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The problem of Achilles tendon overuse-related injuries isunresolved for athletes, especially for habitual runners who areexposed to high injury rates. Considering such injuries initiateunilaterally and are suggested to occur due to overloading, inter-limb differences occurring during running might be a possible linkto its etiology. Current knowledge on inter-limb differences duringrunning and on the bilateral muscle-tendon characteristics ofhabitual runners might provide directions to preventive strategiesdesigned by coaches and clinicians.
This thesis present four articles in which bilateral evaluations wereconducted in habitual runners. In Study I triathletes were evaluatedduring running after cycling while kinetic, kinematic andneuromuscular variables previously associated to Achilles tendoninjury were analyzed bilaterally. In Study II, a similar approach wasused while habitual runners running at two submaximal runningspeeds were investigated. In Study III, variables associated to limbstiffness and center of mass kinematics were analyzed bilaterally atthe same speeds adopted in Study II. In Study IV, theneuromechanical and tendon properties of habitual runners wereevaluated bilaterally during isometric contractions.
Sport and all-kind-of-movement-skills lover. Obtained his master'sdegree in Human MovementSciences at the Federal Universityof Rio Grande do Sul, Brazil whileworking on the effects of cyclingand running on plantarflexor'selastic components. His doctoralproject on bilateral biomechanics ofhabitual runners was granted by theBrazilian Council for Scientific andTechnological Development(CNPq). In 2016 started working asa PhD student at the SwedishSchool of Sport and HealthSciences on his doctoral project.
ISBN 978-91-986490-0-0
Tiago C Jacques
TIA
GO
C JA
CQ
UE
SB
ilateral kinetic, kinematic, neurom
echanical and2021
Doctoral Thesis at GIH - The Swedish School of Sport and Health Sciences
Bilateral kinetic, kinematic,neuromechanical and muscle-tendonproperties of habitual runnersTIAGO C JACQUES
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A v h a n d l i n g s s e r i e f ö r
G y m n a s t i k - o c h i d r o t t s h ö g s k o l a n
Nr 19
BILATERAL KINETIC, KINEMATIC, NEUROMECHANICAL AND
MUSCLE-TENDON PROPERTIES OF HABITUAL RUNNERS
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3
Bilateral kinetic, kinematic, neurome-chanical, and muscle-tendon proper-ties of habitual runners
Tiago Canal Jacques
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©Tiago Canal Jacques Gymnastik- och idrottshögskolan 2021 ISBN 978-91-986490-0-0 Tryckeri: Universitetsservice US-AB, Stockholm 2021 Distributör: Gymnastik- och idrottshögskolan
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“Il bene si fa, ma non si dice. E
certe medaglie si appendono
all’anima, non alla giacca.”
Gino Bartali
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ABSTRACT
Achilles tendon overuse-related injuries are a frequent problem to habitual runners.
Such injuries occur more often unilaterally and its etiology is associated to overloading
of the tendon tissue. Inter-limb differences during running are a possible cause for over-
load due to eventual differences in the mechanical loading provided to each limb. Fur-
thermore, inter-limb differences in Achilles tendon properties were found in athletes due
to sport-induced differences in the mechanical loading and in non-athletes due to limb
preference. Currently, inter-limb differences in the Achilles properties of habitual run-
ners is unknown. The present thesis investigated the existence of inter-limb differences
in biomechanical, neuromechanical and Achilles tendon properties in habitual runners.
In Study I, thirteen triathletes performed a cycle-run simulation while vertical ground
reaction force (GRFv), lower limb kinematics and triceps surae and tibialis anterior acti-
vation were evaluated bilaterally during the start, mid and end stages of the 5 km run-
ning segment. In Study II, GRFv, lower limb kinematics, triceps surae and tibialis ante-
rior activation and Achilles tendon strain were evaluated bilaterally in habitual runners
at two running speeds (2.7 m.s-1 and 4.2 m.s-1). In Study III, spatiotemporal variables,
vertical (kVert) and limb (kLimb) stiffness and center of mass (COM) kinematics were
evaluated bilaterally in habitual runners at the same running speeds adopted in Study II.
In Study IV, maximal plantarflexion isometric force, triceps surae activation and activa-
tion ratios, and Achilles tendon morphological, mechanical and material properties were
evaluated bilaterally in habitual runners. In Study I the Soleus activation was lower in
the preferred limb from 53.4% to 75.89% of the stance phase (p<0.01, ES range = 0.59
to 0.80) at the end stage of running. In Study II, hip extension velocity was greater in
the non-preferred limb from 71% to 93% of the stance phase (p<0.01) during running at
4.2 m.s-1 while no other inter-limb differences were observed. In Study III, no inter-limb
differences were observed in spatiotemporal, kVert and kLimb at investigated running
speeds. However, COM horizontal velocity was greater from 67% to 87.40% of stance
the phase (p<0.05, ES >0.60) when the non-preferred limb was in contact with the
ground. In Study IV, no inter-limb differences were observed in triceps surae activation
or Achilles tendon properties. The activation ratios of MG and SOL, however, were ob-
served to correlate in the preferred limb only.
In summary, neuromuscular and kinematic inter-limb differences were observed when
healthy, non-injured habitual runners performed in running conditions similar to their
8
ecological conditions. Moreover, the Achilles tendon seem to adapt similarly among
limbs of habitual runners, while triceps surae activation strategies might differ between
limbs. Findings of inter-limb differences occurring during running may result in over-
load during running and therefore might be implicated in the etiology of Achilles tendon
overuse-related injuries in habitual runners. Findings of similar tendon properties
among limbs suggest both limbs have similar chances of incurring in the injury process.
Coaches and clinicians might improve current preventive strategies for Achilles tendon
overuse-related injuries by monitoring tendon properties and running biomechanical and
neuromuscular variables bilaterally across the season.
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LIST OF SCIENTIFIC ARTICLES
This thesis is based on the following original manuscripts:
I Jacques T, Bini R, Arndt A. (2021) Running after cycling induces inter-
limb differences in muscle activation but not in kinetics or kinematics.
Journal of Sports Sciences, 39(2):154-160.
https://doi.org/10.1080/02640414.2020.1809176.
II Jacques T, Bini R, Arndt A. Inter-limb differences in vivo tendon behav-
ior, kinematics, kinetics and muscle activation during running. Submitted
to the Journal of Biomechanics. Under review.
III Jacques T, Bini R, Arndt A. Bilateral investigation of spatiotemporal vari-
ables, vertical and limb stiffness, and center of mass kinematics during
submaximal running. Manuscript under preparation for submission to the
Gait & Posture journal.
IV Jacques T, Bini R, Arndt A. Bilateral in vivo neuromechanical properties
of the triceps surae and Achilles tendon in runners and triathletes. Ac-
cepted for publication in the Journal of Biomechanics on 23rd April 2021.
https://doi.org/10.1016/j.jbiomech.2021.110493
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TABLE OF CONTENTS
1 INTRODUCTION ...................................................................................................... 15 1.1 Background ................................................................................................................................ 15 1.2 Bilateral lower limb biomechanics during running .................................................................... 15 1.3 Running biomechanics and tendon overuse injuries ................................................................... 18 1.4 External and internal loading ..................................................................................................... 20 1.5 Achilles tendon loading, properties and structure ...................................................................... 20
1.5.1 Structure ............................................................................................................................ 20 1.5.2 Morphological, mechanical and material properties .......................................................... 21 1.5.3 Adaptation to load ............................................................................................................. 22
1.6 Analysis of continuous data ....................................................................................................... 22
2 AIMS .......................................................................................................................... 24
3 METHODS ................................................................................................................. 25 3.1 Subjects and study designs ......................................................................................................... 25 3.2 Testing protocols ........................................................................................................................ 27
Bilateral evaluation during a cycle-run simulation ..................................................................... 27 3.2.1 Bilateral evaluation during treadmill running .................................................................... 28 3.2.2 Bilateral evaluation during isometric contractions ............................................................ 28 3.2.3 Limb preference ................................................................................................................ 28
3.3 Equipment and procedures ......................................................................................................... 28 3.3.1 Ground reaction force........................................................................................................ 28 3.3.2 Motion capture .................................................................................................................. 29 3.3.3 Maximal isometric torque assessment ............................................................................... 29 3.3.4 Moment arm assessment ................................................................................................... 30 3.3.5 Cross-sectional area assessment ........................................................................................ 31 3.3.6 Muscle-tendon junction displacement ............................................................................... 31 3.3.7 Electromyography ............................................................................................................. 31
3.4 Data analysis .............................................................................................................................. 32 3.4.1 Ground reaction force........................................................................................................ 32 3.4.2 Kinematics ........................................................................................................................ 32 3.4.3 Limb and vertical stiffness ................................................................................................ 33 3.4.4 Tendon length and strain during running ........................................................................... 34 3.4.5 Moment-arm...................................................................................................................... 35 3.4.6 Cross-sectional area .......................................................................................................... 35 3.4.7 Tendon force and stress ..................................................................................................... 36 3.4.8 Tendon rest length, length and strain ................................................................................. 36 3.4.9 Tendon stiffness and modulus of elasticity........................................................................ 36
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3.4.10 Electromyography ........................................................................................................... 37 3.5 Statistical analysis ...................................................................................................................... 37
4 RESULTS ................................................................................................................... 38
5 METHODOLOGICAL CONSIDERATIONS ............................................................ 48 5.1 Cycle-run simulation, treadmill run and fatigue ......................................................................... 48 5.2 Kinetics ...................................................................................................................................... 48 5.3 Kinematics ................................................................................................................................. 48 5.4 Electromyography ...................................................................................................................... 49 5.5 In vivo estimations ..................................................................................................................... 50 5.6 Limb preference assessment ....................................................................................................... 50
6 DISCUSSION ............................................................................................................. 51 6.1 Inter-limb differences during running after cycling.................................................................... 51 6.2 Inter-limb differences during submaximal running .................................................................... 52 6.3 Bilateral neuromuscular and tendon properties .......................................................................... 53 6.4 Implications to overuse-related tendon injury ............................................................................ 54 6.5 Strengths and limitations ............................................................................................................ 56 6.6 Ethical considerations ................................................................................................................ 57 6.7 Conclusions ................................................................................................................................ 57
7 FUTURE DIRECTIONS ............................................................................................ 58
8 SAMMANFATTNING............................................................................................... 60
9 ACKNOWLEDGMENTS .......................................................................................... 62
10 REFERENCES ......................................................................................................... 63
APPENDIX .................................................................................................................... 71
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ABBREVIATIONS
∆COM Center of mass displacement
∆Limb Limb displacement
AT Achilles tendon
COMhoriz Horizontal position or velocity of the center of mass
COMvert Vertical position or velocity of the center of mass
COPAP Anterior-posterior displacement of the center of pressure
CSA Cross-sectional area
EMG Electromyography
Fmax Maximal force
g Gravitational acceleration
GRF Ground reaction force
kLimb Limb stiffness
kVert Vertical stiffness
L Limb length
LG Lateral gastrocnemius
m Body mass
m.s-1 Meters per second
MA Moment arm
MG Medial gastrocnemius
MG-MTJ Medial gastrocnemius muscle-tendon junction
mm Millimeters
SOL Soleus
TA Tibialis anterior
Tc Contact time
Tf Flight time
v Running speed
Wb Body weight
π Pi
15
1 INTRODUCTION
1.1 Background
High rates of Achilles tendon (AT) overuse-related injuries are observed among the run-
ning population [1-5], although its etiology are poorly understood. Biomechanical and
neuromuscular variables were associated to AT injury occurrence [6-15], but uncer-
tainty exist on whether these are cause or consequence of injury. Studies have focused
on inter-limb differences during running since they have been associated to increased
injury risk [16, 17], although variables related to internal loading of the AT were not in-
vestigated bilaterally. Considering excessive loading is suggested to result in tendon tis-
sue damage [18-21] and AT overuse injuries occur more often unilaterally [22], inter-
limb differences occurring during running requires further investigation. Moreover, in-
ter-limb differences were found in athletes and non-athletes due to sport-mediated inter-
limb differences in the mechanical loading [23-25] or due to the preferential use of a
given limb during daily life activities [26-28]. Currently there is no information regard-
ing if inter-limb differences exists in bilateral muscle and tendon properties of habitual
runners. The present thesis adopted experimental designs aimed to fill the above men-
tioned gaps. Directions to coaches and clinicians on possible strategies to prevent or
treat AT overuse-related injuries in habitual runners would arise from such investiga-
tion.
