RESEARCH ARTICLE
Pilates training improves 5-km run
performance by changing metabolic cost and
muscle activity in trained runners
Paula Finatto, Edson Soares Da Silva, Alexandre B. Okamura, Bruna P. Almada, Henrique
B. Oliveira, Leonardo A. Peyre´-Tartaruga*
Exercise Research Laboratory, Escola de Educac¸ão Fı´sica, Fisioterapia e Danc¸a, Universidade Federal do
Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
* leonardo.tartaruga@ufrgs.br
Abstract
Purpose
Strength training improves distance running economy and performance. This finding is
based predominantly on maximal and explosive strength programmes applied to locomotor
muscles, particularly on the lower limbs. It is not certain whether a minimization of metabolic
cost (Cmet) and an improvement in running performance is feasible with strength training of
the postural and trunk muscles.
Methods
Using kinematic, neuromuscular and metabolic measurements of running at two different
speeds before and after a 12-week Pilates training programme, we tested the hypothesis
that core training might improve the running Cmet and performance of trained runners.
Thirty-two individuals were randomly assigned to the control group (CG, n = 16) or the Pila-
tes group (PG, n = 16).
Results
Confirming our hypothesis, a significant improvement (p<0.05) was observed for running
performance in the PG (pre: 25.65±0.4 min; post: 23.23±0.4 min) compared to the CG (pre:
25.33±0.58 min; post: 24.61±0.52 min). Similarly, the PG (4.33±0.07 J.kg-1.m-1) had better
responses than the CG (4.71±0.11 J.kg-1.m-1) during post-training for Cmet. These findings
were accompanied by decreased electromyographic activity of the postural muscles at sub-
maximal running intensities in the PG.
Conclusions
Overall, these results provide a rationale for selecting strength training strategies that target
adaptations on specific postural and locomotor muscles for trained distance runners.
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
1 / 19
a1111111111
a1111111111
a1111111111
a1111111111
a1111111111
OPEN ACCESS
Citation: Finatto P, Silva ESD, Okamura AB,
Almada BP, Oliveira HB, Peyre´-Tartaruga LA (2018)
Pilates training improves 5-km run performance by
changing metabolic cost and muscle activity in
trained runners. PLoS ONE 13(3): e0194057.
https://doi.org/10.1371/journal.pone.0194057
Editor: Yury P. Ivanenko, Fondazione Santa Lucia
Istituto di Ricovero e Cura a Carattere Scientifico,
ITALY
Received: November 28, 2017
Accepted: February 25, 2018
Published: March 21, 2018
Copyright: © 2018 Finatto et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: This work was supported by
Coordenac¸ão de Aperfeic¸oamento de Pessoal de
Nı´vel Superior (CAPES) and Conselho Nacional de
Desenvolvimento Cientı´fico e Tecnolo´gico (CNPq).
The funders had no role in study design, data
collection and analysis, decision to publish, or
preparation of the manuscript.
Introduction
From the cardiorespiratory perspective, running performance, particularly at long distances,
depends on the interaction of different factors [1], including high maximum oxygen consump-
tion (VO2max), the ability to sustain a high fraction of VO2max for long periods, and the ability
to move economically [2]. The latter parameter is designated as metabolic cost (Cmet) and cor-
responds to the oxygen consumption spent to move a certain distance by running at a submax-
imal intensity. Considering a group of runners with a similar body mass, an individual with a
low Cmet would spend less energy and consequently would have lower oxygen consumption
(VO2) than a runner with a high Cmet at a certain running speed [3,4].
A lower Cmet may be achieved via aerobic endurance training programmes, aerobic endur-
ance combined with strength training, and plyometric training [5,6]. Another aspect that may
be related to Cmet is muscle activation, particularly that of muscles of the trunk and lower limbs.
Behm et al.[7] observed that a greater activation of the obliquus externus abdominis muscle and
erector muscles of the upper and sacral spine is required during running for the control of
movements and that the activation pattern of these muscles may be associated with better per-
formance. For this reason, a specific training programme can promote greater stability, which
would decrease necessary muscle recruitment and consequently positively affect Cmet [8,9].
Pilates training (PT) has been widely used to strengthen trunk muscles. PT is based on six
key principles: concentration, control, precision, flow, breathing, and centre of force [10]. The
centre of force was originally designated powerhouse and refers to the extensor muscles of the
spine and hip, the flexor muscles of the spine and hip, and the muscles of the pelvic floor [10].
The centre of force is strengthened to promote further stabilization of the hip and trunk and
favour the integrity of the spine [11].
To the best of our knowledge, no previous studies have specifically addressed the effects of
PT on running. However, training programmes for the stability of the core muscles, which
correspond to the flexor and extensor muscles of the trunk, along with the deeper muscles that
stabilize the trunk, have shown conflicting results when performed for six weeks. Stanton et al.
[12] found significant improvements in core stability in team sport athletes after core training
using Swiss balls; however, they found no significant differences in the activation of abdominal
and extensor muscles of the spine, VO2max or Cmet. By contrast, Sato and Mokha [9] found no
significant improvement in the dynamic stability of trained runners after a core-training pro-
gramme but found a significant decrease in the time of completion for a 5-km run.
Core training and PT aim to strengthen the muscles of the trunk and lower limbs. However, the
principles inherent to PT are not used in core training, and these principles distinguish these two
training modalities and can influence the results of PT. Specific training programmes can result in
a better pattern of activation of the trunk muscles, which would provide more stable joints and
reduce the need for co-contractions for stabilization. Consequently, these programmes could lead to
decreased Cmet and, in turn, improved running performance. We hypothesized that metabolic cost
and trunk muscle activation will be reduced and, consequently, running performance may be
improved. Therefore, it is essential to study the effects of strengthening the muscles of the centre of
force by PT on Cmet and on the muscle activation patterns and biomechanical parameters that could
be indicative of improved Cmet because this strategy can consequently increase running performance.
Materials and methods
Experimental design
To investigate the effects of mat PT in recreational runners, cardiorespiratory and neuromus-
cular adaptations were compared between a group that underwent running training combined
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
2 / 19
Competing interests: The authors have declared
that no competing interests exist.
