Different running patterns along the aerial-terrestrial continuum can result in similar running economy

Abstract

Purpose:
There is no unique or 'ideal' running pattern that is the most economical for all runners. Classifying the global running patterns of individuals into two categories (aerial and terrestrial) using the Volodalen® method could permit a better understanding of the relationship between running economy (RE) and biomechanics. The main purpose was to compare RE between aerial and terrestrial runners.

Methods:
Two coaches classified 58 runners into aerial (n=29) or terrestrial (n=29) running patterns on the basis of visual observations. RE, muscle activity, kinematic, and spatiotemporal parameters of both groups were measured during a 5-min run at 12km·h-1 on a treadmill. Maximal oxygen uptake (VO2max) and peak treadmill speed (PTS) were assessed during an incremental running test.

Results:
No differences were observed between aerial and terrestrial patterns for RE, VO2max, and PTS. However, at 12km·h-1, aerial runners exhibited earlier gastrocnemius lateralis activation in preparation for contact, lesser dorsi-flexion at ground contact, higher co-activation indexes, and greater leg stiffness during stance phase than terrestrial runners. Terrestrial runners had more pronounced semitendinosus activation at the start and end of the running cycle, shorter flight time, greater leg compression, and a more rearfoot strike.

Conclusions:
Different running patterns were associated with similar RE. Aerial runners appear to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas terrestrial runners appear to propel the body more forwards rather than upwards to limit work against gravity. Excluding runners with a mixed running pattern from analyses did not affect study interpretation.

Full text

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Note. This article will be published in a forthcoming issue of the
International Journal of Sports Physiology and Performance. The article
appears here in its accepted, peer-reviewed form, as it was provided by
the submitting author. It has not been copyedited, proofread, or formatted
by the publisher.
Section: Original Investigation
Article Title: Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in
Similar Running Economy
Authors: Thibault Lussiana1,2, Cyrille Gindre2,3, Kim Hébert-Losier4, Yoshimasa Sagawa5,6,
Philippe Gimenez1, and Laurent Mourot1,7
Affiliations: 1Research unit EA4660, Culture Sport Health Society and Exercise Performance
Health Innovation platform, Bourgogne Franche-Comté University, Besançon, France;
2Volodalen Company, Research and Development Department, Chavéria, France; 3Volodalen
Suisse Company, Research and development department, Leysin, Switzerland; 4Department of
Sports Science, National Sports Institute of Malaysia, National Sports Complex, Bukit Jalil, Peti
Surat 7102, Kuala Lumpur, Malaysia; 5Laboratoired’ExplorationFonctionnelle Clinique du
Mouvement, CHRU of Besançon 25000, France; 6Integrative and clinical neurosciences EA481,
Bourgogne Franche-Comté University, Besançon, France; 7Clinical Investigation Centre,
INSERM CIT 808, CHRU of Besançon, Besançon, France.
Journal: International Journal of Sports Physiology and Performance
Acceptance Date: August 1, 2016
©2016 Human Kinetics, Inc.
DOI: http://dx.doi.org/10.1123/ijspp.2016-0107

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Title: Different running patterns along the aerial-terrestrial continuum can result in similar running
economy
Submission type: Original investigation
Authors: Lussiana Thibault1,2,*, Gindre Cyrille2,3, Hébert-Losier Kim4, Sagawa Yoshimasa5,6,
Gimenez Philippe1, and Mourot Laurent1,7
Affiliations:1 Research unit EA4660, Culture Sport Health Society and Exercise Performance
Health Innovation platform, Bourgogne Franche-Comté University, Besançon 25000, France;2
Volodalen Company, Research and development department, Chavéria 39270, France; 3
Volodalen Suisse Company, Research and development department, Leysin 1854, Switzerland; 4
Department of Sports Science, National Sports Institute of Malaysia, National Sports Complex,
Bukit Jalil, Peti Surat 7102, Kuala Lumpur 57000, Malaysia;
5Laboratoired’ExplorationFonctionnelle Clinique du Mouvement, CHRU of Besançon 25000,
France; 6 Integrative and clinical neurosciences EA481, Bourgogne Franche-Comté University,
Besançon 25000, France; 7 Clinical Investigation Centre, INSERM CIT 808, CHRU of Besançon,
Besançon 25000, France.
* Corresponding author: Thibault Lussiana; Address: 31 Chemin de l’Epitaphe, 25000
Besançon; Phone: +33 6. 32 42 43 43; E-mail: thibault.lussiana@gmail.com
Preferred running head: Running patterns and running economy
Abstract word count: 248 / 250 words
Text-only word count after revision: 4126 / 3500 words
Number of figures and tables: 5 figures and 2 tables

