to both of these questions is yes. Thus, we
believe that the use of instrumented treadmills to study
running is justified, and that such studies will make im-
portant contributions to understanding the biomechanics
and physiology of running.
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http://www.acsm-msse.org1100 Official Journal of the American College of Sports Medicine
... 15 Currently, few studies have examined joint power kinetics and running, with limited studies investigating running injuries. [15][16][17] Dicharry reported that running power kinetics are similar to walking at each joint, just with an increased amplitude. 15 Xu et al. recognized that forefoot strike pattern resulted in smaller knee power absorbed and higher ankle power absorbed compared to rearfoot strikers. ...
... 16 Riley et al. compared overground running joint power to treadmill running and found a statistical difference in knee power generated and ankle power absorbed between the two modes of running. 17 To the authors' knowledge, there are no reports available that have assessed joint power of injured runners. ...
... In the end, all subjects had at least 15 steps (normally > 20) per trial. 17 ...
Full-text available
Background There is conflicting data on which kinetic variables are important to consider with running injuries. Furthermore, less is understood regarding differences in these variables when considering demographics such as age, sex, weight, and running speed. The primary question was what joint power kinetic variables were different between non-injured and injured runners. Purpose The purpose of this study was to identify if there were differences in joint power kinetic variables between non-injured runners and injured runners. Study Design Case-Control Study Methods Kinetic data were collected on 122 runners (26 non-injured and 96 injured) over three years with a Bertec force plated treadmill and Qualisys 3D motion capture. The subjects were considered eligible if they self-identified themselves as runners or had running as a key component of their activity. The subjects ran at a comfortable, self-selected pace while two 10-second trials of recordings were used to calculate the means of peak power generated at the hips, knees, and ankles of each gait cycle. Foot strike was categorized by kinematic data. Two sample T-tests were used to compare peak power variables at the hips, knees, and ankles between non-injured and injured runners. Logistic regression analyses examined how a combination of demographics and peak power variables were associated with injuries. Results No peak power variable at the hip, knee, or ankle was significantly different between injured and non-injured runners (p=0.07-0.87). However, higher hip power absorbed was found to be protective against injuries (odds ratio, .16; 95% CI .025-.88) when considering demographics using a logistic regression model including sex, foot strike, BMI, speed, age, and power variables from the hip, knee, and ankle. The area under the ROC curve was .74, which is acceptable discrimination. Conclusion When controlling for age, sex, BMI, foot strike, and speed; higher hip power absorbed was found to be protective against injury. This could be due to the hip muscles’ unique role in absorbing force during early stance phase. Level of Evidence 3b ©The Author(s)
... However, there were also instances of only minor changes [30] or even no changes in stride frequency [25]. Additionally, treadmill running introduces alterations in stride frequency [2,[31][32][33]. At moderate speeds on a treadmill, there is a tendency for a reduction in stride length and an increase in stride frequency compared to natural ground running [34]. ...
... However, it is essential to note that the influence of the treadmill on running movements has led to controversial discussions regarding the results [2]. Despite the controversies, these treadmill-induced changes have been accepted by various authors as representative of running investigations [31,32,35]. ...
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Fatigue has the potential to alter how impact forces are absorbed during running, heightening the risk of injury. Conflicting findings exist regarding alterations in both kinematics and plantar pressure. Thus, this systematic review and subsequent meta-analysis were conducted to investigate the impact of general and localized muscle fatigue on kinematics and plantar pressure distribution during running. Initial searches were executed on 30 November 2021 and updated on 29 April 2023, encompassing PubMed, The Cochrane Library, SPORTDiscus, and Web of Science without imposing any restrictions on publication dates or employing additional filters. Our PECOS criteria included cross-sectional studies on healthy adults during their treadmill running to mainly evaluate local muscle fatigue, plantar pressure distribution, biomechanics of running (kinematics, kinetics, and EMG results), and temporospatial parameters. The literature search identified 6626 records, with 4626 studies removed for titles and abstract screening. Two hundred and one articles were selected for full-text screening, and 20 studies were included in qualitative data synthesis. The pooled analysis showed a non-significant decrease in maximum pressure under the right forefoot’s metatarsus, which was more than the left rearfoot after local muscle fatigue at a velocity of 15 km/h (p-values = 0.48 and 0.62). The results were homogeneous and showed that local muscle fatigue did not significantly affect the right forefoot’s stride frequency and length (p-values = 0.75 and 0.38). Strength training for the foot muscles, mainly focusing on the dorsiflexors, is recommended to prevent running-related injuries. Utilizing a standardized knee and ankle joint muscle fatigue assessment protocol is advised. Future experiments should focus on various shoes for running and varying foot strike patterns for injury prevention.
