![| Peak (A) and nadir (B) values of normalized deoxyhemoglobin concentration ([HHb]) over 11 sprint/recovery cycles with normal breathing (CTL) and voluntary hypoventilation at low lung volume (VHL) before and after 4 weeks of training. Data are presented as means ± SD, expressed as a percent of the first sprint/recovery cycle. **Moderate effect between groups; † Large effect between groups.](https://www.researchgate.net/profile/Francois-Billaut/publication/340407118/figure/fig3/AS:877680102735873@1586266651855/Peak-A-and-nadir-B-values-of-normalized-deoxyhemoglobin-concentration-HHb-over_Q320.jpg)
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ORIGINAL RESEARCH
published: 03 April 2020
doi: 10.3389/fspor.2020.00029
Frontiers in Sports and Active Living | www.frontiersin.org 1April 2020 | Volume 2 | Article 29
Edited by:
Paul S. R. Goods,
Western Australian Institute of
Sport, Australia
Reviewed by:
Nobukazu Kasai,
Japan Institute of Sports Sciences
(JISS), Japan
Julien Louis,
Liverpool John Moores University,
United Kingdom
*Correspondence:
François Billaut
francois.billaut@kin.ulaval.ca
Specialty section:
This article was submitted to
Elite Sports and Performance
Enhancement,
a section of the journal
Frontiers in Sports and Active Living
Received: 29 January 2020
Accepted: 11 March 2020
Published: 03 April 2020
Citation:
Lapointe J, Paradis-Deschênes P,
Woorons X, Lemaître F and Billaut F
(2020) Impact of Hypoventilation
Training on Muscle Oxygenation,
Myoelectrical Changes, Systemic
[K+], and Repeated-Sprint Ability in
Basketball Players.
Front. Sports Act. Living 2:29.
doi: 10.3389/fspor.2020.00029
Impact of Hypoventilation Training on
Muscle Oxygenation, Myoelectrical
Changes, Systemic [K+], and
Repeated-Sprint Ability in Basketball
Players
Julien Lapointe 1, Pénélope Paradis-Deschênes 1, Xavier Woorons 2, Fréderic Lemaître 3
and François Billaut 1
*
1Département de Kinésiologie, Université Laval, Quebec City, QC, Canada, 2University of Lille, University of Artois, University
of Littoral Côte d’Opale, ULR 7369 - URePSSS - Unité de Recherche Pluridisciplinaire Sport Santé Société, Lille, France,
3Faculté des Sciences du Sport, Université de Rouen, Rouen, France
This study investigated the impact of repeated-sprint (RS) training with voluntary
hypoventilation at low lung volume (VHL) on RS ability (RSA) and on performance in
a 30-15 intermittent fitness test (30-15IFT). Over 4 weeks, 17 basketball players included
eight sessions of straight-line running RS and RS with changes of direction into their
usual training, performed either with normal breathing (CTL, n=8) or with VHL (n
=9). Before and after the training, athletes completed a RSA test (12 ×30-m, 25-s
rest) and a 30-15IFT. During the RSA test, the fastest sprint (RSAbest), time-based
percentage decrement score (RSASdec), total electromyographic intensity (RMS), and
spectrum frequency (MPF) of the biceps femoris and gastrocnemius muscles, and biceps
femoris NIRS-derived oxygenation were assessed for every sprint. A capillary blood
sample was also taken after the last sprint to analyse metabolic and ionic markers.