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
1. Abstract
Purpose: There is no unique or 'ideal' running pattern that is the most economical for all runners.
Classifying the global running patterns of individuals into two categories (aerial and terrestrial)
using the Volodalen® method could permit a better understanding of the relationship between
running economy (RE) and biomechanics. The main purpose was to compare RE between aerial
and terrestrial runners. Methods: Two coaches classified 58 runners into aerial (n=29) or terrestrial
(n=29) running patterns on the basis of visual observations. RE, muscle activity, kinematic, and
spatiotemporal parameters of both groups were measured during a 5-min run at 12km·h-1 on a
treadmill. Maximal oxygen uptake (V;.O2max) and peak treadmill speed (PTS) were assessed
during an incremental running test. Results: No differences were observed between aerial and
terrestrial patterns for RE, V;.O2max, and PTS. However, at 12km·h-1, aerial runners exhibited
earlier gastrocnemius lateralis activation in preparation for contact, lesser dorsi-flexion at ground
contact, higher co-activation indexes, and greater leg stiffness during stance phase than terrestrial
runners. Terrestrial runners had more pronounced semitendinosus activation at the start and end of
the running cycle, shorter flight time, greater leg compression, and a more rearfoot strike.
Conclusions: Different running patterns were associated with similar RE. Aerial runners appear
to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas
terrestrial runners appear to propel the body more forwards rather than upwards to limit work
against gravity. Excluding runners with a mixed running pattern from analyses did not affect study
interpretation.
Keywords: running patterns, economy, biomechanics, muscle activity, optimization strategies

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
2. Introduction
Running economy (RE) is an important determinant of running performance.1 Running
biomechanics influences RE, although the nature and magnitude of the relationship is debated.1
For instance, studies have associated both long2 and short3 contact time with enhanced RE. In
contrast, other studies have found no relationship between contact time and RE.4 Similarly, both
rearfoot5 and non-rearfoot6 strike patterns are suggested to be more economical, with Gruber et
al.7 reporting no marked difference in RE on the basis of footstrike pattern, with the self-selected
footstrike being the most economical. Oxygen consumption has been shown to increase linearly
with the muscle electromyographic (EMG) activity of the biceps femoris during the braking phase
of running, whereas an increased co-activation of agonist and antagonist muscles prior to and
following ground contact enhances knee and ankle joint stiffness,8 which enhances force
potentiation during push-off and reduces metabolic cost. Overall, while several studies have
identified relationships between biomechanical factors and RE, results are controversial and
practical applications are unclear.
All considered, it is likely that there is no unique or 'ideal' running pattern that is the most
economical for all runners.1 The Volodalen® method (see below) allows the classification of
runners through visual observation under the premise that runners are a global and dynamic system
that seek to optimize RE.9 This method is very practical in nature, and allows coaches, clinicians,
and scientists to quickly classify the running patterns of individuals along a continuum based on
visual observations. Overall, the method describes two different strategies to optimize RE: one
that relies more on the ability to propel the body forward rather than upwards, and another that
relies more on the ability to store and release elastic energy.10 Individuals who use the first strategy
are called terrestrial runners, while those who use the second are called aerial runners.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Anecdotally, coaches report the presence of both types of runners across the competition spectrum,
with the aerial and terrestrial patterns observed in both recreational and highly-competitive
runners.
Recently, these two running patterns assessed on the basis of five subjectively-evaluated
criteria (Figure 1) were shown to demonstrate distinct objectively-assessed running
characteristics.9 More specifically, aerial runners exhibit shorter contact times, greater leg
stiffness, and longer flight times than terrestrial runners, as well as larger vertical displacements
of the center of mass and maximal vertical ground reaction forces.9 Given the scientific literature
suggesting that self-selected running patterns are the most economical7 and the observed presence
of both aerial and terrestrial runners across the competition spectrum, we can anticipate no
difference in the RE of aerial and terrestrial runners. However, this assumption has not yet been
verified experimentally.
Thus, our main aim was to compare the RE of aerial and terrestrial runners. A secondary
aim was to investigate the muscle activity and biomechanics of the aerial and terrestrial runners
during running to objectify the biomechanical strategies used by both groups. Finally, to verify
that differences between groups were not due to maximal running performance levels, we aimed
to compare maximal aerobic capacities between both groups. We hypothesized that aerial and
terrestrial runners would demonstrate similar RE values despite distinct electromyographic and
biomechanical characteristics.
3. Methods
Participants
Fifty-eight recreational male runners [mean ± standard deviation (SD): age 30 ± 8 y, height
177 ± 5 cm, and body mass 72 ± 9 kg] voluntarily participated in this study. Inclusion criteria were