1.2 Bilateral lower limb biomechanics during running
Inter-limb differences have been investigated during running [17, 29-33] since they
could result in greater mechanical loading being experienced by one limb during train-
ing and competition. A larger loading of a given limb would make it more susceptible to
overloading, which has been associated to musculoskeletal overuse injuries [20, 34]. A
summary of studies focused on the effects of running speed on biomechanical inter-limb
differences is presented in Table 1. Kinetic and kinematic variables were investigated at
16
speeds below 5 m.s-1 (Table 1). The majority of these studies investigated a few sub-
maximal speeds and focused on summarized metrics such as average or peak values ex-
tracted from the investigated biomechanical continuums (Table 1).
Previous studies on inter-limb differences (Table 1) investigated kinetics and kinematics
separately, limiting insights on the relationship between those variables. Furthermore,
the majority of studies investigating inter-limb differences in running adopted a side-to-
side limb classification, while functional classifications (e.g. dominant vs. non-domi-
nant, preferred vs. non-preferred) were much less adopted (Table 1). Although func-
tional classification methods adopted in the literature differ between studies, the side-to-
side limb comparison may limit comparisons considering functional roles lower limbs
are thought to play during locomotion [35-40].
Finally, the investigation of inter-limb differences during running have previously been
limited to runners, therefore not including other habitual runners also exposed to high
running training volumes such as triathletes. In this regard, triathletes represent a special
case in the running population since during racing they run immediately after cycling
[41-44]. The literature provides evidence for effects from prior cycling on subsequent
running biomechanics [41-44], and evidence for inter-limb biomechanical differences
occurring during cycling [45, 46]. However, investigations are lacking on possible bio-
mechanical inter-limb differences during running preceded by cycling.
17
Table 1. Summary of published studies on the effects of running speed on inter-limb biomechanical differences during running.
Study Sample
size Experience / Sex
Dependent
variable Surface/Speed Analysis
Limb classifi-
cation /
Method
Outcome
Hamill et al.
1984 5
Non-runners / 8
Males, 2 Females GRF Track / 4.87 m.s-1
Summarized
metrics
P-NP / kicking
limb
No differ-
ence
Williams et al.
1987 14
Elite runners / Fe-
male GRF Track / 5.36 m.s-1
Summarized
metrics Right-left
No limb-
specific
Karamanidis
et al. 2003 12
Long-distance
runners / Female
Joint kine-
matics
Treadmill / 2.5, 3
and 3.5 m.s-1
Summarized
metrics Right-left
No limb-
specific
Zifchock et al.
2006 24-25
Not-specified / Fe-
male GRF Track / 3.7 m.s-1
Summarized
metrics Right-left
No differ-
ence
Pappas et al.
2015 22
Non-runners
/Male GRF
Treadmill / 2.22
m.s-1
Summarized
metrics
D-ND / forward
jumping test
Greater in
the D
Hughes-Oliver
et al. 2019 20 Runners/Male
Joint kine-
matics Track / 3.35 m.s-1
Summarized/time-
varying metrics
D-ND / not
specified
No differ-
ence
GRF = ground reaction force; P = preferred limb; NP = non-preferred limb; D = dominant limb; ND = non-dominant limb.
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1.3 Running biomechanics and tendon overuse injuries
AT overuse-related injuries are a frequent problem for habitual runners such as triath-
letes [3, 5] and runners [1, 2]. High training loads and improper recovery time between
training sessions may result in inadequate tendon cellular matrix response, leading to a
weakened tendon structure that may limit tendon remodeling [18-21]. Cross-sectional
and prospective studies observed associations between biomechanical and neuromuscu-
lar variables in AT overuse injury. For example, GRF [6], anterior-posterior displace-
ment of the center of pressure [10], lower limb kinematics [8, 9, 12], and limb stiffness
[13, 14] were all associated to the occurrence of AT overuse injury. Regarding neuro-
muscular variables, EMG timing [11], EMG amplitude [7, 47], and the relative contri-
bution of each muscle to total triceps surae normalized activation [47, 48] were also as-
sociated to the occurrence of AT overuse injury. Furthermore, excessive tendon strain
(e.g. tendon deformation) was found to be detrimental to tendon health [49-51] and to
be greater in individuals sustaining AT overuse injury [52]. A summary of studies in-
vestigating the association between biomechanical and neuromuscular variables and AT
overuse injury can be found in Table 2.
19
Table 2. Summary of published studies showing association between biomechanical variables and Achilles tendon overuse-related injuries.
Study Sample
size Experience / Sex Surface / Speed Dependent variable Design
Donoghue et al. 2008 12-22 Non-runners / mixed Treadmill / 2.8 m.s-1 Ankle kinematics Cross-sec-
tional
Donoghue et al. 2008, Azevedo et al. 2009
21-24 Runners, non-runners /
mixed Runway-Treadmill /
2.8 - 2.97 m.s-1 Knee kinematics
Cross-sec-tional
Van Ginckel et al. 2009 129 Novice runners / 19 males, 110 females
Runway GRF, COP Prospective
Baur et al. 2011 30 Runners / mixed Treadmill / 3.3 m.s-1 EMG Cross-sec-
tional
Munteanu et al. 2011 - Mixed Mixed GRF, COP, knee and
ankle kinematics Systematic
review
Wyndow et al. 2013 Non-runners / males Track / 4 m.s-1 EMG Cross-sec-
tional
Davis et al. 2015 249 Runners / females Runway / 3.7 m.s-1 GRF Prospective
Lorimer & Hume 2014, 2016
- Runners, triathletes /
mixed - Stiffness
Systematic review
GRF = ground reaction force; COP = center of pressure; EMG = electromyography.
20
1.4 External and internal loading
External loading during running refers to the action of forces external to the body due to
acceleration of its center of mass, while internal loading refers to the action of forces in-
ternal to body segments (e.g. muscle and tendon forces) produced to control segment
motion due to center of mass accelerations. Studies investigating inter-limb differences
during running focused on biomechanical variables related to external loading (Table 1).
However, it has been shown that external loading is sometimes poorly associated to in-
ternal loading [53-56]. For example, the load in the tibia are not well correlated to GRF
metrics such impact peak and loading rate [53]. Regarding the AT, its peak internal
force is much greater than measured peak GRF [55, 57], while timing of peak AT forces
and peak GRF do not coincide [55, 57]. However, studies investigating inter-limb bio-
mechanical differences during running (Table 1) and the association of running biome-
chanics to AT overuse injury (Table 2) have been limited to the evaluation of variables
related to external loading. There is a lack of investigation regarding the occurrence of
inter-limb differences when considering variables related to tendon internal loading dur-
ing running.
1.5 Achilles tendon loading, properties and structure
1.5.1 Structure
The AT is the strongest tendon in the human body, experiencing tensional forces of up
to 9000 N during overground running at 6 m.s-1 [57]. The AT is comprised of tendon
material transferring force from the triceps surae muscles [58]. The triceps surae is a
synergistic muscle group composed of the medial gastrocnemius (MG), lateral gas-
trocnemius (LG), and soleus (SOL) muscles. The MG originates approximately in the
medial femoral supracondyloid tubercle while the LG originates approximately at the
lateral femoral supracondyloid tubercle, both at the femoral distal epiphysis of the fe-
mur [59]. The SOL has two origins arising from the tibia and fibula, at the inferior bor-
der of the soleal line and at the posterior aspect of the head and upper fourth of the dy-
aphisis respectively [59]. The gastrocnemii (MG and LG) are bilateral muscles since
they actuate both the knee and the ankle joints [59]. Estimated triceps surae volumes ob-
tained from magnetic resonance imaging (MRI) are approximately 257, 150 and 438
21
cm3 for the MG, LG and SOL respectively [60]. The gastrocnemii and soleus aponeuro-
ses combine distally to form the AT [59]. Handsfield, Slane [58], suggests the AT is
comprised of sub-tendons structured by tropocollagen, microfibril, fibril, fibre, and fas-
cicles. The free portion of the AT is defined by the portion of tendon between the calca-
neus insertion and the soleus muscle-tendon junction [59]. Although this portion repre-
sents the tendon per se, the AT is commonly investigated in the literature considering
the free tendon and MG aponeurosis up to the MG muscle-tendon junction (MTJ). The
MG-MTJ is more frequently adopted due to its more superficial position relative to the
SOL-MTJ.
