1
The cumulative loads increase in the knee joint at slow-speed running compared with
2
faster running: A biomechanical study
3 4
Petersen, Jesper (PT, M.Sc.)1,2; Sørensen, Henrik (Ph.D.)1; Nielsen, Rasmus Oestergaard (PT,
5
Ph.D.)1,2
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
6 7 8
Affiliations: 1. Section of Sport Science, Department of Public Health, Aarhus University, DK-8000
9 10
Aarhus. 2. Orthopaedic Surgery Research Unit. Science and Innovation Center, Aalborg
11
University Hospital, DK-9000 Aalborg.
12 13
Corresponding author:
14
Mr. Jesper Petersen, Section of Sport Science, Department of Public Health, Faculty of
15
Health
16
E-mail: [email protected], Telephone: +45 40 40 48 70, Fax: None
Science, Aarhus
University,
Dalgas Avenue
4, DK-8000 Aarhus
C.,
17 18
The authors certify that they have no affiliations with or financial involvement in any
19
organization or entity with a direct financial interest in the subject matter or materials
20
discussed in the article.
21 22 23 24 25 1 2
1
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
26
Study Design: Biomechanical cross-sectional study.
27
Objective: To investigate the hypothesis that the cumulative load in the knee at a given
28
running distance is increased when running speed is decreased.
29
Background: The knee joint load per stride is decreased when running speed is decreased.
30
However, by decreasing running speed the number of strides per given distance is increased.
31
Running at a slower speed may increase the cumulative load at the knee joint at a given
32
distance compared with running the same distance at a higher speed, hence increasing the risk
33
of running-related injuries in the knee.
34
Methods: Kinematic and ground reaction force data were collected from 16 recreational
35
runners utilizing a rearfoot strike during steady-state running at 3 different speeds: 8.02 +/-
36
0.17 km/h, 11.79 +/- 0.21 km/h, and 15.78 +/- 0.22 km/h. Cumulative load (cumulative
37
impulse) over a 1000 meter distance was calculated at the knee joint on the basis of a
38
standard 3-dimensional inverse dynamics approach.
39
Results: Based on a 1000 meter running distance, the cumulative load at the knee was
40
significantly higher at slow running speed than at high running speed (relative difference:
41
80%). The mean load per stride at the knee increased significantly across all biomechanical
42
parameters, except impulse, following an increase in running speed.
43
Conclusion: Slow-speed running decreases knee joint loads per stride and increases the
44
cumulative load at the knee joint for a given running distance compared to faster running.
45
The primary reason for the increase in cumulative load at slower speeds is an increase in
46
number of strides needed to cover the same distance.
47 48
Key Words: running, biomechanics, injury, patellofemoral, tibiofemoral
49 50 3 4
2
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51
BACKGROUND
52
The injury rates vary from 0.8 to 38 injuries per 1000 hours of running based on the types of
53
runners.6, 7, 12, 14, 28 The knee joint, and especially its anterior region, is particularly vulnerable
54
to injuries like patellofemoral pain, patellar tendinopathy, and iliotibial band syndrome. 18 The
55
anterior knee region seems to be the anatomical location predominantly affected by running-
56
related injuries, followed by the lower leg. 27 This highlights the need for a better
57
understanding of the mechanisms leading to running-related injuries in the anterior part of the
58
knee.
59
Increased load in the anterior part of the knee during running may lead to an increased risk of
60
running-related injuries. Increases in knee extensor force likely result in higher soft-tissue
61
load and patellofemoral joint forces. Net joint moments are frequently used to estimate these
62
loads.3-5, 10, 13, 23, 25, 31 Several biomechanical studies have revealed a reduction in load at the
63
anterior part of the knee joint following an increase in step rate 17, a change of running style 1,
64
11, 26
65
In a more clinically-oriented framework, Nielsen et al 20 suggested that excessive mileage may
66
be associated with the development of patellofemoral pain, iliotibial band syndrome, and
67
patellar tendinopathy. The biomechanical rationale to support the assumption that injuries to
68
the anterior knee region are associated with excessive running distance was vaguely
69
described and remains, therefore, unknown. Possibly, the runner changes step rate pattern,
70
running style, shoes, or foot strike pattern while running excessive distances. An alternative
71
factor that may influence injury risk at excessive distances may be changes in running
72
speed.19 The evidence to support this assumption is however limited and must consider both
73
the loads for each stride as well as the cumulative loads for the distance covered.
, a change to a minimalistic running shoe 24, and a change to a forefoot strike 15, 30.