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
good self-reported general health, absence of lower-extremity injury for the last year, and ability
to run submaximally at 12 km·h-1. To limit confounding variables, only males were recruited. All
participants were tested within a 2-month period. The university’s Institutional Review Board
approved the study protocol prior to participant recruitment (CPP: 2014-A00336-41), which was
conducted in accordance with international ethical standards and adhered to the Declaration of
Helsinki of the World Medical Association.
Design
Each participant completed one experimental session in our laboratory. After providing
written informed consent, participants ran a 5-min warm-up on a treadmill (Training Treadmill
S1830, HEF Techmachine, Andrzieux-Bouthon, France) at 10 km·h-1 with no inclination.
During this warm-up, two running coaches with more than 5 years of experience using the
Volodalen® method focused on the global movement patterns of participants with a particular
attention given to five key elements (Figure 1).9 Each criterion was scored between 1 and 5
following the attainment of a consensus between coaches. The global subjective score (V®score),
which is the sum of each individual score, allows the classification of runners into two different
categories: terrestrial (V®score ≤ 15) or aerial (V®score > 15) runners. A score of 15 reflects the mid-
point of the scale, making the use and interpretation of the V®score practical and simple. The V®score
demonstrates adequate intra- and inter-rater reliability (intra-class correlation coefficient,
ICC:0.940 and 0.945; standard error of the mean (SEM):1.28 and 1.31).9
In the present study, 29 participants were classified as aerial runners (V®score: 19.3 ± 2.5)
and the remaining 29 were classified as terrestrial runners (V®score: 11.5 ± 2.0). The baseline
characteristics of runners were similar between the two groups (aerial vs. terrestrial: age 29 ± 9 vs.
30 ± 9 y, height 178 ± 6 vs. 177 ± 5 cm, and body mass 72 ± 9 vs. 71 ± 8 kg, all P > 0.390).

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Following the warm-up, participants performed a submaximal running test and a maximal
incremental running test. Tests were interspersed by a 5-min passive recovery in the seated
position. All subjects were familiar with running on a treadmill as part of their usual training
programs and wore their habitual running shoes (aerial vs. terrestrial: mass 317 ± 50 vs. 300 ± 55
g, heel height 22 ± 5 vs. 20 ± 4 mm, and drop of 9 ± 4 vs. 9 ± 3 mm; all P > 0.249).
Submaximal running test
Participants ran 5 min on a treadmill at 12 km·h-1. This speed was chosen based on
participants’ running performance to avoid efforts above ventilatory threshold. Gas exchange was
measured breath-by-breath using a gas analyzer (Cortex Metamax 3B, Cortex Biophysik, Leipzig,
Germany) and subsequently averaged over 10-s intervals throughout the test. Before each test, the
gas analyzer was calibrated following the manufacturer’s recommendations using ambient air (O2:
20.93% and CO2: 0.03%) and a gas mixture of known composition (O2: 15.00% and CO2: 5.00%).
The spirometer was calibrated using a 3-L syringe. Respiratory exchange ratios (RER), oxygen
uptake (V;.O2), and carbon dioxide output (V;.CO2) were averaged over the last 1-min of the 5-
min running trial. Steady state was confirmed through visual inspection of the V;.O2V;.CO2 curves.
RER had to remain below 1.0 during the trials for data to be included in the analysis, or else the
corresponding data were excluded as deemed to not represent a submaximal effort. RE was
expressed as the distance covered per V;.O2 per body mass (m·ml-1·kg-1)11 and was calculated from
the running velocity divided by the net V;.O2, normalized to individual body mass, where net V;.
O2 is the V;.O2 measured during running minus the resting V;.O2 (averaged over the last 1-min of
a prior 5-min of passive recovery). RE was also expressed as the kilocalories required per distance
covered per body mass (kcal·km-1·kg-1).12

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
An optical measurement system (Optogait®, MicroGate Timing and Sport, Bolzano, Italy)
sampling at 1000 Hz was used to record contact (tc, s) and flight (tf, s) times during the last 1-min
of the 5-min submaximal running trial. As described by Morin et al.13 the spring-mass
characteristics of the lower extremity were estimated using a sine-wave model employing tc, tf,
velocity (v), body mass (m), and leg length (L, the distance between the greater trochanter and the
ground measured in barefoot upright stance). Vertical stiffness (kvert, kN·m-1) was calculated as the
ratio between the maximal vertical force (Fmax, kN) and center of mass displacement (Δz, m) using
the following equations:
   (1)
 

  (2)


 
 (3)
Leg stiffness (kleg, in kN·m-1) was calculated as the ratio between the Fmax and the maximal leg
length deformation, i.e., leg spring compression (ΔL, m), using the following equations:
   (4)

 (5)
where d represents the distance of the point of force application translation, estimated for each
individual to equal 18 % of their leg length.
A high-speed video camera (Sony HDRSR7E, Sony Corporation, Tokyo, Japan) was
placed 2 m from and perpendicular to the acquisition space on a 0.45 m support to capture sagittal
plane kinematics at 200 Hz. Circular opaque markers of 9 mm in diameter were positioned on the
right leg over the greater trochanter, lateral femoral condyle, lateral malleolus, and fifth metatarsal