1.5.2 Morphological, mechanical and material properties
Tendons adapt to mechanical load by changing their morphological, mechanical and
material properties [61-63]. Morphological properties relate to the tendon’s anatomical
structure. Tendon length and tendon cross-sectional area (CSA) are examples of tendon
morphological properties. Due to its low cost and reliability, ultrasonography (US) have
been used to asses those properties [23, 24, 27]. The slack length (e.g. the length prior to
that at which the tendon starts to develop tension) is another commonly assessed mor-
phological property. Tendon slack length is usually adopted in the calculation of tendon
strain, although tendon resting length might also be used for strain estimations [26].
Tendon CSA is assessed by estimating the area of a given coronal cross-section of the
tendon. The tendon’s mid portion (e.g. 3-4 cm proximal to the calcaneal insertion) is a
commonly assessed site for CSA measurements [64, 65]. The mean CSA values can
vary from ≈35 mm2 up to ≈70 mm2 [23, 24, 26, 64]. Although the AT moment arm
(MA) is determined by tendon and bone morphology, it is included in this thesis as a
morphological property. The AT MA is calculated as the perpendicular distance from
the tendon force line of action to the rotation axis of a the ankle joint [66] and can be as-
sessed by combining US and motion capture [67, 68] or by MRI [24].
Commonly assessed AT mechanical properties are strain and stiffness. Tendon strain is
defined as the relative displacement of the tendon, and is assessed by normalizing the
variation in its length by its initial length (e.g. slack or rest length) when no load is pre-
sent. Strain is proposed as an important mechanical property driving tendon adaptation
(e.g. changes in tendon properties) [61-63]. Excessive strain was found to be detri-
mental to tendon tissue integrity [49-51] and linked to the occurrence of tendon overuse
injuries [52]. Direct estimations of the AT length and strain can be obtained by combin-
ing ultrasonography with motion capture [69], although it can also be indirectly esti-
mated using musculoskeletal models [70, 71].
Stiffness is defined as the amount of tendon lengthening per unit of tendon force and is
calculated as the slope of a given portion of the AT force-elongation relationship [23,
22
24, 26]. Tendon force can be estimated by dividing the ankle extension torque by the es-
timated or directly measured AT MA [23, 24, 26]. The tendon modulus of elasticity (or
elastic modulus) is a material property commonly assessed in studies investigating AT
adaptation to mechanical loading [23, 24, 26]. The modulus of elasticity represents the
relation between tendon stress per unit of tendon strain and is calculated as the slope of
a given portion of the tendon stress-strain relationship [23, 24, 26].
1.5.3 Adaptation to load
Inter-limb differences in tendon properties are well documented in athletes involved in
sport modalities in which a leading limb is predominant [23-25]. For example, AT stiff-
ness [23, 25] and elastic modulus [23] are increased in the leading limb (e.g. propulsive
limb) relative to the contralateral limb in jumpers. Similarly, patellar tendon stiffness is
greater in the leading limb of fencers and badminton players in relation to the non-lead-
ing limb [24]. Interestingly, differentiation in tendon properties among limbs seem to
also occur due to mechanical loading induced by limb preference during long-term,
daily use. A greater isometric ankle extensor torque was found in the dominant limb of
healthy non-athlete individuals [28], while AT CSA [27], stiffness and elastic modulus
[26] are also greater in the dominant limb of healthy, non-athlete individuals. These
findings provide evidence indicating differences in tendon properties due to sport prac-
tice and due to limb preference. Currently, the literature lacks information of possible
inter-limb differences in neuromuscular and tendon properties of habitual runners.
1.6 Analysis of continuous data
The statistical analysis procedures employed in prior studies investigating inter-limb
biomechanical differences during running have been conducted using summarized met-
rics (e.g. peaks, means; zero-dimensional data) extracted from the biomechanical con-
tinuum of interest (Table 1). The adoption of such a method oversimplifies the analysis
of complex data such one-dimensional biomechanical and neuromuscular trajectories,
since their time-varying nature cannot be adequately represented using a single value.
Summarized metrics have also frequently been adopted for the investigation of biome-
chanical inter-limb differences in healthy individuals. The adoption of summarized in-
formation to that purpose is not a priori supported, since there is limited evidence from
the literature showing inter-limb biomechanical differences to occur in healthy runners
when such summarized metrics are considered (Table 1). Statistical parametric mapping
(SPM) is one possibility to overcome these limitations. The SPM method “is an n-di-
23
mensional methodology for the topological analysis of smooth continuum changes asso-
ciated with experimental intervention” [72]. Advantages of SPM compared to other
methods are that it considers the entire biomechanical continuum of interest [72, 73], re-
duces chances of regional foci and therefore chances of biased decisions [72, 73], and
incorporates correction for multiple comparisons, making it eventually more robust than
analysis based on summarized metrics [17, 74]. SPM analysis has been adopted in loco-
motion studies investigating joint kinematics, joint kinetics and neuromuscular variables
during locomotion [17, 75-77]. Finally, a comprehensive exploratory data analysis
would not be possible unless incurring in a considerable amount of summarized metrics
being extracted from the biomechanical or neuromuscular continuums of interest.
24
2 AIMS
The general aim of this thesis is to investigate possible biomechanical inter-limb differ-
ences in habitual runners during running and due to running. Specific aims were:
1. To investigate inter-limb differences in kinetic, kinematic and triceps surae activa-
tion in triathletes during running after a cycle-run transition. This aim was ad-
dressed in Study I.
2. To investigate inter-limb differences in kinetic, kinematic, triceps surae activation
and AT strain in habitual runners during submaximal running. This aim was ad-
dressed in Study II.
3. To investigate inter-limb differences in lower limb stiffness in habitual runners dur-
ing submaximal running. This aim was addressed in Study III.
4. To investigate inter-limb differences in neuromuscular characteristics of triceps su-
rae and AT properties of habitual runners. This aim was addressed in Study IV.
25
3 METHODS
3.1 Subjects and study designs
The studies presented in this thesis were approved by the Regional Ethics Review Board
in Stockholm, Sweden and followed the principles outlined in the Declaration of Hel-
sinki. Participants were informed about studies procedures and provided signed consent
of their participation. Participants were informed that at any time point they were al-
lowed to terminate their participation in the study, and that no reason would be required
for such purpose. Subject characteristics and study designs are presented in Table 3.
26
Table 3. Characteristics of the studies presented in the thesis. GRFV = vertical ground reaction force; EMG = electromyography.
Study I Study II Study III Study IV
Descrip-tion
Bilateral lower limb evaluation during running after cycling
Bilateral lower limb eval-uation during running
Bilateral lower limb eval-uation during running
Bilateral lower limb evaluation during isometric contraction
Partici-pants
Triathletes (n = 13) Habitual runners (n = 13) Habitual runners (n = 12) Habitual runners (n = 15)
Design Cross-sectional Cross-sectional Cross-sectional Cross-sectional
Methods
Instrumented insoles
Motion capture
Surface EMG
Instrumented insoles
Motion capture
Surface EMG
Ultrasonography
Motion capture
Isokinetic dynamometry
Surface EMG
Ultrasonography
Varia-bles
GRFv
Lower limb kinematics
Tendon length
Triceps surae/TA EMG
GRFv
Lower limb kinematics Tendon length
Triceps surae/TA EMG
Spatiotemporal
Vertical stiffness
Limb stiffness
COM kinematics
Ankle extensor torque
AT force
Triceps surae/TA EMG
AT mechanical, morphological and material properties
COM = center of mass; GRFv = vertical ground reaction force; TA = tibialis anteriore; EMG = electromyography.
27
3.2 Testing protocols
Bilateral evaluation during a cycle-run simulation
Triathletes visited the laboratory twice. In their first visit, triathletes performed an incre-
mental cycling test for determination of maximal cycling power output on a cycle er-
gometer (Monark LC7, Monark Exercise AB, Sweden). Triathletes performed a warm-
up at 100 W at a self-selected pedaling cadence. The incremental test consisted of a cy-
cling trial starting at 150 W with 20 W workload increments each minute at a constant
pedaling cadence (90 ± 2 rpm) until volitional exhaustion. Maximal power output was
determined as the last stage triathletes were capable to maintain for more than 30 sec-
onds. During their second visit to the laboratory triathletes performed a simulated cycle-
run transition consisting of 20 minutes cycling at 70% of maximal power output imme-
diately followed by a 5 kilometers time-trial treadmill run on a motorized treadmill
(RL2500E, Rodby Innovation AB, Sweden) (Figure 1). Pedaling cadence and workload
were visually inspected and controlled during cycling trials using visual feedback pro-
vided by the cycle-ergometer’s head unit. Triathletes were instructed to run at their race-
pace and were allowed to increase or decrease treadmill speed but were not informed of
their actual running speed.
Figure 1. Laboratory setup adopted during the cycle-run simulations (Study I).
28
3.2.1 Bilateral evaluation during treadmill running
Runners and triathletes visited the laboratory once for the bilateral evaluation of biome-
chanical variables during running. Prior to testing they warmed-up for 10 minutes at a
self-selected speed below 2.7 m.s-1. Subsequently participants performed three running
trials at each speed of 2.7 m.s-1 and 4.2 m.s-1 interspersed by 30 seconds rest on a mo-
torized treadmill (RL2500E, Rodby Innovation AB, Sweden). The first 10 seconds of
each running trial were used to allow participants to reach a steady-state running pat-
tern, and the last 20 seconds of the trial were used for data registration.
3.2.2 Bilateral evaluation during isometric contractions
Runners and triathletes visited the laboratory once for the bilateral evaluation of isomet-
ric torque, EMG and AT properties. The isometric protocol consisted of 4 maximal
plantarflexion contractions performed against a foot plate attached to a dynamometer
(IsoMed 2000, D&R Ferstl GmbH, Germany). Each maximal contraction was inter-
spersed by 1 minute rest period. During contraction participants were instructed to grad-
ually increase force production from 0 to 5 seconds, therefore producing a ‘ramp’
torque. Three trials for warm-up and familiarization were conducted prior to testing by
runners and triathletes performing submaximal contractions while receiving visual feed-
back of their ramp torque production. After maximal isometric torque evaluations, the
AT MA and CSA were evaluated at rest using the same limb configuration adopted dur-
ing the isometric trials.
3.2.3 Limb preference
The self-reported Waterloo Footedness Questionnaire [78] was applied in order to deter-
mine limb preference (Appendix I). Limb preference was defined whenever more than
60% of questionnaire answers were associated to a given limb.