74
5 6
3
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
75
It has been shown that peak forces per stride developed by the vastus medialis, vastus
76
intermedius, and vastus lateralis increase following an increase in running speed from 3.5 m/s
77
to 5.2 m/s.10 In addition, Schache et al23 found knee joint power and work to increase with
78
increasing running speed. This might lead to the assumption that the load at the knee joint is
79
reduced if a runner completes a long-distance run at a lowered running speed. However, it is
80
important to consider the fact that a runner completes a number of strides (ie, loading cycles)
81
while running, and the number of strides depends on stride length, which itself is influenced
82
by running speed. Despite the observed decrease in load per stride at the knee joint when
83
running speed is decreased23, the corresponding increase in the number of strides required to
84
cover a given distance may offset the benefits of reducing load per stride. This suggests an
85
alternative hypothesis: that cumulative load at the knee joint is increased while running at a
86
lower running speed, because the increase in loading cycles may outweigh the benefits of
87
decreased load per stride. Therefore, the purpose of the present study was to investigate the
88
hypothesis that for a given running distance, the cumulative load at the knee joint is increased
89
following a decrease in running speed.
90 91
METHODS
92
Participants
93
A total of 33 recreational runners volunteered for the study. Runners were recruited from the
94
central Denmark region. They were eligible to participate if: 1) they utilized a rearfoot strike
95
while running, 2) they had been injury free (defined as a musculoskeletal injury in the lower
96
extremities) for the past 6 months, and 3) their personal best at a 5 kilometer distance was
97
slower than 17 min (speed = 17.65 km/h). All participants signed informed written consent.
98
The study was approved by the local ethics committee, Central Region, Denmark and
99
conducted in accordance with the ethical standards of the Declaration of Helsinki.
7 8
4
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
100 101
Instrumentation
102
The study was conducted at the Biomechanics Laboratory at Section for Sport Science,
103
Aarhus University. Kinematic data were collected using a 3-dimensional motion capture
104
system (Qualisys AB, Gothenburg, Sweden) with 8 Pro-Reflex MCU infrared high-speed
105
cameras operating at a sampling frequency of 240 Hz. After calibration the maximum
106
residual error was 2 mm, and the measurement volume was approximately 1 m x 1.5 m x 4
107
m. In addition to the kinematic measurements, ground reaction force data were collected at
108
960 Hz using a force plate (AMTI OR6-7, Advanced Medical Technology Inc., Watertown,
109
MA, USA) embedded in the floor in the center of an 18 m running track. The force plate was
110
covered with a thin carpet to conceal its location, thus preventing participants from altering
111
their step length to strike the plate. Running speeds were measured during each trial using 2
112
SpeedLight V2 (Swift Performance Equipment, Brisbane, Australia) wireless light gates
113
placed 3 meters apart before and after the force plate.
114 115
Procedure
116
Prior to testing, all participants were instrumented with 36 retro-reflective markers (19 mm
117
diameter) secured on specific anatomical locations on the pelvis, thighs, shanks, and feet.
118
Marker placement was conducted by a physiotherapist based on Visual 3D marker set
119
guidelines. Ten “tracking markers” were placed bilaterally on the following 5 locations:
120
anterior superior iliac spine, posterior superior iliac spine, head of 2 nd metatarsal, head of 5th
121
metatarsal, and posterior surface of calcaneus. An additional 4 lightweight rigid plastic shells,
122
each with a cluster of 4 retro-reflective markers were attached to the lateral surfaces of the
123
thighs and shanks to track motion of these segments. Ten additional “static markers,” used for
124
segment definition and joint center estimation, were placed on the greater trochanter, medial
9 10
5
125
and lateral femoral condyles, and medial and lateral malleolus of both lower limbs. The rigid
126
shells with cluster marker sets were attached to the body with elastic velcro straps and further
127
secured with elastic bandage, while all other markers were attached directly to the body with
128
double-sided adhesive tape.
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
129 130
For testing, the participants wore tight running clothes and their own conventional running
131
shoes so as to not alter their natural running. A static trial was collected with the participant
132
standing on the force plate with arms folded across the chest (to avoid covering any markers).
133
The “static markers” were then removed, and testing continued with the running trials. Data
134
were collected at the following running speeds: 8 km/h, 12 km/h, and 16 km/h. For practical
135
reasons, the order of running speeds were chosen to be incremental rather than randomized.