... In addition, whether it is possible to compare running on a treadmill with running on a track is uncertain because a laboratory environment is not identical to the usual running environment and may result in different running kinematics and kinetics [73]. This comparison is made in other studies [74,75], where the authors claim differences exist in the results for various variables in both scenarios. In contrast, Pink et al. [76] affirmed that the results are similar for both cases. ...
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The worldwide popularisation of running as a sport and recreational practice has led to a high rate of musculoskeletal injuries, usually caused by a lack of knowledge about the most suitable running technique for each runner. This running technique is determined by a runner’s anthropometric body characteristics, dexterity and skill. Therefore, this study aims to develop a motion capture-based running analysis test on a treadmill called KeepRunning to obtain running patterns rapidly, which will aid coaches and clinicians in assessing changes in running technique considering changes in the study variables. Therefore, a review and proposal of the most representative events and variables of analysis in running was conducted to develop the KeepRunning test. Likewise, the minimal detectable change (MDC) in these variables was obtained using test–retest reliability to demonstrate the reproducibility and viability of the test, as well as the use of MDC as a threshold for future assessments. The test–retest consisted of 32 healthy volunteer athletes with a running training routine of at least 15 km per week repeating the test twice. In each test, clusters of markers were placed on the runners’ body segments using elastic bands and the volunteers’ movements were captured while running on a treadmill. In this study, reproducibility was defined by the intraclass correlation coefficient (ICC) and MDC, obtaining a mean value of ICC = 0.94 ± 0.05 for all variables and MDC = 2.73 ± 1.16° for the angular kinematic variables. The results obtained in the test–retest reveal that the reproducibility of the test was similar or better than that found in the literature. KeepRunning is a running analysis test that provides data from the involved body segments rapidly and easily interpretable. This data allows clinicians and coaches to objectively provide indications for runners to improve their running technique and avoid possible injury. The proposed test can be used in the future with inertial motion capture and other wearable technologies.
... Participants carried out 10000m racewalking on the treadmill with the same speed in measurement A. EMG was collected during two phases (2150 m and 8150 m) for the 10000m racewalking. The literature reported that there was a high correlation between over-ground and treadmill walking equally to r=0.93 (Riley et al., 2008). The treadmill was calibrated and checked before and after each test, according to the instructions of the manufacturer (Johnny Padulo et al., 2014). ...
Full-text available
This study aims to know the effect of 12-weeks of special exercises using rhythmic auditory to improve spatio-temporal stride parameters (STSP), lower limb muscles activity (LLMA), and 10000m racewalking time (RT). The parameters of STSP are stride length (SL), step cadence (SC), and center-of-mass velocity (CMV). The research sample included twelve racewalkers, and they were divided into two groups (control group and experimental group, six in each). STSP was measured using a Sony camera at a speed of 50 frames/sec for analyzing 25-samples for each racewalker in the 10000m racewalking. LLMA was measured using EMG. In addition, we applied the 10000m test to measure RT. Rhythmic auditory was used to regulate the step rhythm in seven special exercises and the essential part of the training. The steps rhythm was divided into three levels: the 1st slow auditory rhythm, the 2nd comfortable auditory rhythm, and the 3rd fast auditory rhythm. From our findings, there is a significant difference in the post-test for SC, CMV, LLMA, and RT, favoring the experimental group, where P.04<.05, η2=.732 for SC, P.038<.05, η2=.485 for CMV, P.015<.05, η2=.333 for LLMA, and P.044<.05, η2=.483 for RT. While there is no significant difference in the post-test for SL, where P.264>.05. In addition, there is a significant improvement between groups favoring the experimental group as ROC=1.62,5.76,7.48,33.9, and 7.03% for SL, SC, CMV, LLMA, and RT respectively. Comparisons showed that the post-test achieved greater Megahed et al. SPORT TK. Year 2023. Volume 12. Article 7. 2 improvement with a large effect in STSP, LLMA, and RT compared to the pre-test that achieved a small effect. Therefore, the rhythmic auditory in the training has a beneficial role in improving spatio-temporal stride parameters, lower limb muscles activity and racewalkers' records.
... Our findings did not fully agree with these observations, as we found our markerless method to estimate a lower hip extension moment, slightly higher peak knee extension moment, and comparable ankle plantarflexion moment during over-ground running (Fig. 4d). Several factors could have contributed to these disagreements, including distinct over-ground and treadmill running kinetics (Riley et al., 2008), moment normalization techniques (Moisio et al., 2003), marker placements, and marker-based model definitions. It is possible that the rapid running motion negatively affected the accuracy of both systems. ...