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
phalangeal joint to assist in computing joint angles. The video sequences were analyzed off-line
using Dartfish Pro Analysis software version 5.5 (Dartfish, Fribourg, Switzerland) to determine
knee (αknee), plantar-flexion (αankle), and foot-ground (αstrike) angles (°) at footstrike during the 1-
min data collection intervals designated above. The αknee was determined using the lines
connecting the lateral malleolus to the lateral femoral condyle and the lateral femoral condyle to
the greater trochanter; the αankle was determined using the lines connecting the fifth metatarsal
phalangeal joint to the lateral malleolus and the lateral malleolus to the lateral femoral condyle;
and the αstrike was determined using the line connecting the tuber calcanei to the fifth metatarsal
phalangeal joint relative to the plane of the treadmill. The reliability of this procedure has been
analysed previously in our laboratory with ICC and SEM values ranging from 0.88-0.98 and 1.1-
1.3° for αknee, αankle, and αstrike. Strike pattern was classified as described by Altman and Davis:14
midfoot strike = -1.6 ° <αstrike< 8.0 °, rearfoot strike = αstrike> 8.0 °, and a forefoot strike = αstrike<-
1.6 °.
EMG activity of the rectus femoris (RF), semitendinosus (ST), tibialis anterior (TA), and
gastrocnemius lateralis (GL) muscles of the right leg was evaluated with pre amplified single
differential surface electrodes (Trigno Wireless, EMG, Delsys Inc, Natick, MA, USA) with an
inter electrode distance of 10 mm and a common mode rejection ratio of 92 dB. The skin
preparation and electrode placements were done according to SENIAM recommendations.15 EMG
and temporal events (i.e., footstrike and toe off recorded with the Optogait®) were synchronized
between systems using ADInstruments system and software (Labchart 7.0, ADInstruments ltd,
Oxford, United Kingdom).Custom scripts developed in Matlab (MathWorks) were used to process
the EMG signals. First, EMG signals were filtered using a second order Butterworth band-pass
filter from 20 to 480 Hz. To generate an EMG profile, signals were then rectified and passed

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
through a critically damped low-pass filter with a 20-Hz cut-off to create a linear envelope. To
produce a representative EMG pattern, 70 consecutive running steps taken from the last 1-min of
the 5-min submaximal running trial were averaged for each individual,16 with the signals being
time normalized to the running cycle (i.e., right foot contact to right foot contact representing 100%
of a cycle).
The EMG activity of each muscle was quantified using the root mean square amplitude
(microvolts) and expressed as a percentage of the peak signal (RMS, in %) captured during the
running trial for each individual. The time of peak activity of each muscle was determined and
expressed as a percentage of the running cycle (peak, in %). In addition, the mean and standard
deviation (± SD) muscle activity were computed for the following sub-phases of the running cycle:
first contact phase (0 to 50% of the stance phase), second contact phase (50 to 100% of the stance
phase), first swing phase (0 to 80% of the swing phase), and second swing phase (80 to 100% of
the swing phase). Co-activation indexes (CO, in %) between the RF/ST and the TA/GL muscles
were also computed for these four sub-phases following the method proposed by Winter.17 More
specifically, agonist and antagonist muscles that show a common area of activity defines a co-
contraction area, with the CO calculated as:
 
  (6)
Maximal incremental test
The maximal incremental running test was performed on the treadmill starting at 10 km·h-
1. The treadmill speed was subsequently increased by 0.5 km·h-1 every minute until volitional
exhaustion. The participants received strong verbal encouragement to ensure attainment of
maximal values during the test. The maximal oxygen uptake (V;.O2max), averaged over 30-s, was

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
said attained when two or more of the following criteria were met: an increase in V;.O2 less than
2.1 ml·kg-1·min-1between two consecutive stages,18 an RER greater than 1.1,19 and/or a heart rate
(RS810, Polar Electro Oy, Kempele, Finland) of ± 10 beats per minute of the predicted maximal
heart rate value (i.e., 220 minus age).19 The highest velocity achieved during the test was recorded
as the peak treadmill speed (PTS). When the participant could not complete the last stage
completely (< 1 min), the PTS was calculated using fractional time supported during the last stage
multiplied by the speed-increment rate.
Statistics
Descriptive statistics of data are presented as mean ± SD values. Since all data were
normally distributed on the basis of the Kolmogorov-Smirnov test, parametric statistical methods
were employed for data analysis. Two-tailed t-tests were used to examine differences between the
two groups of runners. RE and maximal incremental test data were also compared between groups
using data from extreme aerial (n = 14, V®score = 21.5 ± 1.6) and terrestrial (n = 14, V®score = 9.6 ±
1.5) runners to limit confounding from individuals with mid-range V®score values. Pearson
correlation coefficients and their 90% confidence limits (r [lower, upper]) were calculated to assess
the relation between V®score and RE, PTS, and V;.O2max. The following criteria were adopted to
interpret the magnitude of the correlation: ≤0.1, trivial; >0.1–0.3, small; >0.3–0.5, moderate; >0.5–
0.7, large; >0.7–0.9, very large; and >0.9–1.0, almost perfect.20 A correlation was deemed unclear
when its confidence limits overlapped the thresholds for small positive and small negative
correlations (i.e., that is, chances of the correlation being positive and negative were both >5%).20
Statistical significance was accepted when the overall P value was <0.05, with statistics performed
in SigmaStat 12 for Windows (Systat Software Inc., San Jose, CA, USA) and in Microsoft Excel