136
No specific warm-up was performed, as this was provided in the first few trials at the slow
137
speed. Participants were instructed to maintain a constant speed across the entire measuring
138
volume. After each trial the participant received feedback with the aim of achieving the
139
desired running speed. As the force plate was concealed by a thin carpet, the tester altered the
140
starting position of each participant as needed to get a valid foot strike on the force plate. The
141
side to be measured, right or left lower extremity, was randomly chosen prior to the testing of
142
each participant. Running trials were repeated until the participant had 3 valid foot strikes on
143
the force plate, while running within ± 5 % of the desired speed, for each of the running
144
speeds. All 33 participants completed the running trials and maintained a rearfoot strike
145
pattern during all running speeds.
146 147 148 149
11 12
6
150
Data Analyses
151
Qualisys Track Manager (Qualisys AB, Gothenburg, Sweden) software was used to collect
152
the kinematic data and determine the 3-dimensional position of each marker. Further data
153
processing was conducted using Visual 3D (C-Motion, Inc., Germantown, USA).
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
154 155
The first step in the analysis was to verify that all runners were running at a steady constant
156
running speed when passing through the measurement volume. This was verified by
157
comparing the running speed just before the force plate with the running speed just after the
158
force plate. Running speed was calculated from motion capture data as the speed of the
159
midpoint between the 2 anterior superior iliac spine markers. While very small variations
160
were observed, on average, the participants maintained a constant speed.
161 162
Using Visual 3D, data from the static standing trial combined with the mass and height of the
163
participant was used to create a static/hybrid skeletal model. The pelvis segment was created
164
as Visual 3D’s “Coda Pelvis”, and the hip joint center was estimated using the equation
165
determined by Bell et al. 2 The thigh, shank, and foot segments were created as “Thigh model
166
2”, “Shank model 1”, and a 1-segment foot. The knee joint center and ankle joint center were
167
defined as the midpoint between the medial and lateral femoral condyle markers and the
168
midpoint between the medial and lateral malleoli markers, respectively. In the subsequent
169
analyses each body segment was treated as a 6-degree-of-freedom model.
170 171
The kinematic and ground reaction force data were then low-pass filtered with a fourth order
172
Butterworth filter with a cut-off frequency of 8 Hz. A standard 3-dimensional inverse
173
dynamics method based on Newton-Euler equations was then used to quantify the moments
13 14
7
174
acting on the knee joint. Moment data for each participant were normalized by dividing by
175
body mass to enable comparison with results obtained in similar studies previously published.
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
176 177
For each participant, 3 trials at each of the 3 running speeds were included in the data
178
analyses. Stride length was calculated as the distance between heel marker position at 2
179
consecutive ipsilateral heel strikes. Detection of heel strike number 2 was based on kinematic
180
data. An automatic detection algorithm in Visual 3D detects the angle of the foot as well as
181
the speed and vertical position of the heel marker during heel strike 1 (on the force plate).
182
When a similar pattern is detected again, this is classified as ipsilateral heel strike number 2.
183
We also calculated 6 variables related to joint load: peak moment, impulse, peak power
184
(absorption and generation), and work (positive and negative) (FIGURE 1). For each running
185
speed, each of the joint load parameters was calculated per stride. Further, cumulative load
186
(cumulative impulse) was calculated by multiplying the impulse per stride with the number of
187
strides needed to complete a 1000 m distance. The cumulative load at a given running
188
distance is calculated by multiplying the load per stride by the number of strides to cover the
189
defined distance. For the cumulative load to decrease following an increase in running speed,
190
the decrease in number of strides per distance must outweigh the corresponding increase in
191
load per stride.
192 193
A relatively small measuring volume and relatively long stride length at the highest running
194
speed (16 km/h) made it impossible to determine stride length in some of the running trials.
195
Because of this, 17 runners were excluded post-hoc. Demographic characteristics and stride
196
lengths of the remaining 16 runners are presented in TABLE 1. Data from this study has been
197
used in another published study 22.
198
15 16
8
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199
Statistical Analyses
200
Because all participants ran at 8, 12, and 16 km/h and there were no missing values, a random
201
coefficient model allowing for repeated measurement was used. For each parameter, we
202
tested if the development of the load per stride or the cumulative load across the 3 speeds
203
were significantly different than zero. The model was validated by testing for equal standard
204
deviations, by evaluating the correlation of joint load as running speed increases, and by
205
visualizing the residuals in a quartile-quartile plot. All statistical analyses were performed
206
using Stata (Stata/IC 12.0, StataCorp, Texas, USA) and results were considered statistically
207
significant if P
The cumulative loads increase in the knee joint at slow-speed running compared with
2
faster running: A biomechanical study
3 4
Petersen, Jesper (PT, M.Sc.)1,2; Sørensen, Henrik (Ph.D.)1; Nielsen, Rasmus Oestergaard (PT,
5
Ph.D.)1,2
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
6 7 8
Affiliations: 1. Section of Sport Science, Department of Public Health, Aarhus University, DK-8000
9 10
Aarhus. 2. Orthopaedic Surgery Research Unit. Science and Innovation Center, Aalborg
11
University Hospital, DK-9000 Aalborg.