Abbreviations: Anova, Analysis of variance; BF,
biceps femoralis; Cmet, metabolic cos; Cmet10,
metabolic cost at 10 km.h-1; Cmet12, metabolic cost
at 12 km.h-1; CG, control group; E, Easy; EMG,
Electromyographic; GM, gluteus medius; HRVT2,
heart rate at second ventilatory threshold; LD,
latissimus dors; LO, Longissimus; I, Interval; M,
moderate; MVIC, maximal voluntary isometric
contraction; PG, Pilates group; OI, obliquus
internus abdominis; OE, obliquus externus
abdominis; PT, Pilates training; RMS, root mean
square; SE, Standard error; T, threshold; VL, vastus
lateralis; VO2, oxygen consumption; VO2max,
maximum oxygen consumption; VT2, second
ventilatory threshold; W, Watts.
with PT and a control group that underwent only running training. Both groups (Pilates and
control) were trained for 12 weeks and were evaluated before and after the training period.
The post-training evaluations were performed 72 hours after the last training session, and the
subjects completed the evaluations within 10 days with at least 48 hours between the test ses-
sions. The same assessors who were blinded to the training groups conducted the test sessions,
and the same equipment was used in all of the sessions. The subjects were instructed to main-
tain their eating habits during the study period.
Participants
Fifty-eight subjects were interviewed after placement of an advertisement about the study in a
major newspaper in Porto Alegre, Brazil. The 32 enrolled volunteers were randomly assigned
into two groups by electronic randomization: control group (CG; n = 16) (mean±SE, age:
18.44 ± 0.52 years; body mass: 73.64 ± 10.79 kg; height: 176.66 ± 9.89 cm, percent fat:
10.81 ± 2.49%) and Pilates group (PG; n = 16) (mean ± SE, age: 18.42 ± 0.51 years; body mass:
70.71±10.90 kg; height: 175.07 ± 8.06 cm, percent fat: 9.34±1.98%). During data collection, the
CG lost three subjects. During the training period, one subject from the PG was excluded
because his rate of absence from training was higher than 20%. Therefore, 15 subjects in the
CG and 13 subjects in the PG completed all phases of the study. The inclusion criteria were as
follows: male, practice of running for at least six months before the study, with experience in
5-km running races, age between 18 and 28 years, and absence of medical restrictions. The
exclusion criteria were as follows: subjects with experience in Pilates and subjects with hor-
monal, metabolic, neuromuscular, and/or cardiac disorders. All the participants had a running
experience of at most 9 months prior to the start of the study, with the main frequency of 2
times a week. Each individual signed a free and informed consent form. This study was con-
ducted according to the Helsinki Declaration and was approved by the Ethics Committee of
the Federal University of Rio Grande do Sul, Brazil under registration no. 965734.
Procedures
Running training.
Subjects from the CG and PG participated in a 12-week racetrack
training programme (see the training program in the supplementary material, S1 Table). Two
sessions per week were performed. The periodization of running training was based on the
second ventilatory threshold (VT2) obtained in a maximal effort test on a treadmill with maxi-
mum oxygen consumption (VO2max) in a first session of data collection. Accordingly, the
training periodization was based on the heart rate at VT2 (HRVT2) according to the intensity
zones proposed by Daniels [13]: easy (E), 71–86%; moderate (M), 82–98%; threshold (T), 96–
100%; and interval (I), 107–109% of HRVT2 (S1 Table). The training sessions were held at the
three racetracks of the School of Physical Education of the Federal University of Rio Grande
do Sul (Escola de Educac¸ão Fı´sica, Fisioterapia e Danc¸a da Universidade Federal do Rio
Grande do Sul).
Classical mat Pilates training.
The classic mat PT programme lasted 12 weeks. The sub-
jects from the PG underwent the running training described above in addition to two one-
hour weekly sessions of PT performed on days alternate to the days of the running training.
The organization of the session and the intensity and volume of training were in accordance
with the Manual of the Pilates Method Alliance (California, USA). The sessions were organized
into an initial section (execution of PT fundamentals), a main section (execution of PT exer-
cises), and a final section (relaxation). During the initial section, the fundamentals of PT were
performed, and the exercises were selected according to the training period. Classic mat PT
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
3 / 19
consisted of three series, and the number of repetitions and sequences were defined as shown
in Table 1.
Maximum amplitude of the electromyographic signal during MVIC
In a second session, for the evaluation of the maximum isometric amplitude of the electromyo-
graphic (EMG) signal of the aforementioned muscles, the procedures began with electrode
placement and skin preparation on the muscle surfaces of interest [14]. Surface electrodes with
a 15-mm total diameter (MeditraceTM, Mainsfield, Canada) were used in a bipolar configura-
tion, whose inter-electrode distance of 2 cm [15].
After this procedure, the locations of electrode placement for the longissimus (LO), gluteus
medius (GM), vastus lateralis (VL), biceps femoralis (BF) and latissimus dorsi (LD) were deter-
mined according to the recommendations of the SENIAM project (Surface ElectroMyoGraphy
for the Non-Invasive Assessment of Muscles; [16]). In the obliquus internus abdominis (OI)
muscle, the electrodes were placed two cm medially and inferiorly to the anterior superior iliac
spine [17]. In the obliquus externus abdominis (OE) muscle, the electrodes were placed at
mid-distance between the lower part of the rib cage and the anterior superior iliac spine [17].
The reference electrode was placed at the tuberosity of the tibia of the right leg. A level of resis-
tance between the electrodes of up to 3000 O was accepted. After placement of the electrodes,
the subjects were instructed to perform a warm-up by walking for 5 min on a treadmill. All of
the subjects were instructed and encouraged to exert the maximum force in each isometric test
Table 1. 12-week periodization of Pilates training.