Motion analysis is essential for assessing in-vivo human biomechanics. Marker-based motion capture is the standard to analyze human motion, but the inherent inaccuracy and practical challenges limit its utility in large-scale and real-world applications. Markerless motion capture has shown promise to overcome these practical barriers. However, its fidelity in quantifying joint kinematics and kinetics has not been verified across multiple common human movements. In this study, we concurrently captured marker-based and markerless motion data on 10 healthy study participants performing 8 daily living and exercise movements. We calculated the correlation (Rxy) and root-mean-square difference (RMSD) between markerless and marker-based estimates of ankle dorsi-plantarflexion, knee flexion, and three-dimensional hip kinematics (angles) and kinetics (moments) during each movement. Estimates from markerless motion capture matched closely with marker-based in ankle and knee joint angles (Rxy ≥ 0.877, RMSD ≤ 5.9°) and moments (Rxy ≥ 0.934, RMSD ≤ 2.66 % height × weight). High outcome comparability means the practical benefits of markerless motion capture can simplify experiments and facilitate large-scale analyses. Hip angles and moments demonstrated more differences between the two systems (RMSD: 6.7-15.9° and up to 7.15 % height × weight), especially during rapid movements such as running. Markerless motion capture appears to improve the accuracy of hip-related measures, yet more research is needed for validation. We encourage the biomechanics community to continue verifying, validating, and establishing best practices for markerless motion capture, which holds exciting potential to advance collaborative biomechanical research and expand real-world assessments needed for clinical translation.
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Background: Enhancing knee protection for individuals who are overweight and obese is crucial. Cushioning insoles may improve knee biomechanics and play a significant protective role. However, the impact of insoles with varying cushioning properties on knee joints in individuals with different body mass index (BMI) categories remains unknown. Our aim was to investigate the biomechanical effects of insoles with different cushioning properties on knee joints across different BMI grades. Methods: Gravity-driven impact tests were used to characterize the cushioning properties of three types of Artificial Cartilage Foam (ACF18, 28, and 38) and ethylene-vinyl acetate (EVA) insoles. Knee joint sagittal, coronal, and vertical axis angles and moments were collected from healthy-weight (BMI 18.5–23.9 kg/m², n = 15), overweight (BMI 24.0–27.9 kg/m², n = 16), and obese (BMI ≥28.0 kg/m², n = 15) individuals randomly assigned four different insoles during a drop jump. The Kruskal–Wallis test and mixed model repeated measures analysis of variance were used to compare differences among cushioning and biomechanical data across various insoles, respectively. Results: ACF showed higher cushioning than EVA, and ACF38 was the highest among the three types of ACF (all p < 0.001). During the drop jump, the knee flexion angles and moments of the ACF insoles were lower than those of the EVA insoles, the knee adduction angles of the ACF18 and ACF28 insoles were lower than those of the EVA insoles, and ACF18 insoles increased the first cushion time (all p < 0.05) for all participants in whom biomechanical variables demonstrated no interactions between insoles and BMI. Regarding the BMI-dependent biomechanical variables, compared with the EVA insoles, ACF28 insoles decreased the knee flexion angle and ACF38 insoles decreased the knee adduction and rotation moment in the healthy-weight group; ACF18 insoles decreased the knee flexion angle and ACF38 insoles decreased the knee moment in the overweight group; ACF28 insoles decreased the knee flexion and adduction moment, and ACF38 insoles decreased the knee flexion angle and rotation moment in the obese group (all p < 0.05). Conclusion: Insoles with higher cushioning properties could improve knee biomechanics and provide better knee joint protection in people across different BMI ranges.
PurposeFatigue has a potential effect on knee stiffness reduction. Quadriceps fatigue intervention of repeated contractions is one traditional type of inducing knee fatigue. Therefore, defining the connection between quadriceps fatigue and knee stiffness may be beneficial to early knee rehabilitation. Knee passive stiffness was passive component of overall knee stiffness, this study aimed to investigate the effect of quadriceps fatigue on knee passive stiffness.Methods The preliminary experiment was first performed with a separate cohort of 6 participants to verify the passive stiffness measurements. Then 30 participants were recruited in fatigue experiment of lower hip angle conditions. The fatigue protocol was induced by repetitive quadriceps isometric contractions in three fatigue cycles. Knee passive stiffness between pre and post 50% range of motion (ROM) groups were calculated by the regression slope of angular displacement-torque curve.ResultsKnee passive stiffness measurements were lower under conditions of lower hip angle. There was a significant difference in passive stiffness between pre and post 50% ROM groups. Only passive stiffness of pre 50% ROM showed a remarkable decrease after fatigue (approximately 3.8%, p < 0.05).Conclusion When quadriceps reached fatigue with the repeated isometric contractions, the influence of fatigue on knee passive stiffness of pre and post 50% ROM was different. Passive stiffness of pre 50% ROM decreased significantly when the fatigue threshold reached 90-fold isometric contractions. The finding may help understand how passive knee stiffness changes under fatigue conditions. It may also provide references of fatigue dosage in rehabilitation training to improve knee passive stiffness and ROM in early rehabilitation.