Cohen’s effect sizes (ES) were used to compare group differences. Compared with
CTL, VHL did not clearly modify RSAbest, but likely lowered RSASdec (VHL: −24.5%
vs. CTL: −5.9%, group difference: −19.8%, ES −0.44). VHL also lowered the maximal
deoxygenation induced by sprints ([HHb]max; group difference: −2.9%, ES −0.72) and
enhanced the reoxygenation during recovery periods ([HHb]min; group difference: −3.6%,
ES −1.00). VHL increased RMS (group difference: 18.2%, ES 1.28) and maintained MPF
toward higher frequencies (group difference: 9.8 ±5.0%, ES 1.40). These changes were
concomitant with a lower potassium (K+) concentration (group difference: −17.5%, ES
−0.67), and the lowering in [K+] was largely correlated with RSASdec post-training in VHL
only (r=0.66, p<0.05). However, VHL did not clearly alter PO2, hemoglobin, lactate
and bicarbonate concentration and base excess. There was no difference between group
velocity gains for the 30-15IFT (CTL: 6.9% vs. VHL: 7.5%, ES 0.07). These results indicate
that RS training combined with VHL may improve RSA, which could be relevant to
basketball player success. This gain may be attributed to greater muscle reoxygenation,
enhanced muscle recruitment strategies, and improved K+regulation to attenuate the
development of muscle fatigue, especially in type-II muscle fibers.
Keywords: repeated-sprint ability,breath-hold, hypoxia, hypoventilation, muscle oxygenation, muscle recruitment,
potassium
Lapointe et al. Breath-Hold Training During Sprints
INTRODUCTION
As in most team sports, basketball players have to perform
various efforts including sprinting, jumping, and shuffling
interspersed with relatively short and active periods of recovery
(i.e., running and walking). To enhance fitness and delay
neuromuscular fatigue, conditioning programs revolve around
the determinants of repeated-sprint (RS) ability (RSA). These
include energetic substrate depletion, metabolite accumulation,
ionic and muscle excitability changes, and altered muscle
recruitment strategies (Billaut and Bishop, 2009; Girard et al.,
2011). In this never-ending quest for training optimization,
the use of extreme environments has become very popular to
increase the stress placed on athletes. Performing RS training
in hypoxia (the so-called RSH modality) can enhance some
peripheral limiting factors of RSA and improve the ability to
repeat all-out efforts (i.e., sprint endurance) more than the same
training performed in normoxia (Billaut et al., 2012; Brocherie
et al., 2017). Among these purported factors, the enhancement of
oxygen delivery to and oxygenation of active skeletal muscles and
fast-twitch fibers recruitment have been demonstrated on several
occasions and in various sport modalities (Faiss et al., 2013).
However, attending a training camp at terrestrial altitude
and/or using hypoxic generators require specific logistic and
equipment which can be prohibitive. Exercising while voluntarily
holding one’s breath at low lung volume elicits levels of arterial
blood O2saturation (SpO2) similar to those observed during
typical hypoxic conditioning programs simulating altitudes from
1,500 to 3,000 m (i.e., SpO278–92%). Mean SpO2has been shown
to drop down to ∼88% in young healthy adults holding their
breath at functional residual capacity during moderate intensity
cycling efforts (Yamamoto et al., 1987). When applied to RS
exercises, voluntary hypoventilation at low lung volume (VHL)
has also been reported to decrease SpO2(∼87%) and to lead to
greater muscle deoxygenation and blood lactate accumulation
when compared to the same exercise protocol with normal
breathing (Woorons et al., 2017).
VHL has recently been applied to RS training, and data
demonstrate promising improvements in RSA in running
(Fornasier-Santos et al., 2018), swimming (Trincat et al., 2017),
and cycling (Woorons et al., 2019b) after only 2–4 weeks of
training. However, these studies were limited in elucidating the
physiological mechanisms involved in the performance gains.
So far, blood lactate concentration ([Lac−]) has been shown to
increase after VHL training at all-out intensity (Trincat et al.,
2017; Woorons et al., 2019b). This adaptation is in line with the
observation of greater acute [Lac−] after a single RS protocol
and typically reflects a higher contribution from the anaerobic
glycolysis pathway (Woorons et al., 2017). A greater systemic
O2consumption has also been observed and ascribed to an
increase in stroke volume subsequent to ventricular diastolic
filling in response to the large and abrupt inspiration taken
immediately at the end of a breath-hold (Woorons et al., 2019b).