Week 1
Weeks 2 to 6
Weeks 6 to 12
Initial section
Fundamentals 1 to 7
Fundamentals 5 to 12
Fundamentals 13 to 17
Main section
Pre-Pilates
Basic Mat Pilates
Intermediate Mat Pilates
Final section
Relaxation
Relaxation
Relaxation
Exercises that composed the various levels
Fundamentals
Pre-Pilates
Basic Mat Pilates
Intermediate Mat Pilates
1. Breathing
1. The Hundred
1.The Hundred
1. The Hundred
2. Imprinting
2. Roll Down
2. The Roll Up
2. The Roll Up
3. Pelvic Bowl
3. Roll Up
3. Single Leg Circles
3. Leg Circles
4. Knee Sway
4. Single Leg Circles
4. Rolling Like a Ball
4. Rolling Like a Ball
5. Knee Folds/Stirs
5. Rolling Like a Ball
5. Single Leg Stretch
5. Single Leg Stretch
6. Leg Slides
6. Single Leg Stretch
6. Double Leg Stretch
6. Double Leg Stretch
7. Spinal Bridging
7. Double Leg Stretch
7. Legs Up and Down
7. Single Straight Leg
8. Prone Hip Extension
8. Spine Stretch Forward
8. Spine Stretch Forward
8. Double Straight Leg
9. Cervical Nod
9. Saw
9. Criss-Cross
10. Nose Circles
10. Single Leg Kicks
10. Spine Stretch Forward
11. Head Float
11. Beats
11. Open Leg Rocker
12. Ribcage/Angel Arms
12. Double Leg Kicks
12. Corkscrew
13. Rotating Arms
13. Saw
14. Torso Twist
14. Neck Pull
15. Flight
15. Single Leg Kicks
16. Cat
16. Double Leg Kicks
17. Bowing
17. Neck Pull
18. Side Kicks Series
19. Teaser
20. Seal
https://doi.org/10.1371/journal.pone.0194057.t001
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
4 / 19
against the mechanical strength of the Velcro strips to produce this force as fast as possible.
Three measurements of the maximal voluntary isometric contraction (MVIC) were obtained
in each muscle, with a duration of 5 s and an interval of 3 min between each measurement
pre- and post-training and used to normalize the EMG activation during running in each eval-
uation period. To obtain muscle activation, the EMG signal was captured by two electromyo-
graphs (Miotool 400, Miotec, Porto Alegre, Brazil), with a sampling frequency of 2000 Hz in
each channel, using Miograph software (Miotec, Porto Alegre, Brazil) for later analysis in
SAD32 software (UFRGS, Porto Alegre, Brazil). The signal was filtered using a fifth-order But-
terworth band-pass filter with cut-off frequencies between 20 and 500 Hz. After filtering, the
plateau period of isometric activation for 1-s intervals was identified. The root mean square
(RMS) value was obtained via Hamming windowing in 1-s intervals. The measurement with
the highest RMS value was considered valid.
EMG activation during running
Fifteen minutes after the completion of the MVIC measurements, the running protocol was
initiated with two runs at speeds of 10 and 12 km.h-1 performed in random order for 7 minutes
each. The EMG signal was recorded in the last minute of the protocol on a treadmill at each
speed evaluated using the data acquisition software Miograph (Miotec, Porto Alegre, Brazil).
The kinematic data used for evaluation of the EMG signal at the different stride phases were
also obtained in the last minute of each speed evaluated by recording the run with a Casio
(EXLIM-ZR1000) video camera at a sampling rate of 120 Hz. These data were aligned with the
EMG data using a light signal that generates a spike in the EMG signal in the channel specified
for the alignment. Subsequently, the files with data on running and MVICs were exported for
analysis in SAD32 software (UFRGS, Porto Alegre, Brazil). For the analysis of EMG activation
during the runs, the same signal filtering procedure as that used for MVIC was applied. The
RMS curve was obtained via Hamming windowing in 0.1-second intervals. Subsequently, the
RMS signal was shifted and clipped from the signal emitted by the alignment system, in agree-
ment with the video analysis. The times corresponding to the three stride phases (pre-activa-
tion: 100 ms before the contact of the heel with the floor [18]; b) contact phase (contact of the
heel with the ground until detachment of the heel from the ground); and c) swing phase
(detachment of the heel from the ground until contact of the heel to the ground)) were then
identified in the videos for clipping of the EMG signal obtained from five main strides. Subse-
quently, the mean time was calculated from these clippings to obtain the mean RMS value for
each subject and for each stride phase. RMS values representative of EMG activation in each of
the three phases were expressed as a percentage of MVIC. The pattern of EMG activation of
the seven muscles analysed during the runs pre-and post-training in the CG and PG was ana-
lysed via a temporal analysis of the EMG signal in relation to time, considering that the nor-
malized x-axis varied between 0 and 100% of the stride. For this purpose, the raw EMG signal
was shifted according to the alignment system and was rectified and filtered using a fifth-order
Butterworth low band-pass filter with a cut-off frequency of 10 Hz [19]. After filtering, the
EMG signals from five main strides were obtained to calculate the mean curve. The mean
curve of each subject was resampled in 200 points and exported to Excel (Microsoft, Redmond,
USA) for the calculation of the mean curve between the subjects.
Metabolic cost
The treadmill tests at both speeds were performed concurrently with the collection of EMG
data. For this purpose, the subjects remained at rest for 15 min in the sitting position and at
rest for 5 min in the orthostatic position to determine the at rest heart hate and VO2 for
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
5 / 19
confirmation of the initiation of the test. The respiratory exchange ratio should be below 0.85 to
ensure that the individual started from the same resting state in each phase of the test. Subse-
quently, a 5-min warm-up was performed on a treadmill and was immediately followed by two
additional 7-min stages, at running speeds of 10 and 12 km.h-1. These speeds were randomized,
respecting a 5-min interval between the runs or until the heart hate returned to resting levels.
The VO2 values were collected in the last 4 min of each run, and the last 3 min were included in
the analysis. Data were collected using a gas analyser model VO2000 (Medgraphics, Ann Arbor,
USA). The Wmet was considered the difference between the VO2 measured during exercise and
the VO2 at rest, in relation to time. Because the unit of measure used was watts (W), this differ-
ence was multiplied by the energy coefficient (20.9 J.mL-1) and divided by the time in seconds
(60 s). The metabolic cost values relative to the speeds of 10 km.h-1 (Cmet10) and 12 km.h-1
(Cmet12) were calculated by dividing Wmet by the speed in m.s-1.
Time of completion of the 5-km run
In a third session, a 5-km run was performed by all of the subjects in a single test to determine
the total time of completion of the test. The 5-km time was controlled using timers and was con-
firmed by filming. The race was always held at the same time and with similar temperature and
relative humidity conditions. All data can be seen in the supplementary material (S2 Table).
Statistics
The comparisons of run performance variables, metabolic variables, muscle activation, and
sample characteristics between the groups and time factors were performed using the general-
ized estimating equations model. Bonferroni’s complementary test was used to identify signifi-
cant differences. The significance level was set at α<0.05, and the statistical package used was
SPSS version 18.0 (IBM, Armonk, USA).