PurposeThe purpose of this study was to investigate continuous knee passive stiffness and its fatigue responses. Knee osteoarthritis is a clinically degenerative disease that mostly cause sustained stiff knee, hence, there is an urgent need to evaluate continuous knee passive stiffness, which corresponded to the stiffness of various angles during actual continuous knee rotation. However, how to measure this kind of stiffness is yet to reach an agreement.Methods This is a study incorporating 36 individuals, in which the fatigue protocol consisted of three bouts of multiple quadriceps voluntary isometric contractions of their dominant legs. Angle and passive torque were measured before and after each fatigue intervention cycle. Continuous knee passive stiffness of various angles and rate of stiffness under fatigue were both calculated.ResultsWe derived the continuous knee passive stiffness data appeared as an asymmetric U-shaped curve. The passive stiffness (Nm/°) of the initial angle (0°) is 0.249 (0.159–0.285), while that of the other endpoint angle (91°) is 0.156 (0.130–0.354). The responses of continuous knee passive stiffness following fatigue interventions revealed a significant decrease in the knee angle from 10 to 36° (p = 0.02–0.05).Conclusion This renew study experimentally develop a novel approach to expand upon the existing methods of knee passive stiffness measurements. The intrinsic continuous knee passive stiffness and its fatigue responses both vary at specific knee angles. Our findings may provide stiffness assessment for knee osteoarthritis patients, complete fatigue intervention program, and optimize the artificial prosthesis design.
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Collecting large datasets for investigations into human locomotion is an expensive and labor-intensive process. Methods for 3D human pose estimation in the wild are becoming increasingly accurate and could soon be sufficient to assist with the collection of datasets for analysis into running kinematics from TV broadcast data. In the domain of biomechanical research, small differences in 3D angles play an important role. More precisely, the error margins of the data collection process need to be smaller than the expected variation between athletes. In this work, we propose a method to infer the global geometry of track and field stadium recordings using lane demarcations. By projecting estimated 3D skeletons back into the image using this global geometry, we show that current state-of-the-art 3D human pose estimation methods are not (yet) accurate enough to be used in kinematics research.
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Cinematography was used to biomechanically compare individually selected overground jogging and running velocities with equated treadmill jogging and running by adult males and females. All subjects were regular joggers but not competitive track or cross-country runners. No significant differences were recorded in stride length, stride rate, support time or non-support time for males or females when jogging at velocities of between 3.33 and 4.78 m/s (x = 3.70) or 3.45 and 4.80 m/s (x=3.97) respectively. However, it was demonstrated that at velocities of 4.82 - 6.2 m/s for males (x - 5.41) and 4.85 - 5.76 m/s for females (x = 5.29) significant differences did occur between overground and treadmill running. For both males and females stride length decreased, stride rate increased, and the period of non-support was also significantly less when running on a treadmill as compared to running overground.
The clinical objective of the gait analysis laboratory, developed by United Technologies Corporation (Hartford, CT, USA) in 1980, at the Newington Children's Hospital is to provide quantified assessments of human locomotion which assist in the orthopaedic management of various pediatric gait pathologies. The motion measurement system utilizes a video-based data collection strategy similar to commercially available systems for motion data collection. Anatomically aligned, passive, retroreflective markers placed on the subject are illuminated, detected, and stored in dedicated camera hardware while data are acquired from force platforms and EMG transducers. Three-dimensional marker position information is used to determine: (i) the orientation of segmentally-embedded coordinate systems, (ii) instantaneous joint center locations, and (iii) joint angles. Joint kinetics, i.e., moments and powers, may also be computed if valid force plate data are collected.