However, other important limiting factors of RSA have not yet
been fully explored. For example, enhanced blood flow to and
reoxygenation of skeletal muscles, improved muscle recruitment
strategies and reduced perturbations in muscle transmembrane
sodium (Na+) and potassium ions (K+) concentration gradients,
which are known to be readily affected by training in hypoxia,
could each contribute to improving RSA. Furthermore, team-
sport athletes often perform sprints with changes of direction
(COD) in their training. While VHL has been successfully
implemented during acute exercise with COD (Woorons et al.,
2019a), the eccentric phase induced by repeated COD over weeks
of training may increase muscle damages and/or neuromuscular
fatigue (Chaabene et al., 2018). This approach therefore needs
to be tested before recommending implementation within
daily practice.
Therefore, the aim of this study was to examine additional
mechanisms underlying the enhancement of sprint performance
after VHL training. We also aimed to examine whether this
approach could be feasible at all-out intensity with COD,
as performed regularly in team sports. Based on the impact
of RSH training on physiological responses, we hypothesized
that VHL training would improve blood volume and muscle
reoxygenation, enhance acid-base balance and K+regulation,
and maintain muscle recruitment.
MATERIALS AND METHODS
Participants
Seventeen athletes (5 women and 12 men) were recruited from
the Laval University basketball club (mean ±SD; age, 22.3 ±
1.2; height, 185.5 ±11.7 cm; weight, 88.6 ±16.9 kg). Players
competed at national level, and training volume at the time
of the study was 8 sessions per week for an average of ∼13 h.
All participants were healthy, non-smokers, did not use any
medication, and were asked to avoid vigorous exercise, alcohol
and caffeine 24 h before every test and to maintain their regular
diet throughout the study. The study was approved by the
ethics committee of Laval University, and the experiment was
conducted in accordance with the principles established in the
Declaration of Helsinki.
Experimental Design
The study took place during the preparation phase to competition
in May and was integrated within the annual strength
and conditioning planning to limit methodological invalidity.
The experimental protocol consisted of two testing sessions
performed before (Pre-) and after (Post-) a 4-week RS-specific
training (i.e., 8 training sessions). The testing session at Post-
was conducted 3–4 days after the last training session. The two
testing sessions consisted of a running RSA and a 30-15IFT tests
separated by 2 days without intensive training. Before initial
testing, participants visited the laboratory for two familiarization
sessions. In the first session, resting heart rate, blood pressure,
height and weight were recorded. Then, participants were
familiarized with the VHL technique for about 30 min. This
technique has been fully described by Woorons et al. (2017).
Briefly, it consists of breath-holding episodes at low lung volume
performed during brief repeated maximal sprints. Immediately
before every sprint, participants were asked to exhale down
to functional residual capacity and to hold their breath while
running as fast as they could for the duration of the sprint
Frontiers in Sports and Active Living | www.frontiersin.org 2April 2020 | Volume 2 | Article 29
Lapointe et al. Breath-Hold Training During Sprints
(6-s). Right after the sprint, a second exhalation was performed
in order to evacuate the carbon dioxide accumulated in lungs.
The experimenters observed the breathing patterns and gave
constant feedback on the technique. In addition, they questioned
the participants on the difficulty of applying the technique during
sprints. When subjects were able to complete a 6-s sprint at
maximum velocity while properly performing the breathing
technique, familiarization was considered complete. The same
familiarization protocol was undertaken with the COD. In the
second session participants were familiarized with the 30-15IFT
test and again with the VHL technique. After the first testing
session (Pre-), participants were matched into pairs based on
their performances during the RS (score decrement) and 30-
15IFT tests (total distance), and then randomly assigned to a
group that performed the RS training with normal breathing
(CTL, n=8) or with the VHL technique (VHL, n=9).
Repeated-Sprint Training
Athletes had to complete 8 RS training sessions over 4 weeks,
with at least 2 days between sessions. Every training session was
preceded by a standardized warm-up including active mobility,
dynamic stretches, various activation exercises for the posterior
chain and ankle, and ended with two 20-m sprints. The first
session of the week always included COD and was conducted
on an indoor basketball field. Participants started in the middle
of the basketball court facing the baseline, and after a count-
down they had to touch one sideline after the other and finish
where they started (Figure 1). At each repetition, the start was
in the other direction. The second session of the week was
conducted outdoors on an American football field and did not
include COD. In both training protocols, participants had to
sprint for 6 s and then had 24 s of semi-active recovery (i.e.,
walking to the started line). For the COD protocol, participants
were asked to perform the maximum of the running pattern
in 6 s. During the linear running protocol, participants had to
run the maximal distance in 6 s. This work-to-rest ratio has
been documented in previous studies (Woorons et al., 2017).