The sample size computation was based on data (Cmet and performance) from Sato &
Mokha [9] and Stanton et al. [12]. The software used was GPOWER version 3.1 (Power as
1-beta error probability: 95%; Effect size: 0.90; Error assumed as alpha: 0.05). After calculation,
26 subjects were indicated for allocation equally for each group, 13 subjects in CG group and
13 in PG group. We decided insert more subjects in each group, due to a possible sample loss.
Therefore, the present study was initiated with 32 individuals.
Results
Participant baseline characteristics
The sample characterization data are shown in Table 2. No significant differences in this sec-
tion were observed between the groups in the pre-training period.
Table 2. Mean (standard deviation) age, height, body mass, body fat, lean mass, maximal oxygenuptake (VO2max),
and speed at the second ventilatory threshold (VT2) in the pre-training period.
Variable
Group
Control group (n = 16)
Pilates group (n = 15)
p-value
Age (years)
18.44 (0.52)
18.42 (0.51)
0.996
Height (cm)
176.66 (9.89)
175.07 (8.06)
0.404
Body mass (kg)
73.64 (10.79)
70.71 (10.90)
0.391
Body fat (%)
10.81 (2.49)
9.34 (1.98)
0.205
Lean mass (%)
49.82 (2.26)
50.54 (2.40)
0.583
Speed at VT2 (km.h-1)
14.44 (1.33)
14.21 (1.05)
0.837
VO2max (mL.kg-1.min-1)
51.26 (5.43)
51.75 (7.55)
0.926
https://doi.org/10.1371/journal.pone.0194057.t002
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
6 / 19
Running performance and respiratory variables
The variables running time, VO2max, Cmet10, and Cmet12 were not significantly different
between the groups in the pre-training period. In the post-training period, the PG had signifi-
cantly higher VO2max values (p<0.001), a significantly shorter 5-km running time (p<0.001),
and a significantly lower Cmet12 (p = 0.019).
For the time factor, significant differences were found in both groups for all of the variables
evaluated (Table 3).
Electromyographic variables
Maximal voluntary isometric contraction.
The comparisons between the training peri-
ods indicated that the MVIC of the OE, OI, LO, BF, and GM muscles increased significantly in
only the PG whereas the activation of the VL muscle increased significantly in both the CG
and PG between pre- and post-training (Table 4). In addition, no significant differences in
MVIC were found between the CG and PG in pre-training. In post-training, the MVIC of the
OE, OI, LO, and GM muscles was significantly higher in the PG than in the CG.
Muscle activity during running.
The data on muscle activation during the stride phases,
presented as a percentage of the MVIC, indicated a distinct behaviour in relation to the
remaining variables analysed. In the pre-training period, significant differences in the level of
activation of the OE and BF muscles were found in the swing phase at 10 km.h-1 (p = 0.018
and 0.048, respectively) and for the VL (p = 0.024) and BF (p = 0.26) muscles at 10 km.h-1 in
the pre-activation phase.
Obliquus externus abdominis.
A significant increase in the level of activation of the OE
muscle was found in the pre-activation phase between the training periods at 10 km.h-1
(p = 0.022) (Fig 1). However, no differences in the level of activation of this muscle were found
between groups (p = 0.983). In addition, at 10 km.h-1, the percentage of muscle activation
between the training periods decreased only in the swing phase in both groups (p = 0.002).
The percentage of muscle activation significantly decreased in both groups in the support
(p<0.001) and swing (p<0.001) phases at 12 km.h-1. Moreover, in the swing phase post-train-
ing, the level of activation was lower in the PG compared to the CG (p = 0.009).
Obliquus internus abdominis.
At 10 km.h-1, the level of activation of the OI muscle
increased significantly in the pre-activation stage between pre- and post-training in both
Table 3. Effect of running training and running training combined with Pilates on performance and respiratory variables. Data Represent the Mean Values (Stan-
dard Error) for 5-km Running Time, Maximum Oxygen Consumption (VO2max), Metabolic Cost at 10 km.h-1 (Cmet10), Metabolic Cost at 12 km.h-1 (Cmet12), Speed at the
Second Ventilatory Threshold (VT2), and Oxygen Consumption at the Second Ventilatory Threshold (VO2 VT2).
Variable
Group
Period
Effect of time
Effect of group
Interaction group x time
Pre-training
Post-training
p-value
p-value
p-value
5-km running time
CG
25.33 (0.58)
24.61 (0.52)
<0.001
0.441
<0.001
(min)
PG
25.65 (0.44)
23.23 (0.40)a
VO2max
CG
51.32 (1.20)
53.72 (1.58)
<0.001
0.204
<0.001
(mL.kg-1.min-1)
PG
51.8 (1.73)
58.53 (1.59)a
Cmet10
CG
4.27 (0.09)
3.85 (0.13)
<0.001
0.868
0.923
(J.kg-1.m-1)
PG
4.26(0.09)
3.82 (0.08)
Cmet12
CG
5.22 (0.08)
4.71 (0.11)
<0.001
0.014
0.019
(J.kg-1.m-1)
PG
5.00 (0.10)
4.33 (0.07)a
Significant difference between pre- and post-training
a significant difference between the groups in post-training
https://doi.org/10.1371/journal.pone.0194057.t003
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
7 / 19
groups (p = 0.009) (Fig 2). At the speed of 12 km.h-1, the level of activation increased only in
the PG in the pre-activation phase between pre- and post-training (p = 0.01); however, the
level of muscle activation in the PG was lower than that in the CG (p = 0.003).
In the support and swing phases, the percentage of muscle activation decreased significantly
between pre- and post-training at both speeds in both groups (p<0.001). At 12 km.h-1 in post-
training, the level of activation in the PG was significantly lower than that in the CG (p = 0.01).
Vastus lateralis.
The results for the VA muscle are shown in Fig 3. In the pre-activation
phase (group factor, p = 0.273; time factor, p = 0.260) and swing phase (group factor,
p = 0.551; time factor, p = 0.565), there were no significant differences in muscle activation in
the conditions analysed. However, in the support phase, there was a significant decrease in the
level of activation between the two training periods in all of the cases analysed (p<0.001). For
the VA muscle in particular, there were no differences between the groups in any stride
phases.
Longissimus.