A simple external marker system and algorithms for computing lower extremity joint angle motion during level walking were developed and implemented on a computer-aided video motion analysis system (VICON). The concept of embedded axes and Euler rotation angles was used to define the three-dimensional joint angle motion based on a set of body surface markers. Gait analysis was performed on 40 normal young adults three times on three different test days at least 1 week apart using the marker system. Angular motion of the hip, knee, and ankle joints and of the pelvis were obtained throughout a gait cycle utilizing the three-dimensional trajectories of markers. The effect of uncertainties in defining the embedded axis on joint angles was demonstrated using sensitivity analysis. The errors in the estimation of joint angle motion were quantified with respect to the degree of error in the construction of embedded axes. The limitations of the model and the marker system in evaluating pathologic gait are discussed. The relatively small number of body surface markers used in the system render it easy to implement for use in routine clinical gait evaluations. Additionally, data presented in this paper should be a useful reference for describing and comparing pathologic gait patterns.
The purpose of this study was to investigate the influence of midsole hardness and running velocity on external impact forces in heel-toe running. Fourteen subjects were assessed with a force platform and high speed film while running at speeds of 3, 4, 5 and 6 m s-1. The result showed that running velocity does influence external impact force peaks (linear connection) and that midsole hardness does not influence magnitude and loading rate of the external vertical impact forces. Changes in kinematic and kinetic data can be used to explain this result mechanically. However, the neuromuscular control mechanisms to keep external impact forces constant are not known.
Selected variables were measured to examine differences in overground and treadmill running at sprinting speeds of maximal effort. Five college-varsity sprinters volunteered to run 100-yd sprints in both overground and treadmill running conditions. After a minimum of 10 training sessions on the treadmill, the subjects were filmed (75 fps) sprinting 100 yd and expired respiratory gases were collected during an 18-min recovery period. The oxygen debt of the overground condition, means = 47.86 ml X kg-1, was 36% greater than the treadmill running condition, means = 30.64 ml X kg-1. Regardless of individual running style, the major biomechanical differences between treadmill and overground running conditions occurred during the support phase and were observed in the supporting leg. During treadmill running, the leg of the supporting lower extremity was less erect at contact (means = 83.9 vs 88.3 deg) and moved through a greater range of motion (means = 60.6 vs 54.5 deg) with a faster overall angular velocity (means = 566.36 vs 478.07 deg X s-1). The thigh of the supporting lower extremity was more erect at contact (means = 67.1 vs 61.1 deg) and moved with a slower overall angular velocity (means = 435.14 vs 528.77 deg X s-1). Data suggest that the moving treadmill belt reduces the energy requirements of the runner by bringing the supporting leg back under the body during the support phase of running.
Several aspects of dynamic foot function were investigated using ground reaction forces obtained from five runners performing in five different shoes. A minimum of eight trials were necessary in order to obtain stable subject-condition values. Statistically significant subject-shoe interactions occurred for all parameters. It was therefore concluded that a knowledge of shoe characteristics independent of subject characteristics provided little useful information regarding the effects of the shoes tested on selected foot mechanics of the runners. The various subject-conditions were evaluated in an attempt to determine which was the best shoe. Selected descriptive data are presented and the 'best' shoe concept discussed.
The literature shows a wide difference of opinion about the mechanical equality of, or difference between treadmill and overground locomotion. This difference in opinion is often related to the coordinate system which implicitly or explicitly is used. With help of a few theoretical examples of energy calculations this paper shows that the description of treadmill locomotion with respect to a fixed coordinate system can lead to faulty conclusions. It is concluded that as long as the beltspeed is constant a coordinate system should be used which moves with the belt. In such a system no mechanical difference exists in comparison with overground locomotion with respect to a fixed coordinate system. All differences found in locomotion patterns must therefore originate from other than mechanical causes.
Treadmills are often used in research projects to simulate overground locomotion, assuming that locomotion is similar on a treadmill and overground. The purpose of this investigation was to determine whether a treadmill could be used to simulate overground locomotion. Twenty-two subjects ran on four different surfaces: overground and three treadmills that differed in size and power. The kinematics of the right leg and foot were studied using two high-speed Locam cameras (lateral and posterior view). The subjects ran in two different shoes at four different speeds (3.0-6.0 m.s-1). The differences in the kinematics between treadmill and overground running could be divided into systematic and subject dependent components. Subjects systematically planted their feet in a flatter position on the treadmill than overground. Most of the lower extremity kinematic variables, however, showed inconsistent trends for individual subjects, depending on the individual subject's running style, running speed, and shoe/treadmill situation. The differences were substantial. It is not yet understood how the human locomotor system adapts to a particular treadmill running situation. However, it is concluded that individual assessment of running kinematics on a treadmill for shoe or shoe orthotic assessment may possibly lead to inadequate conclusions about overground running.