Participants performed 3 sets of 6 sprints in the first and last
week and 3 sets of 8 sprints in the second and third week.
Each set was separated by a 3-min semi-active recovery. We
chose to increase the training volume in the second and third
weeks of training in order to have a greater training load. On
the other hand, the training volume was reduced in the last
week to avoid, or at least limit, fatigue in the perspective of
the Post-testing session, as usually performed in sport settings.
Both groups performed the same training sessions, but the CTL
kept a normal breathing pattern. Every session was supervised
to ensure that the VHL technique was correctly applied. SpO2
was randomly assessed in both groups throughout the training
sessions with a finger pulse oximeter (Nonin Oxywatch, accuracy
at 70–100%: ∼2%).
Repeated-Sprint Ability Test
The RSA pre- and post-tests were performed on an indoor
American football field. The protocol consisted of 12 ×30 m
straight-line running sprints interspersed with 20 s of active
recovery (run back to the start line). Participants were instructed
FIGURE 1 | Layout of repeated sprint exercise with changes of direction
(COD) on a basketball court.
to sprint as fast as possible during every sprint with no
pacing strategy and to breathe normally. Participants assumed
a standardized starting position with the dominant leg in
front and a two-point stance. Strong verbal encouragements
were provided. Before the test, participants performed a
standardized warm-up after which electromyographic (EMG)
and near-infrared spectroscopy (NIRS) probes were installed (see
sections below).
A photodetector (SciencePerfo, Quebec, Canada; 50 Hz) was
used to measure sprint times. As soon as a participant started a
sprint, an integrated algorithm allowed to begin the recording
and prevent false start error. The photodetector recorded
maximal speed, split times and speed at 5, 10, 15, and 30 m.
The best sprint time (RSAbest) and the average completion time
of the 12 sprints (RSAmean) were computed, and time-based
percent decrement score (RSASdec) was calculated as follows:
[(total sprint time/ideal sprint time ×number of sprint) −1] ×
100 where number of sprints was 12 (Glaister et al., 2008).
The rating of perceived exertion (RPE) score was recorded
directly after the last sprint using the Borg 10-point scale to assess
subjective perceived exertion. A blood sample was taken 1-min
post for subsequent analysis.
30-15 Intermittent Fitness Test
This maximal aerobic test consisted of 30-s shuttle runs
interspersed with 15 s of semi-active recovery. The first stage
was set at 8 km·h−1and speed increased by 0.5 km·h−1at
every stage completed until volitional exhaustion. Tests were
conducted indoor on a basketball court and participants had to
shuttle run between two baselines (28 m apart). The running pace
was governed by a soundtrack and participants were strongly
encouraged. The test ended when a participant was not able
to keep running at the imposed pace. The velocity of the last
completed stage was retained as the participant VIFT. This test is
used extensively to assess the aerobic fitness of team-sport players
(Buchheit et al., 2009). The RPE score was recorded right after the
last stage.
Frontiers in Sports and Active Living | www.frontiersin.org 3April 2020 | Volume 2 | Article 29
Lapointe et al. Breath-Hold Training During Sprints
Near-Infrared Spectroscopy
Measurements
Muscle blood volume and oxygenation were assessed
continuously during the RSA test using a spatially-resolved
portable NIRS apparatus (PortaMon, Artinis Medical System
BV, Netherlands). The NIRS device was installed on the
gastrocnemius lateralis muscle belly (1/4 of the line between
the head of fibula and the heel), parallel to muscle fiber
direction to quantify changes in absorption of near-infrared
light by oxyhemoglobin (HbO2) and deoxyhemoglobin (HHb).