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
(Microsoft Corp., Redmond, WA, USA) using Hopkins spreadsheet (http://www.sportsci.org).
4. Results
RE and performance
RE measured at 12 km·h-1, PTS, and V;.O2max were similar between aerial and terrestrial
runners (see histograms in Figure 2, all P> 0.120), as well as between extreme aerial and terrestrial
runners (see circles in Figure 2, all P> 0.101). The most economical aerial and terrestrial runner
had quite similar RE values (aerial vs. terrestrial runner: 6.00 vs. 5.94 m·ml-1·kg-1 and 0.825 vs.
0.834 kcal·km-1·kg-1).
Correlations between V®score and RE, expressed as m·ml-1·kg-1 and kcal·km-1·kg-1, were
trivial and unclears (r = -0.08 [-0.29, 0.11], P = 0.523 and r = 0.097 [-0.12, 0.28], P = 0.378,
respectively). Correlations were small and clear between V®score and PTS (r = -0.27 [-0.45, -0.07],
P = 0.035), as well as between V®score and V;.O2max (r = -0.29 [-0.47, -0.10], P = 0.027).
Electromyography
Activation profiles of the RF, ST, TA, and GL muscles recorded during the submaximal
running trial in one representative aerial and terrestrial runner are presented in Figure 3. The aerial
group showed an earlier peak GL activity and later peak TA activity than the terrestrial group (see
Figure 4).
5. Discussion
This study demonstrates for the first time that aerial and terrestrial running patterns,
determined using a subjective rating scale, exhibit similar RE despite demonstrating distinct
biomechanical and electromyographic characteristics. Our study adds to the scientific literature

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
indicating that different global running patterns can lead to similar running economy, reflecting
results from previous work with a focus on footstrike pattern.7
The GL showed an earlier activation onset in preparation for landing and reached peak
activation more quickly following ground contact in the aerial compared to the terrestrial runners
(Figure 4), with the aerial pattern demonstrating more positive ankle (i.e., lesser dorsi-flexion)
and negative foot-ground (i.e., lesser rearfoot strike) angles at foot strike. Landing in a more
plantar-flexed position suggests an increased capacity of the passive structures to store elastic
energy at the beginning of the stance phase.21 Greater activation of the plantar-flexors in
preparation for ground contact and during the braking phase can increase the utilization of elastic
energy during human locomotion,22 with pre-activation increasing leg stiffness23 and stretch-
shortening cycle efficiency.24 Furthermore, the aerial runners demonstrated higher co-activation
indexes during the stance phase than the terrestrial runners, suggesting superior knee joint stiffness,
corroborating with the higher leg stiffness values we observed in the aerial group. By investigating
joint-angle moment curves and muscle activity patterns at different running speeds, Kyrlinen et
al.8 inferred that increases in muscle stiffness around the knee and ankle joints during the early
stance phase of running enhanced force potentiation during push-off and increased the mechanical
efficiency of runners. Furthermore, the coupling time (i.e., time between stretching and shortening
of muscle tendon units during the stretch-shortening cycle) is positively related to contact time,
with short coupling times believed to reflect a more efficient utilization of elastic energy during
the stretch-shortening cycle.25 We propose that the aerial runners self-optimization strategy is to
enhance force generation via a more efficient utilization of the stretch-shortening cycle and to limit
the braking phase by contacting the ground close to the center of mass (Figure 5).

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Aura and Komi26 highlighted that there may be substantial inter-individual differences in
one’s ability to store and release elastic energy. Here, the aerial and terrestrial running patterns
showed no differences in RE despite demonstrating distinct neuromuscular and biomechanical
characteristics, suggesting that different biomechanical strategies can lead to a similar oxygen cost
of running. Terrestrial runners contacted the ground more in front of their center of mass (based
on the visual observation) and with more pronounced ankle dorsi-flexion and rearfoot strike than
aerial runners, which was followed by a greater leg compression during stance and longer contact
time. There is evidence to suggest the existence of an inverse relationship between the energy cost
of running, wherein longer contact times are associated with lower rates of energy consumption.27
In fact, a longer contact time allows force to be generated over a longer period of time.27 Thus,
strategies associated with longer ground-contact times, such as rearfoot strike patterns,5 allow
runners to be economical without necessarily promoting the storage and release of elastic energy
through the mechanism described above. These arguments are supported by a recent study wherein
habitual rearfoot strikers had shorter flight times and longer ground contact times than habitual
forefoot strikers, as well as 5.4 and 9.3% better RE at 11 and 13 km·h-1, respectively.5
The EMG analysis showed that the ST muscle of the terrestrial runners worked at a higher
percentage of its peak recorded amplitude during the first contact and second flight phases than
the aerial pattern. These results are consistent with observations by Yong et al.28of greater activity
(normalized to the peak found during walking) of the lateral hamstring muscle during the terminal
swing phase in natural rearfoot strikers. The hip extensor muscles are important in driving the body
powerfully forward8 as a more horizontal resultant ground reaction force vector has been recently
associated with a better running economy.29 Ultimately, using energy to drive the body forward
rather than upwards can reduce the oxygen cost of running, as smaller vertical displacements of