There were no significant differences in the level of activation of the LO
muscle in the pre-activation phase in the conditions analysed. In the support phase at 10
km.h-1, the level of activation decreased in both groups (p = 0.001) (Fig 4). At 12 km.h-1, the
level of activation decreased only in the PG between pre- and post-training (p = 0.003). Fur-
thermore, in post-training, muscle activation in the PG was significantly lower than that in
the CG (p = 0.002).
In the swing phase at 10 km.h-1, there were no significant differences in the level of activation
of the LO between groups (p = 0.630) or between training periods (p = 0.364). At 12 km.h-1 in
post-training, the level of activation of this muscle in the PG was significantly lower than in pre-
training (p<0.001) and was significantly lower than in the CG (p = 0.005).
Biceps femoris.
In the pre-activation phase at 10 km.h-1, there were no significant differ-
ences in the level of activation of the BF muscle between pre- and post-training (p = 0.498)
Table 4. Effects of running training (CG) and running training combined with Pilates (PG) on maximal voluntary isometric contraction (MVIC) in millivolts (mV)
of the obliquus externus abdominis (OE), obliquus internus abdominis (OI), vastus lateralis (VL), longissimus (LO), biceps femoris (BF), gluteus medius (GM), and
latissimus dorsi (LD) muscles.
Variable
Group
Period
Effect of time
Effect of group
Interaction group x time
Pre-training
Post-training
p-value
p-value
p-value
OE MVIC
CG
233.00 (28.41)
229.36 (41.75)
0.005
0.048
0.047
(mV)
PG
249.87 (22.12)
316.95 (26.70)a
OI MVIC
CG
527.14 (60.5)
510.52 (71.19)
0.03
0.037
0.006
(mV)
PG
550.69 (60.85)
685.48 (73.46)a
VL MVIC
CG
425.53 (26.82)
483.16 (36.73)
0.032
0.193
0.138
(mV)
PG
432.39 (40.79)
561.93 (46.61)
LO MVIC
CG
284.31 (17.51)
285.79 (15.25)
0.012
0.027
0.016
(mV)
PG
299.39 (21.31)
371.22 (21.49)a
BF MVIC
CG
379.40 (29.5)
452.78 (37.11)
<0.001
0.559
0.034
(mV)
PG
370.47 (30.56)
510.20 (27.59)
GM MVIC
CG
471.15 (39.47)
529.03 (53.10)
0.006
0.007
0.040
(mV)
PG
450.12 (33.60)
587.68 (45.61) a
LD MVIC
CG
348.14 (28.00)
376.24 (32.59)
0.502
0.660
0.745
(mV)
PG
376.05 (32.86)
385.81 (47.95)
Significant difference between pre- and post-training
a significant difference between the groups in post-training
https://doi.org/10.1371/journal.pone.0194057.t004
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
8 / 19
(Fig 5). However, in the pre-activation phase at 12 km.h-1, the level of activation of this muscle
decreased significantly in both groups (p<0.001).
In the support phase at 10 km.h-1 (p<0.001) and 12 km.h-1 (p<0.001), the level of activation
of the BF decreased significantly between pre- and post-training regardless of the group evalu-
ated. In the swing phase, the level of activation decreased significantly at the two speeds and in
both groups.
Gluteus medius.
In the pre-activation phase at 10 km.h-1 and 12 km.h-1, no significant
differences in the activation of the GM muscle were observed (group factor, p = 0.841, time
factor, p = 0.083; group factor, p = 0.686, time factor, p = 0.081, respectively). In the support
phase at 10 km.h-1 (p = 0.003) and 12 km.h-1 (p<0.001), the percentage of muscle activation
decreased in both groups and at both speeds between the two training periods. At 12 km.h-1 in
post-training, the percentage of muscle activation in the PG was significantly lower than that
in the CG (p = 0.005). In the swing phase at 10 km.h-1, there were no significant differences in
the percentage of muscle activation considering the time factor (p = 0.968) and group factor
(p = 0.712). However, at 12 km.h-1, the level of activation of this muscle decreased in the CG
Fig 1. Upper panels, mean pattern of activation of the obliquus externus abdominis muscle (mV). Lower panels, mean (± standard error) muscle activation in the
three stride phases, presented as a percentage of the MVIC. Red lines represent 12 km.h-1, and blue lines represent 10 km.h-1. Dotted lines represent the control group
(CG), and solid lines represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-
training; a significant difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g001
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
9 / 19
and PG considering the time factor (p<0.001), and muscle activation in the PG was signifi-
cantly lower than in the CG (p = 0.005) in post-training (Fig 6).
Latissimus dorsi. No significant differences were observed in the level of activation of the
LD muscle in any of the running stride phases evaluated (Fig 7).
Discussion
The results support our hypotheses that distance running performance is enhanced after a
12-weeks Pilates training programme. The improvements in performance are accompanied by
a critical reduction on Cmet and trunk muscle activation. This suggests that distance runners
are able to transfer effective gains from a slow-type core strength training method to the run-
ning movement.
There is great interest in the mechanisms capable of minimizing energy expenditure during
running because these mechanisms play an essential role in the search for strategies to improve
performance. From the mechanical point of view, the "mass-spring” model reflects the
Fig 2. Upper panels, mean activation pattern of the obliquus internus abdominis muscle (mV). Lower panels, mean (± standard error) muscle activation in the three
stride phases, presented as a percentage of the MVIC. Red lines represent 12 km.h-1, and blue lines represent 10 km.h-1. Dotted lines represent the control group (CG),
and solid lines represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-training; a
significant difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g002
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
10 / 19
occurrence of storage and release of elastic energy during running, which helps minimize the
expenditure of metabolic energy [20]. Therefore, changes in this mechanism could affect per-
formance and improve running economy (RE) [4].
Hoff et al.[21] concluded that shorter contact time with the ground is accompanied by a
longer time at a lower level of muscle activation, indicating lower metabolic demand at the
same submaximal speed.
Therefore, lower metabolic demand in the muscles is dependent on a number of factors,
including the activation level of the task. According to a recent model by Miller et al.[22] on
energy minimization during running, the decrease in muscle activity is the primary strategy to
generate greater energy economy during running. This model was built using the speed of 3.76
m.s-1, which is similar to the highest speed evaluated in this study (12 km.h-1) and supports the
results found herein.