The device was enclosed in a transparent plastic bag to
protect it from sweat, fixed with tape and covered by a black
bandage to avoid interference with background light. The
position was marked with indelible pen for the post-visit. A
modified form of the Beer-Lambert law, using two continuous
wavelengths (760 and 850 nm) and a differential optical
path length factor of 4.95, was used to calculate micromolar
changes in tissue HbO2(1[HbO2]), HHb (1[HHb]), and
total hemoglobin [1[tHb] =[HbO2]+[HHb]; used as an
index of change in regional blood volume (van Beekvelt et al.,
2001)].
The NIRS data were acquired at 10 Hz and then filtered
using a tenth-order Butterworth low-pass filter with a 4 Hz cut-
off frequency. Analysis of muscle O2extraction was limited to
[HHb] because this variable is less sensitive than [HbO2] to
perfusion variations and abrupt blood volume changes during
contraction and recovery (de Blasi et al., 1993; Ferrari et al.,
2004). From the filtered signal, one value for each of the maximal
and minimal [HHb] and [tHb] was manually identified for
every sprint/recovery cycle throughout the RSA test for accurate
detection of oxygenation peaks and nadirs (Faiss et al., 2013;
Rodriguez et al., 2018). All peaks ([HHb]max and [tHb]max),
nadirs ([HHb]min and [tHb]min), and amplitude changes (i.e.,
peak-to-nadir difference: 1[HHb] and 1[tHb]) were then
normalized to the peak, nadir and amplitude recorded during the
first sprint/recovery cycle (Faiss et al., 2013).
Electromyographic Acquisition and
Analysis
During every sprint of the RSA test, the EMG signals of the biceps
femoris (BF) and gastrocnemius lateralis (GAS) were recorded
from the dominant leg with surface electrodes (Delsys, Trigno
Wireless, Boston, MA). Electrode sites were prepared before
every test (hair shaved, skin lightly abraded and cleaned with
alcohol). Electrodes were fixed longitudinally over the muscle
belly according to SENIAM’s recommendations (Hermens et al.,
2000). The position was marked with indelible pen for the post-
visit and participants were asked to maintain the writing visible
on the skin. The EMG signal was pre-amplified and filtered
(bandwidth 12–500 Hz, gain =1,000, sampling frequency 2 kHz)
and recorded with Delsys hardware (Bagnoli EMG System;
Delsys, Inc., USA). The activity of each muscle was determined by
measuring the mean value of the root-mean-square (RMS) and
the median power frequency (MPF) between the onset and the
offset of the first 6 subsequent bursts of the sprint. The RMS and
MPF values of both muscles were summed and then normalized
to the first sprint value of each condition (Smith and Billaut,
2010).
Blood Sampling and Analysis
A 92-µL blood sample was drawn ∼1 min after the last sprint
from fingertips using a capillary tube and analyzed with a
portable blood analyser (Epoc R
Blood Analysis System, Siemens
Healthinners, Munich, Germany). A thermal quality assurance
calibration was conducted before the pre- and the post-session
with a buffered aqueous solution according to manufacturer’s
recommendations. The blood measured pH, carbon dioxide and
oxygen partial pressure (PCO2, PO2), concentrations of sodium
([Na+]), potassium ([K+]), ionized calcium ([Ca++]), chloride
([Cl−]), glucose ([Glu]), lactate ([Lac−]) and hematocrit (Hct),
and calculated hemoglobin ([cHgb]), bicarbonate ([cHCO3−]),
total carbon dioxide, base excess of extra cellular fluid [BE(ecf)],
and base excess of blood [BE(b)].
Statistical Analysis
All data are reported as mean ±standard deviation (SD),
percentage of normalized values or percentage of change from
Pre-training. Before analysis, all variables were log-transformed
except for negative values (base excess). The Post- to Pre-training
and VHL-CTL differences were analyzed using Cohen’s effect
size (ES) ±90% confidence limits and compared to the smallest
worthwhile change (0.2 multiplied by the between-participant
SD) (Batterham and Hopkins, 2006;Hopkins et al., 2009).