3.3 Equipment and procedures
3.3.1 Ground reaction force
The GRFv was registered using an instrumented insole system (Pedar® Mobile System,
Novel GmBh, Munich, Germany) placed inside each participant’s running shoes (Figure
2) operating with a sampling rate of 100 Hz. The insoles were calibrated according to
29
manufacturer instructions, while the system’s accuracy, validity and repeatability have
been addressed elsewhere [79].
Figure 2. The instrumented insole system (Pedar® Mobile System, Novel GmBh, Mu-
nich, Germany) used for GRFv registration.
3.3.2 Motion capture
A twelve camera motion capture system (Oqus 4-series, Qualisys AB, Gothenburg,
Sweden) operating with a sampling rate of 300 Hz registered the three-dimensional co-
ordinates of 35 reflective markers placed on bone landmarks and segments during run-
ning7. A six camera motion capture system (Oqus 4-series, Qualisys AB, Gothenburg,
Sweden) operating with a sampling rate of 300 Hz was used for registration of three-di-
mensional coordinates of reflective markers attached to the US probe, lateral and medial
malleoli, and the calcaneus during maximal isometric contractions and AT-MA proto-
cols.
3.3.3 Maximal isometric torque assessment
The ankle extensor torque produced during a maximal isometric contraction was regis-
tered using an isokinetic dynamometer (IsoMed 2000, D&R Ferstl GmbH, Germany)
operating with a sampling rate of 3000 Hz (Figure 3). The knee joint was positioned at
45 degrees of flexion while the ankle joint was in neutral position (0 degrees, foot per-
pendicular to the tibia). The participant’s foot was securely strapped to the dynamome-
ter’s foot plate to avoid foot movement, in particular the heel rising from the foot plate.
30
Figure 3. Knee, ankle, US probe and EMG electrodes configurations adopted during
maximal isometric contractions performed on an isokinetic dynamometer. US = ultra-
sound; EMG = electromyography.
3.3.4 Moment arm assessment
The AT-MA was assessed using a hybrid method combining ultrasonography and mo-
tion capture [68, 80]. A 60 mm field-of-view linear array B-mode US probe operating
with a sampling rate of 75 Hz (Echo Blaster 128, LV 7.5/60/128Z-2, Telemed, Lithua-
nia) was positioned longitudinally to the AT line of action to register a sagittal cross-
section of the AT as close as possible to the rotation axis of the ankle joint (Figure 4).
The three-dimensional coordinates of reflective markers identifying the extrapolated US
probe surface and on the lateral and medial malleolus were registered simultaneously
during US imaging.
Figure 4. Ultrasound imaging of the AT line of action, the US probe field-of-view and
the ankle joint locations were simultaneously registered to the assessment of the Achil-
les tendon moment-arm.
31
3.3.5 Cross-sectional area assessment
Cross-sectional imaging of the AT was registered using a 35 mm field-of-view linear ar-
ray B-mode US probe operating with a sampling frequency of 50 Hz (EnVisor M2540,
L7535, Philips Electronics N.V., the Netherlands). Two coronal cross-sectional images
were registered from each limb at the free AT mid-portion defined as the point 40 mm
from the AT calcaneal insertion.
3.3.6 Muscle-tendon junction displacement
The MG-MTJ displacement was registered using a 60 mm field-of-view linear array B-
mode US probe operating with a sampling rate of 75 Hz (Echo Blaster 128, LV
7.5/60/128Z-2, Telemed, Lithuania). During the isometric contraction trials the US
probe was positioned as illustrated in Figure 3. During running trials the US probe posi-
tion was positioned as illustrated in Figure 5.
Figure 5. An ultrasound probe was firmly strapped to the limb for registration of the
medial gastrocnemius muscle-tendon junction (MG-MTJ) displacement during running.
The three-dimensional coordinates of reflective markers placed on the distal border of
the US probe field of view and the calcaneus bone were registered simultaneously with
the US imaging.
3.3.7 Electromyography
Surface EMG was used to register the myoelectric activity of MG, LG, SOL and tibialis
anterior (TA) bilaterally using a telemetered system (Noraxon Telemyo 2400T G2, Nor-
axon, USA) operating with a sampling rate of 3000 Hz. Pairs of surface Ag/AgCl bipo-
lar electrodes (Neuroline 720, Ambu Inc., Denmark) were placed parallel to the muscle
fibers on each muscle bilaterally. The skin was carefully shaved and cleaned with alco-
hol wipe prior to electrode placement in order to reduce skin impedance. Electrodes
were carefully positioned over the MG, LG, SOL and TA muscles observing an inter-
electrode distance of 20 millimeters, while electrode location was replicated among
32
limbs. All surface EMG procedures followed guidelines established by the Surface
EMG for Non-Invasive Assessment of Muscles (SENIAM) concerted action [81].
3.4 Data analysis
3.4.1 Ground reaction force
GRF data were exported using the instrumented insole acquisition software (Pedar®
Mobile System, Novel GmBh, Munich, Germany) into Matlab® (The MathWorks Inc.,
Natick, Massachusetts, USA). Raw GRFv signals were filtered at 10 Hz using a 2nd or-
der low pass Butterworth filter and subsequently up-sampled to 300 Hz by a Fast Fou-
rier Transform (FFT) interpolation method. Touch-down and toe-off were determined
using a 50 N threshold [82]. Ten consecutive steps were averaged for each limb and
considered as representative of each participant’s GRF pattern during stance.
3.4.2 Kinematics
Marker trajectories registered during running and during a static trial were tracked and
labeled using the Qualisys Track Manager software (Qualisys AB, Gothenburg, Swe-
den) and exported as .c3d files. The data were subsequently converted to the standard
.trc file format adopted in OpenSim [83] using an open source toolbox (BTK,
https://code.google.com/archive/p/b-tk/) in Matlab®. A generic musculoskeletal model
[84] consisting of head, torso, pelvis, right and left femur, patella, tibia and fibula, cal-
caneus and toes was scaled to each participant’s anatomy using three-dimensional coor-
dinates of reflective markers attached to participants’ body registered during a static
trial. Segment mass properties were scaled proportionally to the total participant body
mass. Segment lengths were scaled in order to represent participants’ anthropometry
based on the relation between bone landmarks, and muscle-tendon units were subse-
quently scaled relative to segment lengths considering the model’s predefined origin
and insertions for triceps surae muscle-tendon units. During scaling, the virtual markers
located on the model were relocated to match the location of experimental markers dur-
ing the static trial by solving an inverse kinematic problem that minimizes the weighted
square error between experimental and virtual marker coordinates. The scaling process
resulted in a subject-specific musculoskeletal model reflecting each participant’s anthro-
pometrics (Figure 6). All subject-specific musculoskeletal models were built using the
same model [84]. Detailed information such model’s degrees of freedom, rigid body co-
ordinate system, joint types, and other are presented in detail by Rajagopal, Dembia
33
[84]. Joint generalized coordinates during running were estimated using the scaled sub-
ject-specific musculoskeletal models and registered marker trajectories were calculated
using inverse kinematics in OpenSim. Generalized coordinates generated by the model
were subsequently filtered using a 3rd order infinite impulse response (IIR) Butterworth
filter with a cutoff frequency of 10 Hz using the Analysis Tool in OpenSim. Joint kine-
matics and muscle-tendon lengths extracted from ten steps were averaged for each limb
and regarded as representative of runners and triathletes’ patterns during stance.
Figure 6. A musculoskeletal model scaled to participants’ anthropometrics was used for
inverse kinematics procedures in OpenSim.
3.4.3 Limb and vertical stiffness
Modelled maximal force (Fmax), vertical stiffness (kvert) and limb stiffness (klimb) were
calculated using methods presented in more detail elsewhere [85-87]:
Maximal force
𝐹𝑚𝑎𝑥 = 𝑚𝑔𝜋
2 (
𝑡𝑓
𝑡𝑐+ 1)
where Fmax = maximal force, m = body mass (kilograms), g = gravitational acceleration
(m.s-2), tf = flight time (seconds), tc = contact time (seconds).
Vertical stiffness
𝑘𝑉𝑒𝑟𝑡 =𝐹𝑚𝑎𝑥
∆𝐶𝑂𝑀
where kvert = vertical stiffness, ∆COM = vertical displacement of the center of mass
(meters).
34
Limb stiffness
𝑘𝐿𝑖𝑚𝑏 =𝐹𝑚𝑎𝑥
∆𝐿𝑖𝑚𝑏
∆𝐿𝑖𝑚𝑏 = 𝐿 − √𝐿2 – (𝑣𝑡𝑐
2)
2
+ ∆𝐶𝑂𝑀
where ∆Limb = limb displacement (meters), L = limb length (meters), v = running
speed (m.s-1), tc = contact time (s), ∆COM = vertical displacement of the center of mass
(meters);
Contact time (tc) and flight time (tf) were calculated by differentiating reference frames
identified from touch-down and toe-off, while COM displacement during stance was
obtained using the musculoskeletal model and inverse kinematics results from Open-
Sim. Tc, tf, and ∆COM averaged from ten consecutive steps from each submaximal
speed were used as representative of each limb.
3.4.4 Tendon length and strain during running
The MG-MTJ displacement registered by US during running was exported to an open
source video analysis software (Tracker 5.0.7, Open Source Physics, https://www.com-
padre.org/osp/index.cfm). The origin of a local coordinate system was defined as the su-
perior left corner of the US field of view and the x coordinates defined the tendon’s
proximal-distal displacement. The two dimensional coordinates of the MG-MTJ relative
to the coordinate system were determined by tracking the MG-MTJ displacement during
running frame-by-frame (Figure 14). AT lengthening (mm) was estimated by summing
the instantaneous vector length determined from the calcaneus marker to the US probe
to the tracked MG-MTJ displacement. AT strain was calculated during running as AT
lengthening divided by the AT length at toe-off.
35
Figure 7. A video analysis software (Tracker 5.0.7, Open Source Physics,
https://www.compadre.org/osp/index.cfm) was used to track the medial gastrocnemius
muscle-tendon junction. Small red dots represent history of the MG-MTJ tracked posi-
tion each time frame.