12 13
Corresponding author:
14
Mr. Jesper Petersen, Section of Sport Science, Department of Public Health, Faculty of
15
Health
16
E-mail: [email protected], Telephone: +45 40 40 48 70, Fax: None
Science, Aarhus
University,
Dalgas Avenue
4, DK-8000 Aarhus
C.,
17 18
The authors certify that they have no affiliations with or financial involvement in any
19
organization or entity with a direct financial interest in the subject matter or materials
20
discussed in the article.
21 22 23 24 25 1 2
1
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
26
Study Design: Biomechanical cross-sectional study.
27
Objective: To investigate the hypothesis that the cumulative load in the knee at a given
28
running distance is increased when running speed is decreased.
29
Background: The knee joint load per stride is decreased when running speed is decreased.
30
However, by decreasing running speed the number of strides per given distance is increased.
31
Running at a slower speed may increase the cumulative load at the knee joint at a given
32
distance compared with running the same distance at a higher speed, hence increasing the risk
33
of running-related injuries in the knee.
34
Methods: Kinematic and ground reaction force data were collected from 16 recreational
35
runners utilizing a rearfoot strike during steady-state running at 3 different speeds: 8.02 +/-
36
0.17 km/h, 11.79 +/- 0.21 km/h, and 15.78 +/- 0.22 km/h. Cumulative load (cumulative
37
impulse) over a 1000 meter distance was calculated at the knee joint on the basis of a
38
standard 3-dimensional inverse dynamics approach.
39
Results: Based on a 1000 meter running distance, the cumulative load at the knee was
40
significantly higher at slow running speed than at high running speed (relative difference:
41
80%). The mean load per stride at the knee increased significantly across all biomechanical
42
parameters, except impulse, following an increase in running speed.
43
Conclusion: Slow-speed running decreases knee joint loads per stride and increases the
44
cumulative load at the knee joint for a given running distance compared to faster running.
45
The primary reason for the increase in cumulative load at slower speeds is an increase in
46
number of strides needed to cover the same distance.
47 48
Key Words: running, biomechanics, injury, patellofemoral, tibiofemoral
49 50 3 4
2
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
51
BACKGROUND
52
The injury rates vary from 0.8 to 38 injuries per 1000 hours of running based on the types of
53
runners.6, 7, 12, 14, 28 The knee joint, and especially its anterior region, is particularly vulnerable
54
to injuries like patellofemoral pain, patellar tendinopathy, and iliotibial band syndrome. 18 The
55
anterior knee region seems to be the anatomical location predominantly affected by running-
56
related injuries, followed by the lower leg. 27 This highlights the need for a better
57
understanding of the mechanisms leading to running-related injuries in the anterior part of the
58
knee.
59
Increased load in the anterior part of the knee during running may lead to an increased risk of
60
running-related injuries. Increases in knee extensor force likely result in higher soft-tissue
61
load and patellofemoral joint forces. Net joint moments are frequently used to estimate these
62
loads.3-5, 10, 13, 23, 25, 31 Several biomechanical studies have revealed a reduction in load at the
63
anterior part of the knee joint following an increase in step rate 17, a change of running style 1,
64
11, 26
65
In a more clinically-oriented framework, Nielsen et al 20 suggested that excessive mileage may
66
be associated with the development of patellofemoral pain, iliotibial band syndrome, and
67
patellar tendinopathy. The biomechanical rationale to support the assumption that injuries to
68
the anterior knee region are associated with excessive running distance was vaguely
69
described and remains, therefore, unknown. Possibly, the runner changes step rate pattern,
70
running style, shoes, or foot strike pattern while running excessive distances. An alternative
71
factor that may influence injury risk at excessive distances may be changes in running
72
speed.19 The evidence to support this assumption is however limited and must consider both
73
the loads for each stride as well as the cumulative loads for the distance covered.
, a change to a minimalistic running shoe 24, and a change to a forefoot strike 15, 30.