Effect sizes were classified as small (>0.2), moderate (>0.5),
and large (>0.8). Using mechanistic inferences, qualitative
probabilistic terms for benefit were assigned to each effect using
the following scale: <0.5% most unlikely; 0.5–5% very unlikely;
5–25% unlikely; 25–75% possibly; 75–95% likely; 95–99.5%
very likely; >99.5% almost certainly. If the chance of having
better/greater and poorer/lower performances or physiological
changes were both >5%, the effect was deemed “unclear”
or “unmeaningful” (Batterham and Hopkins, 2006; Hopkins
et al., 2009). Pearson correlations were calculated to assess
associations between physiological changes and performance
improvements. Correlation coefficients of >0.1, >0.3, >0.5, and
>0.7 were considered small, moderate, large and very large
(Hopkins et al., 2009).
RESULTS
Of the 17 participants recruited, 13 completed the entire protocol
and were included in the analysis (VHL, n=7 and CTL, n=6).
One participant could not complete the study because of injury
not related to the study. The three others missed more than 3
training sessions and were therefore excluded from data analyses.
All participants from the VHL group tolerated the breathing
technique without any issues or complications. During training,
the averaged SpO2recorded during the three sets (including
sprints and recovery phases, but excluding the inter-set 3-min
recovery) was 87.7 ±4.6% for the VHL group and 96.9 ±0.5%
for CTL.
Frontiers in Sports and Active Living | www.frontiersin.org 4April 2020 | Volume 2 | Article 29
Lapointe et al. Breath-Hold Training During Sprints
Performance
Performance results for the RSA and 30-15IFT tests are displayed
in Table 1.Figure 2 also depicts the completion time for every
sprint in both VHL and CTL. The calculated smallest worthwhile
change for RSAbest equated to 0.5 s. Training had no effect on
RSAbest in any groups, but had a possible benefit on RSAmean
in both groups (VHL: −2.5 ±1.8% vs. CTL: −3.4 ±2.6%),
with no clear difference between groups. However, when the last
four sprints of the series were analyzed, VHL clearly reduced the
mean completion time compared to CTL (−3.0 ±4.3%, ES −0.31
±4.3, chances to observe poorer/trivial/better performance
after VHL: 3%/30%/67%). The calculated smallest worthwhile
change for RSASdec was 0.42%. The VHL group’s RSASdec clearly
improved from 7.3 ±3.2% to 5.5 ±2.7% with the intervention
(−24.5 ±27.2%, ES −0.47 ±0.40), while the change in the CTL
group from 7.1 ±3.1 to 6.5 ±2.5% remained unclear (−5.9 ±
21.5%, ES −0.13 ±0.42). This yielded a likely small advantage
for VHL over CTL (group difference: −19.8 ±33.8%, ES −0.44 ±
0.58, 4%/20%/76%). Maximal velocity in the 30-15IFT improved
both in VHL (7.5 ±2.9%) and in CTL (6.9 ±3.4%) above the
smallest worthwhile change of 0.33 km/h, with no clear difference
between groups.
Muscle Oxygenation
Muscle oxygenation during the RSA tests in VHL and CTL
is depicted in Figure 3 and between-groups changes for NIRS
variables are displayed in Figure 4. From pre- to post-training,
[tHb] peaks and amplitudes did not change in either groups.
However, [tHb]min increased in both VHL (1.2 ±0.3%, ES 0.31
±0.09, 97%/3%/0%) and CTL (1.3 ±0.8%, ES 0.30 ±0.19,
81%/19%/0%), with no difference between groups. Furthermore,
[HHb]max clearly decreased in VHL (−1.5 ±0.6%; ES −0.39
±0.15, 0%/2%/98%), but clearly increased in CTL (1.4 ±
0.6%, ES 0.30 ±0.18, 92%/8%/0%). As a result, there was an
almost certain difference between groups with VHL attenuating
the maximal deoxygenation (−2.9 ±0.8, ES −0.72 ±0.19,
0%/0%/100%). Similar changes were observed for [HHb]min
with a clear decrease in VHL (−2.3 ±0.6%; ES −0.65 ±0.17,
0%/0%/100%) and a clear increase in CTL (1.3 ±0.5%, ES 0.33 ±
0.12, 96%/4%/0%), yielding an almost certain difference between
groups (−3.6 ±0.8%, ES −1.00 ±0.21, 0%/0%/100%).