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
the center generally improves running economy.30 Although it is difficult to directly compare the
level of muscle activity between groups given the dynamic normalization method used in this
study, we propose that terrestrial runners self-optimize their running pattern by propelling the body
forwards rather than upwards and limiting the work against gravity.
The correlation coefficients between V®score and RE (expressed as m·ml-1·kg-1 or kcal·km-
1·kg-1) were trivial and unclears, supporting our results of no meaningful difference in the RE of
aerial and terrestrial runners. On the other hand, the small negative correlations between V®score
and PTS, as well as V®score and V;.O2max are suggestive of a tendency towards better performance
during the maximal incremental test in our terrestrial compared to our aerial runners.
Unfortunately, at the time of participant recruitment and data collection, we did not seek to collect
data regarding the distances and types of events that our runners preferred or in which they
performed better. The recreational level of our runners may limit the generalization of the current
study findings.
Moreover, the assessment of RE at a unique submaximal speed (i.e., 12 km∙h-1) limits
inferences to slower and faster speeds as aerial and terrestrial runners might show different RE
responses to changes in running speed. For instance, given the enhanced contribution from the
storage and release of elastic energy to running as speed increases,31 aerial runners may be
relatively more economical than terrestrial runners at faster speeds, and inversely at slower speeds.
Another consideration here is the threshold used to classify aerial and terrestrial runners.
Consistent with previous investigations,9,10 a cut-off score of 15 was chosen to classify runners in
order to facilitate the use and interpretation of the V®score, and data from all participants were
included in the analysis to reflect the reality of the population and represent the entire running
pattern continuum. Although excluding runners with mid-range V®score values did not meaningfully

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
influence RE and PTS interpretation, further validation of the use of a two-group classification
system with a deterministic V®score of 15 is needed.
6. Practical applications
From a practical perspective, fix, bend, roll, and push summarizes the terrestrial self-
optimization strategy; whereas fly, touch, and bounce summarizes the aerial one. As running
pattern can vary under different conditions (e.g., in a fatigued state or under psychological stress),
we advise coaches to assess their athletes more than once before using the V®score to inform their
training prescription. In any case, through a better understanding of these biomechanical strategies
and their relationships with RE at an individual level, our results could assist athletes and coaches
to individualize exercise prescription, thereby improving training responses. Athletes and coaches
can modify certain aspects of the running technique, favoring either the aerial or terrestrial pattern
or even both depending on training objectives and what might benefit the athlete the most.
However, a cross-over intervention study assessing the effect of a training program targeting either
the stretch shortening cycle or forward propulsion on the RE of aerial and terrestrial runners is
warranted. Also, it should be mentioned that running technique is not the only factor to influence
RE. There are several other biomechanical and physiological factors that are involved, which were
not evaluated in the current study.
7. Conclusions
Aerial and terrestrial runners demonstrate similar RE measures despite exhibiting distinct
running biomechanics and electromyographic characteristics. Aerial runners exhibited earlier GL
activation, lesser dorsi-flexion, and higher co-activation indexes and leg stiffness than terrestrial
runners. Terrestrial runners showed more pronounced recruitment of the ST in the late swing phase