In addition to the decrease in Cmet at both speeds in both study groups as a result of the
training applied, we found an overall decrease in the percentage of muscle activation at the
same speed in post-training. Moreover, the PG displayed a significantly greater decrease in
Cmet12 and in the 5-km run performance compared to the CG. This decrease was accompanied
by a higher VO2max and a further decrease in the level of activation of the OE (Δ6.77% in the
Fig 3. Upper panels, mean activation pattern of the vastus lateralis muscle (mV). Lower panels, mean (± standard error) muscle activation in the three stride phases,
presented as a percentage of the MVIC. Red lines represent 12 km.h-1, and blue lines represent 10 km.h-1. Dotted lines represent the control group (CG), and solid lines
represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-training; a significant
difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g003
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
11 / 19
swing phase,), OI (Δ5.84% in the support phase and Δ9.73% in the swing phase), LO (Δ8.00%
in the support phase and Δ16.03% in the swing phase), and GM (Δ9.81% in the support phase
and Δ5.05% in the swing phase) muscles compared to the CG at 12 km.h-1, in accordance with
the model of Miller et al.[22].
Therefore, if better performance in the 5-km run can be determined by a higher VO2max,
the ability to sustain a higher fraction of VO2max, and a better RE, and because the decrease in
the percentage of muscle activation optimizes energy minimization during running [21,22],
our findings suggest the presence of a correlation between a 12-week training programme of
classic PT and the mechanisms capable of minimizing energy during running, thus contribut-
ing to improved performance (Fig 8).
When analysed in isolation, the decreased percentage of muscle activation found during
running in both groups at 10 and 12 km.h-1 can be explained by the so-called "neuromuscular
economy" [23], which is defined as the decrease in the number of motor units recruited when
considering a situation involving a similar submaximal task. This mechanism explains in part
Fig 4. Upper panels, mean activation pattern of the longissimus muscle (mV). Lower panels, mean (± standard error) muscle activation in the three stride phases,
presented as a percentage of the MVIC. Red lines represent 12 km.h-1, and blue lines represent 10 km.h-1. Dotted lines represent the control group (CG), and solid lines
represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-training; a significant
difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g004
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
12 / 19
the results of the present study, in which the same running speeds were analysed in pre- and
post-training.
Besides, the running training performed by the CG decreased the percentage of muscle acti-
vation at both speeds between pre- and post-training, and the decrease in the PG was signifi-
cantly stronger. These results indicate the possible presence of neuromuscular economy,
particularly when analysed together with the results for the MVIC. The maximum amplitude
of the EMG signal in the VAS muscle was significantly higher post-training in both groups.
However, the level of activation of the OA, LO, OI, and GM muscles increased significantly
only in the PG, who underwent special training for these muscles.
The increase in the maximum amplitude of the MVIC along with the higher VO2max found
in post-training may decrease the relative loads, which correspond to the speeds in pre-train-
ing and justify the decreased recruitment of motor units during the performance of the same
task in the post-training period. This hypothesis would explain the findings in the PG, who
showed a stronger decrease in the percentage of muscle activation during running and shorter
5-km run completion time compared to the CG.
Fig 5. Upper panels, mean activation pattern of the biceps femoris muscle (mV). Lower panels, mean (± standard error) muscle activation in the three stride phases,
presented as a percentage of the MVIC. Red lines represent 12 km.h-1, and blue lines represent 10 km.h-1. Dotted lines represent the control group (CG), and solid lines
represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-training; a significant
difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g005
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
13 / 19
The reduction in the time of completion of this run, the improvement in Cmet12, and the
greater decrease in the percentage of EMG activation in the PG during running appear to be
associated with the control and stabilization of the lumbopelvic region. The correlation
between EMG activity and stability is well established in the literature. In fact, findings empiri-
cally show that the neural system responds to changes in spinal stability [24] and gives support
to the adaptive process model on motor learning [25]. The control of the trunk is an important
factor for Cmet, and leg movements are closely associated with lumbopelvic movements; thus,
the latter depend on the stiffness of the abdominal muscles [3,25].
Therefore, the increase in running speed would cause more lumbopelvic movements and
consequently greater instability, which would require greater neuromuscular control to
achieve stability during cyclical movements such as running [8,26]. In turn, this increased neu-
romuscular demand for stabilization of the lumbopelvic region appears to be associated with a
greater contribution of concentric activations—which are more energy-consuming than
eccentric and isometric activations—and reinforces the fact that an unstable system is also less
economical [25,27].
Fig 6. Upper panels, mean activation pattern of the gluteus medius muscle (mV). Lower panels, mean (± standard error) muscle activation in the three phases,
presented as a percentage of the MVIC. Red lines represent 12 km.h-1, whereas blue lines represent 10 km.h-1. Dotted lines represent the control group (CG), and solid
lines represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-training; a significant
difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g006
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
14 / 19
From this perspective, lumbopelvic stabilization is one of the aims of Pilates. Among its
guiding principles, breathing [28] and centring [29] have been shown to stimulate the deep
abdominal muscles responsible for stabilization, including the rectus abdominis muscles, OI,
OE, and transversus abdominis [8]. In this respect, Phrompaet et al.[30] evaluated the effects
of PT in the control of lumbopelvic movements. At the end of eight weeks of training, the
authors found that 65% of the subjects in the Pilates group passed the lumbopelvic stability test
after four weeks of training, and 85% passed the test after eight weeks of training, whereas
none of the subjects in the control group passed the test. The authors indicate that the
improved recruitment of abdominal muscles during PT appears to help develop the strength
of these muscles, leading to improved stability. However, EMG activity was not evaluated in
that study.
Sato and Mokha [9] evaluated a six-week core-training programme and found improve-
ment in a 5-km run completion time. The run completion time decreased significantly in the
experimental group (from 29.29±2.38 to 28.42±2.23 min) but did not decrease in the control
group. In addition, Stanton et al. [12] evaluated participants after six weeks of core training
Fig 7. Upper panel, mean activation pattern of the latissimus dorsi muscle (mV). Lower panel, mean (± standard error) muscle activation in the three stride phases,
presented as a percentage of the MVIC. Red lines represent 12 km.h-1, and blue lines represent 10 km.h-1. Dotted lines represent the control group (CG), and solid lines
represent the Pilates group (PG). The vertical dotted lines indicate the end of the contact phase.  Significant difference between pre- and post-training; a significant
difference between groups (p<0.005).
https://doi.org/10.1371/journal.pone.0194057.g007
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
15 / 19
with a Swiss ball and found a significant improvement in lumbopelvic stability; however, no
differences were found in running economy, VO2max, or in the EMG activity of the trunk
muscles.