Electromyographic Activity
The changes in temporal profile of EMG amplitude (RMS)
and spectral profile of median power spectrum (MPF) for the
two investigated muscles in both conditions are displayed in
Figure 5. As depicted, and in line with other RSA studies,
the EMG RMS decreased over the 12 sprints both pre- and
post-training. However, while the average value for the 12
sprints did not change in CTL (−1.5±2.8, ES−0.14 ±0.26,
2%/64%/34%), RMS almost certainly increased in VHL (16.5 ±
4.5%, ES 1.01 ±0.29, 100%/0%/0%). This led to an almost certain
TABLE 1 | Mean changes in performance and perceptual exercise responses in the repeated-sprint ability (RSA) and the 30-15IFT tests after repeated-sprint training
performed with voluntary hypoventilation at low lung volume (VHL) or normal breathing (CTL).
Pre- Post- Within group
Post/Pre (Cohen’s d)
Probability (%)
RSAbest
(s)
VHL
CTL
VHL-CTL (Cohen’s)
Qualitative inference
4.80 ±0.35
4.83 ±0.36
4.86 ±0.36
4.88 ±0.43
0.04 ±0.30
Unclear
0.15 ±0.17
0.10 ±0.22
31/61/0
21/77/2
19/73/9
RSAmean
(s)
VHL
CTL
VHL-CTL (Cohen’s)
Qualitative inference
5.16 ±0.47
5.18 ±0.51
5.03 ±0.41
5.01 ±0.55
0.10 ±0.32
Unclear
−0.27 ±0.19
−0.32 ±0.23
0/26/74
0/19/81
30/64/6
RSASdec
(%)
VHL
CTL
VHL-CTL (Cohen’s)
Qualitative inference
7.25 ±3.18
7.08 ±3.08
5.49 ±2.70
6.46 ±2.50
–0.44 ±0.58
Likely beneficial
−0.47 ±0.40
−0.13 ±0.42
1/12/88
9/53/38
4/20/76
RPE RSA
(AU)
VHL
CTL
VHL-CTL (Cohen’s)
Qualitative inference
7.5 ±1.15
8.03 ±1.23
7.08 ±1.22
7.88 ±1.22
−0.24 ±0.53
Unclear
−0.32 ±0.30
−0.11 ±0.46
1/23/77
12/52/37
8/37/55
VIFT
(km·h−1)
VHL
CTL
VHL-CTL (Cohen’s)
Qualitative inference
18.78 ±1.68
18.63 ±1.75
20.18 ±1.39
19.88 ±1.41
0.07 ±0.49
Unclear
0.81 ±0.32
0.69 ±0.35
100/0/0
98/1/0
33/50/17
RPE 30–15
(AU)
VHL
CTL
VHL-CTL (Cohen’s)
Qualitative inference
7.58 ±0.68
7.72 ±1.22
7.94 ±0.76
8.38 ±0.98
−0.33 ±0.96
Unclear
0.43 ±0.59
0.53 ±0.67
76/20/4
81/15/4
17/23/57
Data are presented as means ±SD. Cohen’s effect size ±90% confidence limits. Clear changes within and between groups are indicated in bold. RSAbest, best sprint time; RSAmean,
average completion time of the 12 sprints; RSASdec, % score decrement; RPE, rate of perceived exertion; VIFT , maximal velocity reached in the Intermittent 30–15 fitness test; AU,
arbitrary units.
Frontiers in Sports and Active Living | www.frontiersin.org 5April 2020 | Volume 2 | Article 29
Lapointe et al. Breath-Hold Training During Sprints
FIGURE 2 | Completion time for every sprint of the RSA test performed with normal breathing (CTL) and voluntary hypoventilation at low volume (VHL) before and
after 4 weeks of repeated-sprint training. Data are presented as means ±SE. *Small effect between groups.