74
5 6
3
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
75
It has been shown that peak forces per stride developed by the vastus medialis, vastus
76
intermedius, and vastus lateralis increase following an increase in running speed from 3.5 m/s
77
to 5.2 m/s.10 In addition, Schache et al23 found knee joint power and work to increase with
78
increasing running speed. This might lead to the assumption that the load at the knee joint is
79
reduced if a runner completes a long-distance run at a lowered running speed. However, it is
80
important to consider the fact that a runner completes a number of strides (ie, loading cycles)
81
while running, and the number of strides depends on stride length, which itself is influenced
82
by running speed. Despite the observed decrease in load per stride at the knee joint when
83
running speed is decreased23, the corresponding increase in the number of strides required to
84
cover a given distance may offset the benefits of reducing load per stride. This suggests an
85
alternative hypothesis: that cumulative load at the knee joint is increased while running at a
86
lower running speed, because the increase in loading cycles may outweigh the benefits of
87
decreased load per stride. Therefore, the purpose of the present study was to investigate the
88
hypothesis that for a given running distance, the cumulative load at the knee joint is increased
89
following a decrease in running speed.
90 91
METHODS
92
Participants
93
A total of 33 recreational runners volunteered for the study. Runners were recruited from the
94
central Denmark region. They were eligible to participate if: 1) they utilized a rearfoot strike
95
while running, 2) they had been injury free (defined as a musculoskeletal injury in the lower
96
extremities) for the past 6 months, and 3) their personal best at a 5 kilometer distance was
97
slower than 17 min (speed = 17.65 km/h). All participants signed informed written consent.
98
The study was approved by the local ethics committee, Central Region, Denmark and
99
conducted in accordance with the ethical standards of the Declaration of Helsinki.
7 8
4
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
100 101
Instrumentation
102
The study was conducted at the Biomechanics Laboratory at Section for Sport Science,
103
Aarhus University. Kinematic data were collected using a 3-dimensional motion capture
104
system (Qualisys AB, Gothenburg, Sweden) with 8 Pro-Reflex MCU infrared high-speed
105
cameras operating at a sampling frequency of 240 Hz. After calibration the maximum
106
residual error was 2 mm, and the measurement volume was approximately 1 m x 1.5 m x 4
107
m. In addition to the kinematic measurements, ground reaction force data were collected at
108
960 Hz using a force plate (AMTI OR6-7, Advanced Medical Technology Inc., Watertown,
109
MA, USA) embedded in the floor in the center of an 18 m running track. The force plate was
110
covered with a thin carpet to conceal its location, thus preventing participants from altering
111
their step length to strike the plate. Running speeds were measured during each trial using 2
112
SpeedLight V2 (Swift Performance Equipment, Brisbane, Australia) wireless light gates
113
placed 3 meters apart before and after the force plate.
114 115
Procedure
116
Prior to testing, all participants were instrumented with 36 retro-reflective markers (19 mm
117
diameter) secured on specific anatomical locations on the pelvis, thighs, shanks, and feet.
118
Marker placement was conducted by a physiotherapist based on Visual 3D marker set
119
guidelines. Ten “tracking markers” were placed bilaterally on the following 5 locations:
120
anterior superior iliac spine, posterior superior iliac spine, head of 2 nd metatarsal, head of 5th
121
metatarsal, and posterior surface of calcaneus. An additional 4 lightweight rigid plastic shells,
122
each with a cluster of 4 retro-reflective markers were attached to the lateral surfaces of the
123
thighs and shanks to track motion of these segments. Ten additional “static markers,” used for
124
segment definition and joint center estimation, were placed on the greater trochanter, medial
9 10
5
125
and lateral femoral condyles, and medial and lateral malleolus of both lower limbs. The rigid
126
shells with cluster marker sets were attached to the body with elastic velcro straps and further
127
secured with elastic bandage, while all other markers were attached directly to the body with
128
double-sided adhesive tape.
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
129 130
For testing, the participants wore tight running clothes and their own conventional running
131
shoes so as to not alter their natural running. A static trial was collected with the participant
132
standing on the force plate with arms folded across the chest (to avoid covering any markers).
133
The “static markers” were then removed, and testing continued with the running trials. Data
134
were collected at the following running speeds: 8 km/h, 12 km/h, and 16 km/h. For practical
135
reasons, the order of running speeds were chosen to be incremental rather than randomized.