3.4.5 Moment-arm
The linear distance from the AT mid-portion line (Figure 5) to the true US probe surface
was measured using an open source video analysis software (Tracker 5.0.7, Open
Source Physics, https://www.compadre.org/osp/index.cfm) after proper ultrasound im-
age calibration using known distances from the ultrasound field of view. Since the dis-
tance from true US probe surface to the extrapolated US probe surface was known, AT-
MA was simply determined by subtracting those distances from the distance of US
markers to the mid-point of the ankle joint as previously described [68, 80].
3.4.6 Cross-sectional area
Registered US images of the AT in the coronal plane were imported to ImageJ image
analysis software (ImageJ 1.5i, National Institute of Health, USA). The polygon tool
was used in ImageJ to determine the AT CSA (Figure 8) as previously described [64,
65] after proper image calibration and accounting for pixel aspect ratio. The CSA was
considered as the average of three measurements taken from the AT from each limb.
36
Figure 8. The CSA (area within the segmented yellow line) was manually determined
using ImageJ (version 1.50i, National Institutes of Health, USA) and coronal cross-sec-
tional Achilles tendon images registered with ultrasound.
3.4.7 Tendon force and stress
Ankle extensor torque registered during maximal isometric contractions were filtered at
10 Hz using a 4th order low pass Butterworth filter. The ramp portion of torque produc-
tion was determined from 1% of peak torque to 100% of peak torque. The AT force in
each limb was approximated by dividing ankle extensor torque by its respective esti-
mated AT MA. The AT stress (N.mm-2) was calculated for each limb dividing the AT
force by its CSA.
3.4.8 Tendon rest length, length and strain
The MG-MTJ displacement registered during the isometric contractions was analyzed
using the same procedures as for the running trials. The AT resting length (mm) was
calculated as the sum of the instantaneous vector length determined from the calcaneus
marker to the US probe marker and the MG-MTJ local coordinates with the foot at-
tached to dynamometer footplate at rest. The AT lengthening was calculated as the vari-
ation in the AT length during the isometric contractions by using the same method as
for calculating the AT rest length. The AT strain (%) was calculated as the AT lengthen-
ing (mm) divided by rest length (mm).
3.4.9 Tendon stiffness and modulus of elasticity
The AT stiffness (N.mm-1) was estimated as the linear regression from 30% to 90% of
the AT force-elongation relationship. The AT modulus of elasticity (GPa) was estimated
as the linear regression from 30% to 90% of the AT stress-strain relationship curve.
37
3.4.10 Electromyography
Raw EMG signals registered during the cycle-run and submaximal running trials (Fig-
ure 15) were band-pass filtered at 20-500 Hz using a 5th order Butterworth filter. Subse-
quently the root man square (RMS) envelopes were calculated from the filtered signal
using a 40 ms moving-window. Raw EMG signals registered during isometric contrac-
tions were band-pass filtered at 30-850 Hz using a 4th order Butterworth filter and RMS
envelopes were calculated using a 300 ms moving-window. EMG RMS in Study I was
normalized using the peak EMG RMS found between the Start, Mid and End stages of
the 5 km run. The EMG RMS in Study II was normalized using the peak RMS value
found in each respective speed. In Study IV the EMG RMS was normalized using the
peak RMS from the trial in which maximal torque occurred. The relative contribution
each triceps surae muscle to total triceps surae activation and of the MG to total gas-
trocnemii (MG + LG) activation was determined. These MG, LG, and SOL ratios were
calculated by dividing each muscle normalized activation by the sum of all triceps surae
normalized activations as in Crouzier, Lacourpaille [88]. The ratio of MG normalized
activation by the gastrocnemii normalized activation [88] was defined as ‘GAS’ ratio.
3.5 Statistical analysis
Discrete data analysis was adopted in Studies II and IV. For all the other inter-limb
comparisons, the SPM analysis was adopted for testing the analysis of time-series data.
All data were tested for normal distribution. In the case of non-normal data distribution,
Wilcoxon signed-rank tests or statistical non-parametric tests (SnPM) were adopted.
Paired t-tests were used in Studies I, II, III and IV to identify possible difference be-
tween the preferred and non-preferred limb. Pearson’s correlation coefficients were
used in Studies III and IV for the assessment of the level of relationship between varia-
bles. Effect sizes were calculated for the zero-dimensional and one-dimensional data as
differences between the means weighted by the mean of standard deviations [89].
38
4 RESULTS
In Study I, results from the GRFv and COPAP during the stance phase show no cluster
crossing the SPM threshold at any time-point (Figure 9). Similarly, in Study II no dif-
ferences were found in GRF during either slow (2.7 m.s-1) or fast (4.2 m.s-1) running.
No inter-limb differences were observed in the analysis of limb and vertical stiffness, or
spatiotemporal variables during slow and fast running (Table 5, Figure 10).
39
Figure 9. Upper panels: vertical ground reaction force [GRFV, in body weights (Wb)] and anterior-posterior center of pressure displacement
(COPAP) across the three stages (Start, Mid, End) of running after cycling; preferred limb: blue solid lines; non-preferred limb: orange solid
lines: Lower panels: statistical parametric mapping (SPM, blue lines) and effect size (ES, orange lines) results are shown respective to vari-
ables presented in the upper panels.
40
Figure 10. Mean, standard deviation and 95% confidence internals for modelled maximal force (Forcemax), vertical stiffness (kVert), limb
stiffness (kLimb), and limb displacement (∆Limb) at slow (2.7 m.s-1) and fast (4.2 m.s-1). Black dots representing participant’s values for the
preferred (P) and non-preferred (NP) limbs.
41
Table 5. Statistical results from inter-limb comparisons (preferred vs non-preferred) conducted in Study III.
2.7 m.s-1 4.2 m.s-1
p value ES 95% CI for ES p value ES 95% CI for ES
Fmax 0.52 -0.19 -0.76 0.38 0.52 -0.19 -0.76 0.38
kVertbreaking 0.17 -0.41 -0.99 0.18 0.17 -0.41 -0.99 0.18
kVertpropulsion 0.23 0.36 -0.23 0.93 0.23 0.36 -0.23 0.93
kLimbbreaking 0.87 0.04 -0.52 0.61 0.87 0.04 -0.52 0.61
kLimbpropulsion 0.54 0.17 -0.39 0.74 0.54 0.17 -0.39 0.74
∆Limbbreaking 0.89 0.03 -0.52 0.60 0.89 0.03 -0.52 0.60
∆Limbpropulsion 0.66 -0.12 -0.69 0.44 0.66 -0.12 -0.69 0.44
Limb length 0.71 -0.16 -0.52 0.61 - - -
Contact time 0.86 -0.04 -0.61 0.51 0.86 -0.04 -0.61 0.51
Flight time 0.23 -0.36 -0.94 0.22 0.23 -0.36 -0.94 0.22
Stride time 0.75 0.09 -0.47 0.65 0.75 0.09 -0.47 0.65
Braking time 0.53 0.18 -0.39 0.75 0.53 0.18 -0.39 0.75
Propulsion time 0.53 -0.18 -0.75 0.39 0.53 -0.18 -0.75 0.39
p = p value, ES = effect size; CI = confidence interval.
In Study II hip joint extension velocity was greater in the non-preferred limb at both
tested speeds from 71% to 93% (p<0.01) of the stance phase (Figure 11). Furthermore,
in Study III a greater COMhoriz velocity in the preferred limb was observed during 0-
12% of the stance phase (p<0.05, ES >0.60), and greater COMhoriz velocity in the non-
preferred limb during 67-87.40% of stance (p<0.05, ES >0.60) during slow running
(Figure 12). During fast running, the COMhoriz velocity was found to be greater in the
preferred limb during 0-1.6% of stance (p=0.05, ES>0.60). Furthermore, no inter-limb
differences were observed in Study I and II regarding the MG, LG and SOL tendon
strains estimated from the musculoskeletal model and in Study II considering strain
from in vivo estimations (Figure 13).
42
Figure 11. Joint velocities during slow and fast running across the stance phase (touch
down to ipsilateral toe off); Upper panels: the preferred limb in represented by blue
lines while the non-preferred limb is represented by orange lines. Lower panels: statis-
tical parametric mapping analysis (SPM, blue lines) and effect size (ES, orange lines)
results are presented respectively to upper panels. Slow running (2.7 m.s-1) = dashed
lines; fast running = solid lines represent (4.2 m.s-1).
43
Figure 12. Upper panels: center of mass vertical (COMvert) and horizontal (COMhoriz)
positions and velocities at slow (2.7 m.s-1) and fast (4.2 m.s-1) running speeds. Slow run-
ning: black dashed lines; fast running: black solid lines; vertical black dashed and solid
lines indicate the transition from breaking to propulsion at slow and fast running speeds
respectively. Lower panels: statistical parametric mapping (SPM, blue lines) and effects
size (ES, orange lines) results are presented respectively to upper panels. Vertical solid
red lines indicate data clusters which crossed the t threshold indicating p < 0.05.
44
Figure 13. AT elongation and strain during running from touch-down to ipsilateral
touch-down at slow and fast running. Upper panels: blue lines representing the pre-
ferred limb; orange lines representing the non-preferred limb; dashed lines: slow run;
solid lines: fast run; vertical dashed and solid black lines indicate toe-off at the slow
and fast run respectively. Lower panels: statistical parametric mapping (SPM, blue
lines) and effect size (ES, orange lines) results are shown respectively to upper panels.
Dashed lines represent slow running (2.7 m.s-1), while solid lines represent fast running
(4.2 m.s-1).
In Study I the SOL activation was lower in the preferred limb from 53.4% to 75.89% (p
< 0.01, ES range = 0.59 to 0.80) of the stance phase at the final stage of running after
cycling Figure 14. The LG activation was also lower in the preferred limb from 67.75%
to 82.66% of the stance phase at the same stage (p <0.01), although the effects was con-
sidered of small magnitude (ES range = 0.41 to 0.51) Figure 14. The MG activation was
observed to be lower in the non-preferred limb relative to the preferred at the mid stage
from 75.24%-80.78% of the stance phase (p =0.01) although the difference was consid-
ered small (ES range = 0.39 to 0.58) Figure 14. No inter-limb differences were observed
in the EMG analysis across a stride during submaximal running in Study II (Figure 15).
45
Figure 14. Medial gastrocnemius (MG), lateral gastrocnemius (LG) and soleus (SOL) activations during Mid and End stages of running
after cycling. Vertical solid red lines indicate where clusters of data crossed the t threshold indicating p < 0.05.