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
and early ground contact phase, longer contact time, and greater leg compression than aerial
runners. In fact, aerial runners appear to benefit from storing and release of elastic energy (i.e.,
shorter coupling times and higher leg stiffness) to a greater extent than terrestrial runners who
appear to propel the body more forwards rather than upwards to minimize oxygen cost. Given that
the Volodalen® method classifies runners along a continuum, the current study results also include
runners with a mixed running pattern who employ both aerial and terrestrial strategies to varying
extents (i.e., more mid-range V®score). Excluding these mixed runners from analyses still support
that aerial and terrestrial running patterns have similar RE, which is achieved through different
biomechanical and neuromuscular means. Both strategies involve a certain trade-off given that the
aerial strategy encourages vertical oscillation and work against gravity, whereas the terrestrial
strategy limits the energetic contribution from the stretch-shortening cycle. Whether one can
benefit fully from the economical advantages of both strategies is not certain as a trade-off between
strategies appears unavoidable.
8. Acknowledgements
This study was supported by the University of Bourgogne Franche-Comté (France) and the
Exercise, Performance, Health, and Innovation Platform of Besançon. We thank Matsport and
Compressport companies for the loan of equipment. We also thank the participants for their
availability and active participation. The results of the current study do not constitute endorsement
of the product by the authors or the journal.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
9. References
1. Moore IS. Is There an Economical Running Technique? A Review of Modifiable
Biomechanical Factors Affecting Running Economy. Sports Med. 2016; 46(6):793-807.
2. Støren Ø, Helgerud J, Hoff J. Running stride peak forces inversely determine running
economy in elite runners. J Strength Cond Res. 2011;25(1):117-123.
3. Paavolainen LM, Nummela AT, Rusko HK. Neuromuscular characteristics and muscle
power as determinants of 5-km running performance. Med Sci Sports Exerc.
1999;31(1):124-130.
4. Williams KR, Cavanagh PR. Relationship between distance running mechanics, running
economy, and performance. J Appl Physiol. 1987;63(3):1236-1245.
5. Ogueta-Alday A, Rodríguez-Marroyo JA, García-López J. Rearfoot striking runners are
more economical than midfoot strikers. Med Sci Sports Exerc. 2014;46(3):580-585.
6. Di Michele R, Merni F. The concurrent effects of strike pattern and ground-contact time
on running economy. J Sci Med Sport. 2014;17(4):414-418.
7. Gruber AH, Umberger BR, Braun B, Hamill J. Economy and rate of carbohydrate oxidation
during running with rearfoot and forefoot strike patterns. J Appl Physiol. 2013;115(2):194-
201.
8. Kyröläinen H, Belli A, Komi PV. Biomechanical factors affecting running economy. Med
Sci Sports Exerc. 2001;33(8):1330-1337.
9. Gindre C, Lussiana T, Hebert-Losier K, Mourot L. Aerial and terrestrial patterns: a novel
approach to analyzing human running. Int J Sports Med. 2016;37(1):25-26.
10. Lussiana T, Gindre C. Feel your stride and find your preferred running speed. Biol Open.
2016;5(1):45-48.
11. Turner AM, Owings M, Schwane JA. Improvement in running economy after 6 weeks of
plyometric training. J Strength Cond Res. 2003;17(1):60-67.
12. Jeukendrup AE, Wallis GA. Measurement of substrate oxidation during exercise by means
of gas exchange measurements. Int J Sports Med. 2005;26(1):28-37.
13. Morin JB, Dalleau G, Kyröläinen H, Jeannin T, Belli A. A simple method for measuring
stiffness during running. J Appl Biomech. 2005;21(2):167-180.
14. Altman AR, Davis IS. A kinematic method for footstrike pattern detection in barefoot and
shod runners. Gait Posture. 2012;35(2):298-300.
15. Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for
SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol.
2000;10(5):361-374.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
16. Hug F. Can muscle coordination be precisely studied by surface electromyography? J
Electromyogr Kinesiol. 2011;21(1):1-12.
17. Winter DA. Biomechanics and motor control of human movement. Wiley-Interscience.
Toranto-Ontario; 1990.
18. Taylor HL, Buskirk E, Henschel A. Maximal oxygen intake as an objective measure of
cardio-respiratory performance. J Appl Physiol. 1955;8(1):73-80.
19. Howley ET, Bassett DR, Welch HG. Criteria for maximal oxygen uptake: review and
commentary. Med Sci Sports Exerc. 1995;27(9):1292-1301.
20. Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in
sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):3-13.
21. Lieberman DE, Venkadesan M, Werbel WA, et al. Foot strike patterns and collision forces
in habitually barefoot versus shod runners. Nature. 2010;463(7280):531-535.
22. Ishikawa M, Pakaslahti J, Komi PV. Medial gastrocnemius muscle behavior during human
running and walking. Gait Posture. 2007;25(3):380-384.
23. Moritz CT, Farley CT. Human hopping on very soft elastic surfaces: implications for
muscle pre-stretch and elastic energy storage in locomotion. J Exp Biol. 2005;208(5):939-
949.
24. Finni T, Ikegawa S, Komi PV. Concentric force enhancement during human movement.
Acta Physiol Scand. 2001;173(4):369-377.
25. Kobsar D, Barden J. Contact time predicts coupling time in slow stretch-shortening cycle
jumps. J Strength Cond Res. 2011;25:51-52.
26. Aura O, Komi PV. The mechanical efficiency of locomotion in men and women with
special emphasis on stretch-shortening cycle exercises. Eur J Appl Physiol. 1986;55(1):37-
43.
27. Kram R, Taylor CR. Energetics of running: a new perspective. Nature.
1990;346(6281):265-267.
28. Yong JR, Silder A, Delp SL. Differences in muscle activity between natural forefoot and
rearfoot strikers during running. J Biomech. 2014;47(15):3593-3597.
29. Moore IS, Jones AM, Dixon SJ. Reduced oxygen cost of running is related to alignment of
the resultant GRF and leg axis vector: A pilot study. Scand J Med Sci Sports. July 2015.
doi:10.1111/sms.12514.
30. Halvorsen K, Eriksson M, Gullstrand L. Acute effects of reducing vertical displacement
and step frequency on running economy. J Strength Cond Res. 2012;26(8):2065-2070.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
31. Lai A, Schache AG, Lin Y-C, Pandy MG. Tendon elastic strain energy in the human ankle
plantar-flexors and its role with increased running speed. J Exp Biol. 2014;217(17):3159-
3168.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Figure 1: Subjective grid of the Volodalen® method to assess the individual running pattern.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Figure 2: Running economy (RE) expressed as m·ml-1·kg-1 and as kcal·km-1·kg-1, peak treadmill
speed (PTS), and maximal oxygen uptake (V;.O2max) obtained during the maximal incremental
test in aerial and terrestrial patterns.
Note – Values are mean ± SD (error bars). More positive RE values indicate better RE. The circles
represent the values obtained from the exclusion of 30 participants with mid-range V®score values.
White circles are the mean values of 14 extreme aerial runners (V®score = 21.5 ± 1.6), while black
circles are the mean values of 14 extreme terrestrial runners (V®score = 9.6 ± 1.5).