136
No specific warm-up was performed, as this was provided in the first few trials at the slow
137
speed. Participants were instructed to maintain a constant speed across the entire measuring
138
volume. After each trial the participant received feedback with the aim of achieving the
139
desired running speed. As the force plate was concealed by a thin carpet, the tester altered the
140
starting position of each participant as needed to get a valid foot strike on the force plate. The
141
side to be measured, right or left lower extremity, was randomly chosen prior to the testing of
142
each participant. Running trials were repeated until the participant had 3 valid foot strikes on
143
the force plate, while running within ± 5 % of the desired speed, for each of the running
144
speeds. All 33 participants completed the running trials and maintained a rearfoot strike
145
pattern during all running speeds.
146 147 148 149
11 12
6
150
Data Analyses
151
Qualisys Track Manager (Qualisys AB, Gothenburg, Sweden) software was used to collect
152
the kinematic data and determine the 3-dimensional position of each marker. Further data
153
processing was conducted using Visual 3D (C-Motion, Inc., Germantown, USA).
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at University of Ulster Library on January 16, 2015. For personal use only. No other uses without permission. Copyright © ${year} Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
154 155
The first step in the analysis was to verify that all runners were running at a steady constant
156
running speed when passing through the measurement volume. This was verified by
157
comparing the running speed just before the force plate with the running speed just after the
158
force plate. Running speed was calculated from motion capture data as the speed of the
159
midpoint between the 2 anterior superior iliac spine markers. While very small variations
160
were observed, on average, the participants maintained a constant speed.
161 162
Using Visual 3D, data from the static standing trial combined with the mass and height of the
163
participant was used to create a static/hybrid skeletal model. The pelvis segment was created
164
as Visual 3D’s “Coda Pelvis”, and the hip joint center was estimated using the equation
165
determined by Bell et al. 2 The thigh, shank, and foot segments were created as “Thigh model
166
2”, “Shank model 1”, and a 1-segment foot. The knee joint center and ankle joint center were
167
defined as the midpoint between the medial and lateral femoral condyle markers and the
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midpoint between the medial and lateral malleoli markers, respectively. In the subsequent
169
analyses each body segment was treated as a 6-degree-of-freedom model.
170 171
The kinematic and ground reaction force data were then low-pass filtered with a fourth order
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Butterworth filter with a cut-off frequency of 8 Hz. A standard 3-dimensional inverse
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dynamics method based on Newton-Euler equations was then used to quantify the moments
13 14
7
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acting on the knee joint. Moment data for each participant were normalized by dividing by
175
body mass to enable comparison with results obtained in similar studies previously published.
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For each participant, 3 trials at each of the 3 running speeds were included in the data
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analyses. Stride length was calculated as the distance between heel marker position at 2
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consecutive ipsilateral heel strikes. Detection of heel strike number 2 was based on kinematic
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data. An automatic detection algorithm in Visual 3D detects the angle of the foot as well as
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the speed and vertical position of the heel marker during heel strike 1 (on the force plate).
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When a similar pattern is detected again, this is classified as ipsilateral heel strike number 2.
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We also calculated 6 variables related to joint load: peak moment, impulse, peak power
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(absorption and generation), and work (positive and negative) (FIGURE 1). For each running
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speed, each of the joint load parameters was calculated per stride. Further, cumulative load
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(cumulative impulse) was calculated by multiplying the impulse per stride with the number of
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strides needed to complete a 1000 m distance. The cumulative load at a given running
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distance is calculated by multiplying the load per stride by the number of strides to cover the
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defined distance. For the cumulative load to decrease following an increase in running speed,
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the decrease in number of strides per distance must outweigh the corresponding increase in
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load per stride.
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A relatively small measuring volume and relatively long stride length at the highest running
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speed (16 km/h) made it impossible to determine stride length in some of the running trials.
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Because of this, 17 runners were excluded post-hoc. Demographic characteristics and stride
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lengths of the remaining 16 runners are presented in TABLE 1. Data from this study has been
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used in another published study 22.
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15 16
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Statistical Analyses
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Because all participants ran at 8, 12, and 16 km/h and there were no missing values, a random
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coefficient model allowing for repeated measurement was used. For each parameter, we
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tested if the development of the load per stride or the cumulative load across the 3 speeds
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were significantly different than zero. The model was validated by testing for equal standard
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deviations, by evaluating the correlation of joint load as running speed increases, and by
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visualizing the residuals in a quartile-quartile plot. All statistical analyses were performed
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using Stata (Stata/IC 12.0, StataCorp, Texas, USA) and results were considered statistically
207
significant if P