46
Figure 15. Upper panels: medial gastrocnemius (MG), lateral gastrocnemius (LG), so-
leus (SOL) and TA activations at submaximal running speeds. Lower panels: statistical
parametric mapping (SPM, blue line) and effect size (ES, orange lines) results are
shown respectively to upper panels. In both upper and lower panels dashed lines repre-
sent slow running (2.7 m.s-1), while solid lines represent fast running (4.2 m.s-1). Note
that muscle activation is presented for a full stride (e.g. touch-down to ipsilateral touch-
down).
The results from Study IV indicate no inter-limb differences in AT morphological, me-
chanical or material properties (Table 6). No inter-limb differences were observed in tri-
ceps surae ratios and TA activation patterns during maximal isometric contractions
(Figure 16). Furthermore, the results from an intra-limb analysis showed that MG and
LG ratios correlated significantly to SOL ratio (MG-SOL: r=-0.53, p=0.04; LG-SOL:
r=-0.80, p<0.01) and to GAS ratio (MG-GAS: r=0.56, p=0.03; LG-GAS: r=-0.86,
p<0.01) in the preferred limb. In the non-preferred limb, MG and LG ratios correlated
significantly to GAS ratio (MG-GAS: r=0.79, p<0.01; LG-GAS: r=-0.86, p<0.01), and
LG ratio to SOL ratio (LG-SOL: r=-0.65, p=0.01). All results from the Pearson’s corre-
lation analysis are presented in the Appendix.
47
Table 6. Achilles tendon morphological, mechanical and material properties presented as mean (standard deviation) and the corresponding Pearson’s correlation coefficient (r) for the association between limbs.
N P limb NP limb p ES r
CSA (mm2) 15 68.76 (12.14) 68.52 (10.58) 0.93 0.02 0.54*
Elongation (mm) 15 14.24 (4.41) 12.67 (4.81) 0.13 0.41 0.65*
Emodulus (GPa) 15 0.34 (0.14) 0.43 (0.22) 0.09 0.46 0.58*
Force (N) 15 2088 (891) 1940 (849) 0.14 0.39 0.90*
MA (mm) 15 44.34 (5.34) 46.28 (6.75) 0.15 0.39 0.68*
Rest length (mm) 15 186.68 (21.77) 185.87(21.83) 0.87 0.04 0.62*
Stiffness(N.mm-1) 15 150.32 (50.62) 167.36 (67.28) 0.08 0.62 0.85*
Strain (%) 15 7.7 (2.7) 6.8 (2.5) 0.17 0.37 0.56*
Stress (N.mm-2) 15 30.82 (12.52) 27.79 (9.6) 0.10 0.44 0.84*
Torque (N.m-1) 15 95.81 (40.01) 93.44 (43.65) 0.58 0.14 0.92*
CSA = cross sectional area; MA = moment arm; P = preferred; NP = non-preferred; ES = effects
size. *statistically significant correlation (p<0.05).
Figure 16. Upper panels: triceps surae and tibialis anterior EMG normalized by peak
RMS across the ramp portion of maximal isometric contractions. Solid gray lines: pre-
ferred limb; solid red lines: non-preferred limb; Shaded areas: ±1 standard deviation.
Lower panels: statistical parametric mapping (SPM) paired t-test analysis across the
ramp portion of the maximal isometric contractions.
48
5 METHODOLOGICAL CONSIDERATIONS
5.1 Cycle-run simulation, treadmill run and fatigue
It was not possible to control for exclusive effects of fatigue due to the absence of a
control run (e.g. no preceding cycling) in Study I. Furthermore, a fixed pedaling ca-
dence and workload were adopted for standardization purposes, although it may not
mimic ecological conditions of pedal power production in triathlon [90]. Running
speeds investigated in Study II were chosen to complement prior studies focused on in-
ter-limb differences when investigating external load related variables, which were up to
3.7 m.s-1. Fatigue was not present in Study II since trials were of short duration and in-
terspersed by enough recovery time.
5.2 Kinetics
Inter-limb differences in high frequency components of the GRF were not registered
since the used instrumented insole system is limited to a low operating sampling rate.
Stiffness parameters during running were estimated using spatiotemporal parameters,
and the validity and reliability of the applied method were demonstrated previously [85-
87]. High intra and inter-day reliability have been reported during treadmill running at
4.4 m.s-1 [85]. Regarding to validity, prior studies showed acceptable bias when compar-
ing the method to gold standard reference values for both overground and treadmill run-
ning [87]. Finally, high intra-class correlation coefficients (values of 0.61 and 0.99 for
leg length and force estimations respectively) and -5%, -1% and 6% difference between
the reference and the indirect method have been reported for limb stiffness, force and
limb length [86].
5.3 Kinematics
The knee joint is constrained to the sagittal plane in the musculoskeletal model adopted
in this thesis [84]. Habitual runners were using shoes and therefore the foot marker set
49
did not allow adequate quantification of subtalar and metatarsophalangeal joint kinemat-
ics. Therefore, the subtalar and metatarsophalangeal joints were constrained to zero de-
grees following procedures elsewhere [84]. In Study I slack length from the model was
used for tendon strain estimations, whereas in Study II tendon length at toe-off was
adopted for tendon strain estimations. This was to account for possible differences in
knee and ankle kinematics at toe-off, since MG, LG and SOL muscle-tendon unit paths
are dependent on those joint configurations. Segment and muscle-tendon unit lengths
are defined during the scaling process [84], and are defined symmetrically in OpenSim
[83]. Thus, slack length, tendon length and therefore tendon strain derived from the
musculoskeletal models fail to accurately identify subject-specific inter-limb differ-
ences. Future studies may investigate the effect of adding degrees of freedom to the
knee joint, adopting unconstrained subtalar and metatarsophalangeal joints, and improv-
ing scaling accuracy when evaluating muscle-tendon strains bilaterally using musculo-
skeletal models.
5.4 Electromyography
Surface electromyography was previously adopted in studies investigating neuromuscu-
lar adaptations to long duration cycling protocols (e.g. >3 hours) in triathletes [91, 92],
and also in cycle-run transition studies [93, 94]. Electrodes might be sensitive to the
time they are in use mainly due to sweating, which affects the electro-mechanical stabil-
ity skin-sensor interface with possible implications to the EMG signal registration [95].
In Study I triathletes cycled with EMG electrodes already attached to the skin to allow a
faster transition from cycling to run as in prior studies [93, 94]. Although not mentioned
in prior studies [91-94], it is not possible to exclude any effects of sweating on the elec-
tro-mechanical stability of the sensors and thus in the registered EMG signal across the
cycle-run simulation. In addition, different EMG normalization procedures were
adopted in Studies I and II. In Study I the independent variables were both running
stages and limb preference, which required normalization by the peak EMG RMS
achieved in the entire running trial. In Study II, the independent variable was limb pref-
erence only, which in turn allowed EMG normalization using the peak EMG RMS
achieved during each tested running speed.
50
5.5 In vivo estimations
Tendon length and strain estimations derived from motion capture combined to MG-
MTJ displacement registered using ultrasonography requires some caution. The ‘exter-
nal’ Achilles tendon length differs depending upon whether the anatomical curvature is
accounted for [96]. Furthermore, a great range of ultrasound sampling rates (30 to 146
Hz) have been used for MG-MTJ displacement registration during running [97-101].
Those sampling rates are considered to be well below the ideal for the accurate estima-
tion of muscle-tendon dynamics [102, 103]. Future studies would benefit from the adop-
tion of greater sampling rates than used so far [97-101] and from including tendon cur-
vature [96] when aiming for accurate tendon length and strain estimations.
5.6 Limb preference assessment
Some of the previous studies on bilateral analysis have adopted questionnaires for deter-
mination of limb preference/dominance (see Table 1). In this thesis limb preference was
assessed by applying the Waterloo footedness questionnaire [78] following similar
methods in the literature where questionnaires were applied [26, 46]. However, the rela-
tion between limb preference/dominance classification and its relevance to each limb’s
functional biomechanical role during locomotion is not well known. Studies on bilateral
biomechanical analysis during bilateral tasks such as running might benefit from stand-
ardization of methods aiming to improve definition of functional roles of each limb dur-
ing locomotion.
51
6 DISCUSSION
Investigations on inter-limb biomechanical differences during running have been con-
ducted based upon the rationale that they would result in differences in the mechanical
loading experienced by each limb. Previous studies have focused on discrete data ex-
tracted from the biomechanical continuum, and on evaluating a limited range of sub-
maximal speeds. Moreover, those studies have not examined running populations apart
from runners, and have focused on external loading variables, therefore not investigat-
ing variables associated to internal loading. Moreover, information is lacking regarding
the bilateral muscle-tendon characteristics of habitual runners. The present thesis
adopted experimental designs aimed to fill these knowledge gaps, therefore providing a
broader analysis of inter-limb biomechanical differences during running and of bilateral
muscle-tendon status in habitual runners. The present thesis focused on the Achilles ten-
don since overuse injuries in this tendon are a frequent problem to habitual runners [1-
5].
6.1 Inter-limb differences during running after cycling
The SOL activation was reduced in the preferred limb at the final stage of running after
cycling from mid-stance to the beginning of toe-off. Besides triceps surae EMG, no in-
ter-limb differences were found in kinetics or kinematics, including tendon strains esti-
mated from the musculoskeletal model. Since there are more actuators than necessary to
actuate the ankle joint, direct effects from reductions in EMG RMS to ankle joint kine-
matics may not be expected. Furthermore, it is not possible to directly translate myoe-
lectric information obtained from EMG to muscle force production [104]. However, alt-
hough the studies in this thesis were not designed to explain the nature of inter-limb dif-
ferences, a reduction in SOL activation could be speculated to be related to its role dur-
ing cycling and running. During cycling the SOL has a major role in transferring power
to the cranks [105] while during running SOL has a major role during support and pro-
pulsion [106-108]. An early observation of decreases in SOL activation during a run
preceded by cycling in triathletes [94] may be linked to the important roles of SOL in
cycling and running. In addition, a large neural drive to SOL in the preferred limb was
previously suggested to occur during walking [37]. A greater neural drive to the SOL in
52
the preferred limb might also have occurred in the triathletes during the cycle-run simu-
lation. This might have reduced the central nervous system capacity to maintain the
same level of neural drive to both limbs throughout the entire protocol. Although specu-
lative, this theory might be supported by recent findings that neural drive is not equally
shared by synergistic muscle groups such as the triceps surae [109]. A greater neural
drive to SOL might also occur to counteract the less optimal MG fascicle length occur-
ring during knee flexion, which was associated to reductions in MG firing rates [110].