By contrast, in the present study, the run completion time decreased from 25.33±0.58 to
24.61±0.52 min in the CG and from 25.65±0.44 to 23.23±0.40 min in the PG. In addition, the
PG had an improvement in VO2max (from 51.8±1.73 mL.kg-1.min-1 in pre-training to 58.53
±1.59 mL.kg-1.min-1 in post-training, p<0.001) and Cmet12 (from 5.0±0.10 J.kg-1.m-1 in pre-
training to 4.33±0.07 J.kg-1.m-1 in post-training, p<0.001) and a decrease in the percentage of
EMG activation of the trunk muscles.
However, despite the conflicting results with the literature with regard to core training, the
present study is distinguished by the duration of the training period. In the cited studies, only
Fig 8. Schematic drawing of the performance model proposed in this study [2,3,20,22].
https://doi.org/10.1371/journal.pone.0194057.g008
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
16 / 19
a six-week training programme was conducted whereas the present study utilized a 12-week
training programme in both groups, and this longer training may have contributed to the
results obtained. Moreover, unlike core training, PT should be performed considering its prin-
ciples, which can help increase muscle activation to higher levels [28,29].
In conclusion, PT significantly improved the 5-km run performance. This improved perfor-
mance is associated with the optimization of mechanisms capable of minimizing energy
expenditure. That is, a lower percentage of EMG activation of the trunk muscles during run-
ning as a result of strength gain. Therefore, the greater running economy seems to be positively
influenced the 5-km run performance in recreational runners.
Conclusions
The results of this study indicate that PT can be incorporated into the training programmes of
recreational runners to improve running performance and VO2max and to strengthen trunk
muscles. In addition, in situations in which the development of aerobic power is limited by
cardiac or pulmonary capacity, PT may improve performance at a lower metabolic cost by
decreasing muscle demand during unnecessary pelvic movements and improve other health-
related aspects, including a lower risk of injury. However, little is known about the effects of
PT on mechanisms that minimize energy expenditure, mechanical parameters, and their cor-
relation with running performance. Therefore, further studies are necessary to elucidate these
relationships.
Supporting information
S1 Table. 12-week periodization of running training using the following intensity scores:
E, Easy; M, Moderate; T, Threshold; and I, Interval, as a function of the heart rate at VT2.
(DOCX)
S2 Table. General dataset.
(XLSX)
Acknowledgments
Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nı´vel Superior (CAPES) and Conselho Nacio-
nal de Desenvolvimento Cientı´fico e Tecnolo´gico (CNPq). The funders had no role in study
design, data collection and analysis, decision to publish, or preparation of the manuscript. We
are grateful to the Locomotion Group of the Federal University of Rio Grande do Sul for dis-
cussions and comments. L.A. Peyre´-Tartaruga is an established investigator of the Brazilian
Research Council (CNPq), Brası´lia, Brazil.
Author Contributions
Conceptualization: Paula Finatto, Leonardo A. Peyre´-Tartaruga.
Data curation: Paula Finatto, Edson Soares Da Silva, Alexandre B. Okamura, Bruna P.
Almada, Henrique B. Oliveira, Leonardo A. Peyre´-Tartaruga.
Formal analysis: Paula Finatto, Edson Soares Da Silva, Alexandre B. Okamura, Bruna P.
Almada, Henrique B. Oliveira, Leonardo A. Peyre´-Tartaruga.
Funding acquisition: Leonardo A. Peyre´-Tartaruga.
Investigation: Paula Finatto, Edson Soares Da Silva, Alexandre B. Okamura, Bruna P. Almada,
Henrique B. Oliveira, Leonardo A. Peyre´-Tartaruga.
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
17 / 19
Methodology: Paula Finatto, Edson Soares Da Silva, Alexandre B. Okamura, Bruna P. Almada,
Henrique B. Oliveira, Leonardo A. Peyre´-Tartaruga.
Project administration: Leonardo A. Peyre´-Tartaruga.
Resources: Paula Finatto, Leonardo A. Peyre´-Tartaruga.
Software: Paula Finatto, Edson Soares Da Silva, Henrique B. Oliveira, Leonardo A. Peyre´-
Tartaruga.
Supervision: Leonardo A. Peyre´-Tartaruga.
Visualization: Paula Finatto, Alexandre B. Okamura, Leonardo A. Peyre´-Tartaruga.
Writing – original draft: Paula Finatto.
Writing – review & editing: Paula Finatto, Edson Soares Da Silva, Alexandre B. Okamura,
Bruna P. Almada, Henrique B. Oliveira, Leonardo A. Peyre´-Tartaruga.
References
1.
Joyner MJ. Modeling: optimal marathon performance on the basis of physiological factors. J Appl Phy-
siol. 1991; 70: 683–687. https://doi.org/10.1152/jappl.1991.70.2.683 PMID: 2022559
2.
di Prampero PE, Atchou G, Bruckner JC, Moia C. The energetics of endurance running. Eur J Appl Phy-
siol Occup Physiol. 1986; 55: 259–266. PMID: 3732253
3.
Saunders PU, Pyne DB, Telford RD, Hawley JA. Factors affecting running economy in trained distance
runners. Sports Med. 2004; 34: 465–485. PMID: 15233599
4.
Foster C, Lucia A. Running economy: the forgotten factor in elite performance. Sports Med. 2007; 37:
316–319. PMID: 17465597
5.
Millet GP, Jaouen B, Borrani F, Candau R. Effects of concurrent endurance and strength training on
running economy and.VO(2) kinetics. Med Sci Sports Exerc. 2002; 34: 1351–1359. PMID: 12165692
6.
Storen O, Helgerud J, Stoa EM, Hoff J. Maximal strength training improves running economy in distance
runners. Med Sci Sports Exerc. 2008; 40: 1087–1092. https://doi.org/10.1249/MSS.0b013e318168da2f
PMID: 18460997
7.
Behm DG, Cappa D, Power GA. Trunk muscle activation during moderate- and high-intensity running.
Appl Physiol Nutr Metab. 2009; 34: 1008–1016. https://doi.org/10.1139/H09-102 PMID: 20029508
8.