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Figure 3: Illustrations of mean ± SD muscle activation during the submaximal running (12 km·h-
1) trial in one typical terrestrial (left figure) and aerial (right figure) runner, expressed as a
percentage of the running cycle.
Note – Dashed lines delineate toe off events.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Figure 4: Time of peak activity of the rectus femoris (RF-peak), semitendinosus (ST-peak), tibialis
anterior (TA-peak), and gastrocnemius lateralis (GL-peak) muscles obtained during the
submaximal running (12 km·h-1) trial in aerial and terrestrial groups.
Note – Values are mean ± SD (error bars).

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Figure 5: Illustration summarizing the biomechanical and electromyographic characteristics of
both 1) aerial and 2) terrestrial self-optimizations.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Table 1: Contact (tc) and flight (tf) times, step frequency (f), downward displacement of the center of mass (Δz), leg compression during
stance (ΔL), maximal force (Fmax), vertical (kvert) and leg (kleg) stiffness, and knee (αknee), ankle (αankle), and foot-ground (αstrike) angles
when at footstrike during the submaximal running (12 km·h-1) trial in aerial and terrestrial running groups.
Groups
tc (s)
tv (s)
f (step·s-1)
Δz (m)
ΔL (m)
Fmax (kN)
kvert (kN·m-1)
kleg (kN·m-1)
αknee (°)
αankle (°)
αstrike (°)
Aerial
0.268 ± 0.020
0.092 ± 0.021
2.79 ± 0.18
0.062 ± 0.009
0.131 ± 0.015
1.49 ± 0.25
24.2 ± 2.7
11.5 ± 2.3
168 ± 4
117 ± 10
9.8 ± 9.2
Terrestrial
0.287 ± 0.022
0.069 ± 0.022
2.83 ± 0.14
0.058 ± 0.007
0.139 ± 0.013
1.36 ± 0.21
23.6 ± 3.5
9.8 ± 1.6
167 ± 4
111 ± 5
16.9 ± 6.4
p values
<0.001
<0.001
0.161
0.013
0.016
0.011
0.275
<0.001
0.236
0.002
<0.001
Note – Values are mean ± SD. Level of significance is P < 0.05.

“Different Running Patterns Along The Aerial-Terrestrial Continuum Can Result in Similar Running Economy”
by Thibault L et al.
International Journal of Sports Physiology and Performance
© 2016 Human Kinetics, Inc.
Table 2: Root mean square activation amplitude (% of peak) during four sub-phases of the running cycle for the rectus femoris (RF-
RMS), semitendinosus (ST-RMS), tibialis anterior (TA-RMS), and gastrocnemius lateralis (RF-RMS) muscles, as well as co-activation
indexes for the rectus femoris and semitendinosus (RF/ST-CO) and for the tibialis anterior and gastrocnemius lateralis (TA/GL-CO) in
the aerial and terrestrial running pattern groups.
First 50% of the contact phase
Second 50% of the contact phase
First 50% of the swing phase
Second 50% of the swing phase
Aerial
Terrestrial
Aerial
Terrestrial
Aerial
Terrestrial
Aerial
Terrestrial
RF-RMS (%)
45.4 ± 15.6
47.3 ± 12.0
59.2 ± 12.8
56.3 ± 12.7
38.9 ± 13.8
40.2 ± 13.3
15.8 ± 9.2
17.4 ± 9.7
ST-RMS (%)
64.2 ± 10.7
68.2 ± 12.2
*
52.3 ± 18.3
50.3 ± 23.9
29.5 ± 22.4
33.1 ± 30.7
59.9 ± 13.7
65.3 ± 13.2
*
TA-RMS (%)
72.0 ± 9.2
72.0 ± 6.1
46.4 ± 17.4
38.9 ± 19.4
34.4 ± 10.8
37.2 ± 10.4
46.7 ± 14.6
46.5 ± 13.4
GL-RMS (%)
46.7 ± 12.7
41.8 ± 11.7
*
76.9 ± 4.5
76.3 ± 3.9
13.2 ± 6.4
14.8 ± 8.7
10.3 ± 8.3
8.4 ± 5.1
RF/ST-CO (%)
61.9 ± 13.0
55.1 ± 8.2
*
69.0 ± 11.6
59.5 ± 15.6
*
47.6 ± 14.5
41.4 ± 15.9
40.2 ± 15.5
40.9 ± 10.6
TA/GL-CO (%)
62.2 ± 11.5
58.4 ± 12.3
67.2 ± 16.3
59.8 ± 17.6
43.2 ± 13.5
43.0 ± 14.7
33.0 ± 16.4
31.2 ± 16.7
Note – Values are mean ± SD. Level of significance is P < 0.05. The asterisks (*) indicate a significant difference between aerial and
terrestrial patterns.