Currently, information concerning LG fascicles and firing rates is lacking. With that in
mind, the modulation of neural drive to a given limb and to a given muscle within a
synergistic muscle group should be further investigated considering the triceps surae
during running in triathletes.
In summary, Study I filled current gaps in the literature by investigating inter-limb dif-
ferences in GRF, lower limb kinematics and triceps surae EMG in triathletes during a
cycle-run simulation. No inter-limb differences in external load-related variables were
found during running preceded by cycling. The observed reduction in SOL EMG RMS
in the preferred limb might occur due to a prolonged greater neural drive to that limb
and to the important roles of SOL in both cycling and running.
6.2 Inter-limb differences during submaximal running
In Study II greater hip extension velocity was found in the non-preferred limb after the
mid-stance towards toe-off at both slow and fast running. Furthermore, a greater COM-
horiz velocity was found during the braking portion of stance performed with the pre-
ferred limb at slow and fast running. The COMhoriz velocity was also greater in the non-
preferred limb during the propulsion phase of stance at slow running speed in Study III,
with a similar but non-significant difference also observed during fast running. Moreo-
ver, when a side-to-side rather than a limb preference comparison was conducted in
Study III, inter-limb differences in kLimb and braking and propulsion times were found.
However, no inter-limb differences in GRF, triceps surae EMG or AT length and strain
were found. Furthermore, the MG, LG, SOL and TA tendon strain analyses from mus-
culoskeletal models showed no inter-limb differences, in agreement with joint displace-
ment results.
Study III suggested that the preferred limb may be limited in controlling COMhoriz ve-
locity during braking in relation to the non-preferred limb, since COMhoriz velocity was
found to be lower in the beginning of preferred limb stance. In contrast, the non-pre-
ferred limb appears more prone to generating greater propulsion, since the COMhoriz ve-
locity was greater when that limb was in contact with the ground. The greater hip veloc-
ity found in the non-preferred limb in Study II may be one possible mechanism helping
53
to generate the greater COMhoriz velocity during a similar portion of the stance phase in
Study III. It is noteworthy that no inter-limb differences in knee or ankle joint kinemat-
ics accompanied the differences in hip joint kinematics. If kinematic symmetry during
running is an aim of the central nervous system (CNS), then results from Study II sug-
gest it is more difficult to achieve similar joint velocities in the proximal than in the dis-
tal joints. On the other hand, if neural drive [37] or other CNS strategies determine
functional roles for each limb during running, then inter-limb differences in hip and
therefore COMhoriz velocity may be innate in human locomotion modes. A final specula-
tion considers the intrinsic musculoskeletal properties of each limb. Adding a mass be-
tween 0.5 to 2 kg to able-bodied individuals was found to alter hip and knee joint kinet-
ics during walking [111, 112]. Masses ranging from 150 to 350 g added to the foot were
also found to affect stride frequency, anterior-posterior impulse, limb stiffness, and me-
chanical work during running [113]. If inter-limb differences in segments mass are in-
nate to habitual runners as identified in sprinters [114] and active individuals [115], they
may affect joint and COM kinematics, with possible implications to propulsion.
In summary, Studies II and III filled current gaps in the literature by investigating inter-
limb differences in external and internal load related variables during submaximal run-
ning. Inter-limb differences were observed in hip and COM kinematics and may be re-
sponsible for side-to-side differences in propulsion during running. The literature sug-
gests joint torques and powers are modulated across the hip, knee and ankle joints when
running speed varies [116-119]. However, the bilateral distribution of joint moments
across the stance due to inter-limb differences in propulsion and its possible implication
to AT loading are not known and requires investigation.
6.3 Bilateral neuromuscular and tendon properties
No inter-limb differences in triceps surae EMG or AT properties were found in Study
IV. However, correlations among EMG ratios differed between limbs, suggesting mus-
cle coordination may not be identical between the preferred and non-preferred limbs.
Bilateral deficits in neuromechanical properties were suggested to occur due to homolo-
gous muscle groups being treated as single one by the CNS (e.g. common drive theory)
or due to an innate, chronic asymmetric neural drive to the preferred and non-preferred
limbs[120]. Therefore, assuming running as a task involving the coordination of both
limbs simultaneously, bilateral rather than unilateral isometric contractions may have
been able to mimic possible bilateral deficits occurring in the habitual runners investi-
gated in Study IV. Although inter-limb differences were not observed in EMG ratios, a
significant intra-limb correlation between MG and SOL was observed only in the pre-
ferred limb. If muscle synergism is an aim of the CNS during a given task, then inter-
54
limb differences in the correlation among triceps surae muscles ratios observed in Study
IV may indicate an improved ability of the preferred-limb to perform such a task. Since
information of bilateral EMG ratios are still scarce, the results from Study IV should be
further confirmed.
AT properties investigated in Study IV were chosen based upon prior studies showing
that limb preference may induce inter-limb differences in some AT properties in non-
athletes [26-28]. Speculations can be made relative to findings of no inter-limb differ-
ences in AT properties of habitual runners. Inter-limb biomechanical differences during
running was not a criteria for participation in Study IV, which possibly included indi-
viduals in a wide spectrum of inter-limb differences in AT loading during training and
competitions. Thus, any inter-limb differences in AT properties resulting from limb
preference as observed in non-athletes [26-28] might be mitigated rather than exacer-
bated in habitual runners due to training and competition routines. Whichever are the
reasons for findings from Study IV, the quantification and the magnitude of the me-
chanical loading during running leading to alterations in AT properties are difficult
problems to address. The magnitude problem is illustrated by the fact that in trained
runners with 5 years of experience and 80 km/week training volume only AT CSA was
found to be greater than in non-runners, while mechanical and neuromechanical proper-
ties were not different between groups [121]. Similarly, a nine month running training
program performed by non-runners resulted in no alteration in AT mechanical proper-
ties [122]. The quantification and magnitude problems could be addressed in prospec-
tive studies aiming to monitor AT properties in habitual runners in combination with in-
ternal and external loading quantification aiming to understand the relationship between
mechanical loading and muscle-tendon adaptation across the season.
In summary, Study IV investigated possible inter-limb differences in triceps surae neu-
romuscular properties concomitantly with AT properties in habitual runners. The results
suggest that habitual running training does not lead to differential adaptation in muscle
activation and tendon properties, at least considering the experimental design adopted in
Study IV. However, triceps surae coordination strategies inferred from EMG ratios
seem to differ between limbs during unilateral fixed-end isometric contractions. Inter
and intra-limb differences in triceps surae EMG ratios necessitate further investigation
during isometric and dynamic bilateral tasks.
6.4 Implications to overuse-related tendon injury
Inter-limb differences in SOL EMG RMS found in Study I may be related to the high
rates of AT overuse-related injuries in triathletes [3, 5]. Unequal displacements ob-
served within the AT during different conditions [123-126] are proposed to be the result
55
of differential sliding occurring between triceps surae sub-tendons [58, 127]. Assuming
intra-tendon sliding is similar among limbs, it is possible that a differential SOL activa-
tion occurring between limbs may also result in differential tendon displacements be-
tween limbs. If those unequal displacements are resulting in differential strain within the
AT in each limb, than inter-limb differences in tendon strain may arise. Strain drives
important tendon adaptive responses that, depending on the magnitude, can be positive
or negative to tendon’s health [18, 19, 49, 50, 62, 128]. Although a possible influence of
muscle activation on AT fiber gliding could be linked to the high rates of tendon injury
in triathletes, the role of differential displacements within AT are still not completely
understood. Studies have shown that aging [123], repair [124] and overuse-related ten-
don injury [129] seem to result in more uniform displacement occurring within the AT,
suggesting that some degree of differential displacement is actually an innate character-
istic of the healthy tendon. Although further investigation is necessary to unveil healthy
or optimal levels of differential displacement within the AT and the effects of triceps su-
rae activations on it, triathletes may benefit from a strength training program for ankle
extensors aiming to prevent possible decreases in neural drive. This in turn could pre-
vent differences in triceps surae activation among limbs to occur during running after
cycling.
The results from Study II and III indirectly suggest the preferred limb has a functional
role as a propulsive limb. A limb dedicated to propulsion was previously suggested to
occur during walking [37-40] and running [35, 36], and therefore might be an innate
characteristic of humans’ locomotion. Considering triceps surae muscle forces are im-
portant contributors to propulsion in running [106-108], and that peak AT forces occur
after mid-stance [55], inter-limb differences during propulsion would theoretically result
in greater AT loading in the limb producing greater propulsion. Simple strategies may
be employed to monitor inter-limb differences during propulsion such feedback of the
anterior-posterior GRF or COMhoriz velocity, which could be achieved by adapting cur-
rent available wearable technologies such inertial measuring units of instrumented in-
soles. However, it is important to bear in mind the low correlation between external and
internal loading [53-55]. The lack of effective strategies to reduce AT injury rates in the
running population may therefore be linked to the fact that predominantly variables re-
lated to external loading were addressed in biomechanical studies investigating the asso-
ciation between running biomechanics and tendon overuse-related injury [6, 8-10]. Alt-
hough coaches and clinicians are encouraged to register external loading data during
training and competitions to monitor the magnitude of inter-limb differences in propul-
sion, future research is necessary to address the effects of propulsion on AT loading by
using internal loading related variables.
The results from Study IV showed that muscle and tendon properties are not different
between the preferred and non-preferred limb of habitual runners. It is well documented
56
that AT overuse-related tendon injury results in altered tendon properties [52, 64, 130,
131]. Modalities in which high magnitudes of mechanical loading occur to one limb are
well known to induce unilateral changes in tendon properties [23, 24, 132]. Those mo-
dalities pose the question of which magnitudes of AT loading are responsible for opti-
mal and non-optimal tendon adaptive responses. The overuse injury process usually oc-
curs first unilaterally and only in some cases progresses to the contralateral limb [133].
What causes one limb to develop symptoms at first seems to be the missing puzzle in
the AT overuse-related injury problem. With that in mind, in order to establish effective
strategies to prevent overloading it is crucial to identify which magnitudes of inter-limb
differences are necessary to trigger differential adaptations in muscle-tendon properties
in habitual runners. Therefore, from findings of Study IV it seems plausible to recom-
mend coaches and clinicians to monitor AT properties bilaterally in order to identify ab-
rupt changes in tendon properties that could result in pathological conditions. Finally,
few studies have focused on the individual contribution of activation and forces from
triceps surae muscles to AT loading and change in its properties [47, 127]. With that in
mind, it seems relevant to future studies to clarify i) which magnitudes of mechanical
loading are important for tendon adaptation in habitual runners and ii) how inter and in-
tra-limb differences in muscle coordination strategies (e.g. EMG ratios) occurring
within triceps surae muscles would affect AT loading and possibly differential displace-
ments and strains during running.