Saunders SW, Schache A, Rath D, Hodges PW. Changes in three dimensional lumbo-pelvic kinematics
and trunk muscle activity with speed and mode of locomotion. Clin Biomech. 2005; 20: 784–793.
9.
Sato K, Mokha M. Does core strength training influence running kinetics, lower-extremity stability, and
5000-M performance in runners? J Strength Cond Res. 2009; 23: 133–140. https://doi.org/10.1519/
JSC.0b013e31818eb0c5 PMID: 19077735
10.
Muscolino JE, Cipriani S. Pilates and the “powerhouse”—I. J Bodyw Mov Ther. 2004; 8: 15–24.
11.
Culligan PJ, Scherer J, Dyer K, Priestley JL, Guingon-White G, Delvecchio D, et al. A randomized clini-
cal trial comparing pelvic floor muscle training to a Pilates exercise program for improving pelvic muscle
strength. Int Urogynecol J. 2010; 21: 401–408. https://doi.org/10.1007/s00192-009-1046-z PMID:
20094704
12.
Stanton R, Reaburn PR, Humphries B. The effect of short-term Swiss ball training on core stability and
running economy. J Strength Cond Res. 2004; 18: 522–528. https://doi.org/10.1519/1533-4287(2004)
18<522:TEOSSB>2.0.CO;2 PMID: 15320664
13.
Daniels J. Daniels’ running formula. Champaign, IL: Human Kinetics; 2005.
14.
De Luca CJ. The use of surface electromyography in biomechanics. J Appl Biomech. 1997; 13: 135–
163.
15.
Beck TW, Housh TJ, Johnson GO, Weir JP, Cramer JT, Coburn JW, et al. The effects of interelectrode
distance on electromyographic amplitude and mean power frequency during isokinetic and isometric
muscle actions of the biceps brachii. J Electromyogr Kinesiol. 2005; 15: 482–495. https://doi.org/10.
1016/j.jelekin.2004.12.001 PMID: 15935960
16.
Hermens HJ, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, et al. European recommendations for
surface electromyography. Roessingh Research and Development. 1999; 8: 13–54.
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
18 / 19
17.
Marques NR, Morcelli MH, Hallal CZ, Gonc¸alves M. EMG activity of trunk stabilizer muscles during cen-
tering principle of Pilates method. J Bodyw Mov Ther. 2013; 17: 185–191. https://doi.org/10.1016/j.jbmt.
2012.06.002 PMID: 23561865
18.
Kyrolainen H, Avela J, Komi PV. Changes in muscle activity with increasing running speed. J Sports
Sci. 2005; 23: 1101–1109. https://doi.org/10.1080/02640410400021575 PMID: 16194986
19.
Cappellini G, Ivanenko YP, Poppele RE, Lacquaniti F. Motor patterns in human walking and running. J
Neurophysiol. 2006; 95: 3426–3437. https://doi.org/10.1152/jn.00081.2006 PMID: 16554517
20.
Saibene F, Minetti AE. Biomechanical and physiological aspects of legged locomotion in humans. Eur J
Appl Physiol. 2003; 88: 297–316. https://doi.org/10.1007/s00421-002-0654-9 PMID: 12527959
21.
Hoff J, Gran A, Helgerud J. Maximal strength training improves aerobic endurance performance. Med
Sci Sports. 2002; 12: 288–295.
22.
Miller RH, Umberger BR, Hamill J, Caldwell GE. Evaluation of the minimum energy hypothesis and
other potential optimality criteria for human running. Proc Biol Sci. 2012; 279: 1498–1505. https://doi.
org/10.1098/rspb.2011.2015 PMID: 22072601
23.
Cadore EL, Pinto RS, Alberton CL, Pinto SS, Lhullier FL, Tartaruga MP, et al. Neuromuscular economy,
strength, and endurance in healthy elderly men. J Strength Cond Res. 2011; 25: 997–1003. https://doi.
org/10.1519/JSC.0b013e3181d650ba PMID: 20881506
24.
Santos SP, Benda RN, Couto CR, Campos CE, Andrade AGP, Lage GM, et al. The level of perfor-
mance stabilization influences motor adaptation on isometric force control task. PLoS ONE. 2017; 12:
e0185939 https://doi.org/10.1371/journal.pone.0185939 PMID: 29073273
25.
Gardner-Morse MG, Stokes IA. The effects of abdominal muscle coactivation on lumbar spine stability.
Spine. 1998; 23: 86–91; discussion 91–82. PMID: 9460158
26.
England SA, Granata KP. The influence of gait speed on local dynamic stability of. Gait Posture. 2007;
25: 172–178. https://doi.org/10.1016/j.gaitpost.2006.03.003 PMID: 16621565
27.
Granata KP, Orishimo KF. Response of trunk muscle coactivation to changes in spinal stability. J Bio-
mech. 2001; 34: 1117–1123. PMID: 11506782
28.
Barbosa AWC, Guedes CA, Bonifa´cio DN, de Fa´tima Silva A, Martins FLM, Barbosa MCSA. The Pilates
breathing technique increases the electromyographic amplitude level of the deep abdominal muscles in
untrained people. J Bodyw Mov Ther. 2015; 19: 57–61. https://doi.org/10.1016/j.jbmt.2014.05.011
PMID: 25603743
29.
Barbosa AW, Martins FL, Vitorino DF, Barbosa MC. Immediate electromyographic changes of the
biceps brachii and upper rectus abdominis muscles due to the Pilates centring technique. J Bodyw Mov
Ther. 2013; 17: 385–390. https://doi.org/10.1016/j.jbmt.2013.01.003 PMID: 23768286
30.
Phrompaet S, Paungmali A, Pirunsan U, Sitilertpisan P. Effects of Pilates training on lumbo-pelvic sta-
bility and flexibility. Asian J Sports Med. 2011; 2: 16–22. PMID: 22375213
Pilates training improves 5-km run performance
PLOS ONE | https://doi.org/10.1371/journal.pone.0194057
March 21, 2018
19 / 19

Pilates training improves 5-km run performance by changing metabolic cost and muscle activity in trained runners.
Finatto, Paula,Silva, Edson Soares Da,Okamura, Alexandre B,Almada, Bruna P,Storniolo, Jorge L L,Oliveira, Henrique B,Peyré-Tartaruga, Leonardo A