6.5 Strengths and limitations
Strengths of this thesis are
• The inclusion of non-usually investigated habitual runners such as triathletes;
• The inclusion of submaximal running speeds not previously investigated;
• Standardization of limb preference assessment;
• The implementation of a statistical analysis considering the entire biomechanical
continuum of interest;
• The bilateral investigation of kinetic, kinematic and EMG variables simultaneously
during running;
• The first-time bilateral registration of MG-MTJ displacement during running;
• The inclusion of both male and female habitual runners.
• Limitations of this thesis are:
• Lack of a control run in Study I;
• A limited number of internal-loading related variables;
• A limited ultrasound sampling rate for MG-MTJ registration during running;
• To not address independently males and females;
57
A few other limitations were already considered in the Methodological Considerations
section.
6.6 Ethical considerations
This thesis aimed to be inclusive by having men and women as participants which is an
important aspect for equality in research practice. All participants were informed they
could stop participation in the study at any time, and received feedback on their evalua-
tions. All procedures and their purposes were made as clear as possible to participants.
Experimental protocols were designed to not have participants in the laboratory for
longer than necessary and any sort of psychological pressure on participants was
avoided. Considering findings from this thesis, it would be unethical from coaches and
clinicians to not monitor bilateral biomechanics and tendon characteristics of habitual
runners throughout the seasons if equipment is available for doing so. Preventive strate-
gies to avoid injury might be the most ethical path to follow.
6.7 Conclusions
Inter-limb differences in biomechanical and neuromuscular variables previously associ-
ated to AT overuse-related injuries occur in running conditions common to habitual run-
ners.
Inter-limb differences occurred in portions of the stance phase where AT loading is
known to be greater.
Triceps surae neuromechanical and Achilles tendon properties are similar among limbs
of habitual runners.
From a perspective of muscle-tendon capacity for managing running loads, tendons in
both limbs have equal chances of developing injury.
Coaches and clinicians should monitor neuromuscular and biomechanical inter-limb-
differences during running concomitantly with neuromechanical and tendon properties
adaptation across the season in order to prevent potentially harmful conditions for the
AT.
58
7 FUTURE DIRECTIONS
Investigations have been performed aiming to identify biomechanical causes of tendon
overuse injuries in runners [7-10, 13, 14, 52]. Regardless of valuable effort from those
studies, not only tendon but running overuse-related injury rates did not decline in the
past years [1, 2]. It seems therefore that experimental designs adopted in previous stud-
ies were not able to adequately address the ‘missing puzzle’ of the running injury prob-
lem [54, 134].
A strong evidence that inter-limb differences may be an important part of the that puzzle
and should be addressed in future studies resides in the fact that the majority of tendon
injuries occur unilaterally [22]. Furthermore, future studies on inter-limb differences
might further focus on the entire biomechanical continuum of interest approach for sta-
tistical analysis considering limitations of the summarized metrics procedure. Future
studies should also explore the effects of timing of gait events in the analysis of biome-
chanical continuums, since they were found to affect the results of methods designed for
time-varying analysis such as the SPM [135]. In conjunction with this, a more thorough
examination of internal-loading should be conducted, since there is a dearth of literature
on bilateral joint and muscle kinetics during running at different submaximal speeds and
fatigue levels. In this regard, recent advances in techniques for personalized musculo-
skeletal models [136-138] and wearables [139, 140] have the potential to enhance cur-
rent musculoskeletal loading estimations and to allow data to be registered during more
ecological conditions, which will certainly help to get closer to real-world running
loads. Another important direction will be the implementation of ultrafast ultrasound
which has the potential to adequately capture muscle-tendon dynamics [103, 141, 142],
in combination with algorithms capable of real-time tracking of muscle-tendon behavior
[143]. In addition to that, accurately quantifying the amount of mechanical stimulus ca-
pable to generate alterations in tendon morphological, mechanical and material proper-
ties in habitual runners by adopting prospective experimental designs [25, 144] is para-
mount to improve prevention and treatment strategies designed by coaches and clini-
cians regarding overuse-related injuries.
Lastly, overuse-related tendon injuries may not occur due to overloading solely. In vitro
studies [19] suggest tendon micro trauma followed by sub-optimal mechanical loading
could be an alternative explanation to the cascade of degenerative processes associated
with tendon damage and injury [19]. This proposed mechanism might be related to
59
compensations in the mechanical loading occurring between limbs after initiation of the
unilateral injury process, which could result in sub-loading of the injured tendon since
the other limb is still adequately managing loads. Currently no study has adopted the
sub-optimal loading theory in experimental designs involving frequently injured popula-
tions such as habitual runners.
60
8 SAMMANFATTNING
Överbelastningsskador på hälsenan är ett vanligt förekommande problem hos löpare.
Dessa skador uppträder inte sällan ensidigt och etiologin är förknippad med överbelast-
ning av senvävnaden. Bilaterala skillnader mellan ben under löpning är en möjlig orsak
till överbelastning på grund av eventuella skillnader i den mekaniska belastningen som
varje ben utsätts för. Sidoskillnader har beskrivits i hälsenans egenskaper hos idrottare
på grund av sportrelaterade skillnader i mekanisk belastning, och hos icke-idrottare på
grund av benpreferens. Sidoskillnader i hälsenans mekaniska egenskaper mellan ben
hos löpare har dock inte beskrivits tidigare. Denna avhandling undersökte förekomsten
av skillnader mellan benen i biomekaniska-, neuromekaniska- och hälsensegenskaper
hos löpare. I studie I utförde 13 triatleter en simulerad cykel till löpning transition och
den vertikala reaktionskraft (ground reaction force, GRFv), nedre extremiteternas kine-
matik, och muskelaktivering i triceps surae och tibialis anterior musklerna utvärderades
bilateralt under start-, mitten- och slutfasen av 5 km löpning på löpband. I studie II ut-
värderades GRFv, nedre extremiteternas kinematik, muskelaktivering i triceps surae och
tibialis anterior samt hälsenans töjning bilateralt hos löpare under två löphastigheter (2.7
m.s-1 och 4.2 m.s-1). I studie III utvärderades spatiotemporala variabler, den vertikala
(kVert) och extremitetens (kLimb) styvhet samt masscentrumets (centre of mass, COM)
kinematik bilateralt hos löpare under samma löphastigheter som i studie II. I studie IV
utvärderades den maximala isometriska plantarflexionsstyrkan, triceps surae-aktive-
ringen och aktiveringsförhållanden, och hälsenans morfologiska, mekaniska och materi-
alegenskaper bilateralt hos löpare. I studie I var soleus-aktiveringen lägre i det före-
dragna benet mellan 53.4% och 75.89% av stödfasen (p <0.01, ES-intervall = 0.59 till
0.80) i slutfasen av 5 km löpning. I studie II var höftextensionshastigheten snabbare i
det icke-föredragna benet mellan 71% och 93% av stödfasen (p <0.01) under löpning
vid 4.2 m.s-1. Inga andra skillnader mellan benen observerades. I studie III observerades
inga skillnader mellan extremiteterna i spatiotemporala variabler, kVert eller kLimb vid
de undersökta löphastigheterna. COM-horisontalhastigheten var snabbare från 67% till
61
87.40% av stödfasen (p <0.05, ES> 0.60) för det icke-föredragna benet. I studie IV ob-
serverades inga skillnader mellan extremiteterna i triceps surae-aktivering eller hälse-
nans egenskaper. Aktiveringsförhållandena för gastrocnemius medialis och soleus kor-
relerade endast i det föredragna benet.
Sammanfattningsvis beskrev avhandlingen bilaterala neuromuskulära och kinematiska
skillnader mellan extremiteterna när friska, icke-skadade löpare sprang under förhållan-
den som liknade deras ekologiska träningssituation. Dessutom verkar hälsenan anpassa
sig lika bilateralt hos löpare, medans aktiveringsstrategier för triceps surae kan skilja sig
mellan benen. Upptäckterna av skillnader mellan extremiteter under löpning kan vara
relevanta för att undvika överbelastning och skillnaderna kan vara viktiga för etiologin
av överbelastningsskador i hälsenan hos löpare. Att senegenskaperna inte skilde sig bi-
lateralt tyder på att båda ben är lika utsatta för skaderisker. Tränare och kliniker kan för-
bättra nuvarande förebyggande strategier för överbelastningsskador på hälsenan genom
att övervaka senegenskaper och biomekaniska och neuromuskulära variabler bilateralt
under löpning över säsongen.
62
9 ACKNOWLEDGMENTS
I’m truly thankful to all of whom directly or indirectly provided support to this work.
A special thanks to my supervisors Rodrigo Bini and Toni Arndt who provided me an
invaluable chance to improve as an investigator. I’ll bring forward the lessons learned
from you.
Thanks to the GIH staff for the innebandy lessons and chats during lunch time.
Thanks to all GIH lecturers and professors who encouraged me - directly or indirectly -
to keep following the ideas I had in mind.
A big thanks to everyone in the PhD room. There we had great discussions about every-
thing (although only 10% was related to science).
Thanks to the incredibly smart and sport-focused students/researchers I crossed by
while working on this thesis. You were all source of inspiration with your applied pas-
sion and curiosity about sport and human movement.
Grazie to the Italian crew I met in the final months of my PhD for such energy. I hope to
catch you in Italia one day.
A big thanks to all people who volunteered to the studies presented here. Your excite-
ment and engagement with sport research was certainly motivating.
Thanks to the Swedish Research Council for Sport Science (CIF) for partially funding
this work. Thanks to the Brazilian Council for Scientific and Technological Develop-
ment (CNPq) for fully funding this work.
A huge final thanks to my family for helping me to develop a free and curious mind.
You were always clear examples of endurance and innovation. I’ll look for you.
63
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APPENDIX
Pearson’s correlation analysis between activation ratios and peak activations in the
preferred (upper plots) and non-preferred (lower plots) limb. MG = medial
gastrocnemius; LG = lateral gastrocnemius; SOL = soleus; GAS = gastrocnemii.