FIGURE 3 | Peak (A) and nadir (B) values of normalized deoxyhemoglobin concentration ([HHb]) over 11 sprint/recovery cycles with normal breathing (CTL) and
voluntary hypoventilation at low lung volume (VHL) before and after 4 weeks of training. Data are presented as means ±SD, expressed as a percent of the first
sprint/recovery cycle. **Moderate effect between groups; †Large effect between groups.
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Lapointe et al. Breath-Hold Training During Sprints
FIGURE 4 | Percentage difference and qualitative interference in the change in
NIRS variables from Pre- to Post- in VHL compared to CTL.
difference between training groups (18.2 ±5.1%, ES 1.28 ±0.38,
100%/0%/0%). Similar to the RMS changes, MPF decreased from
Pre- to Post-training in CTL (−2.0 ±2.0%, ES −0.45 ±0.43,
1%/15%/84%), but increased in VHL (7.7 ±4.7%, ES 0.97 ±0.61,
98%/2%/0%). There was a very likely clear advantage of VHL
training in maintaining MPF over CTL (9.8 ±5.0%, ES 1.40 ±
0.74, 99%/1%/0%).
Blood Sample Analysis
Table 2 displays the changes and VHL-CTL differences for
blood parameters in the RSA tests. In Post-, compared to
Pre-, pH increased in CTL (0.5 ±0.5%; ES 0.58 ±0.58,
88%/10%/2%), but remained unchanged in VHL, yielding a
clear difference between groups (−0.4 ±0.5%, ES −0.38 ±
0.51, 4%23%/73%). Partial pressure of carbon dioxide (PCO2)
marginally decreased in CTL (−3.6 ±5.5%; ES −0.27 ±0.40,
3%/34%/63%), and remained unchanged in VHL, yielding a
likely difference between groups (8.5 ±11.2%, ES 0.61 ±
0.79, 82%/14%/5%). Although the changes in [K+] were not
meaningfully different from Pre- to Post- within each group
(10.4% increase in CTL vs. 9.0% decrease in VHL), comparing
the changes between groups yielded a likely difference (−17.5
±31.2, ES −0.67 ±0.94, 5%/13%/80%). The lowering in [K+]
was largely correlated with the improvement in RSASdec post-
training in the VHL group only (r=0.66, P=0.03). All
other blood markers were not meaningfully different between
training groups.
Perceptual Exercise Responses
RPE scores for the RSA and 30-15IFT tests are displayed in
Table 1. RPE only decreased after VHL in Post- compared with
Pre- in the RSA test (−5.8 ±5.7%, ES −0.32, 1%/23%/77%),
while CTL did not exhibit any changes. However, there was
no clear difference between groups. In the 30-15IFT test, RPE
increased in both groups at Post-, and there was no difference
between groups.
DISCUSSION
We report that 8 sessions of RS training including COD
performed with voluntary respiratory blockage at low lung
volumes by basketball players elicited clear, though not large,
RSA gain compared to training with unrestricted breathing,
but this improvement was not transferable to longer activities.
The novel findings were that training with VHL, in contrast
to control, enhanced muscle reoxygenation during recovery
periods, increased total electric activity (RMS) and power
spectrum frequency (MPF) of the lower-limb muscles and
reduced the extracellular [K+], which was significantly correlated
with the gain in RSA.
The improvement in RSA (and absence of change in
maximal speed) was also demonstrated in highly-trained rugby
players who increased the maximum number of sprints before
exhaustion by 64% (Fornasier-Santos et al., 2018) and in trained
swimmers who displayed 35% improvement in sprint number
(Trincat et al., 2017). Woorons et al. (2019b) were the first to use
a close-loop design and reported a 4.1% improvement in mean
power score decrement during ten 6-s sprints. In a recent study,
which also used a close-loop test, running RSA was improved
by 2.5% in team-sport players after 3 weeks of high-intensity
cycle training with VHL (Woorons et al., 2020). Our present
results confirm these findings and together robustly highlight that
RSA can be improved in a relatively short timeframe within the
training calendar. In most team sports, the ability of players to
resist and/or limit neuromuscular fatigue to maintain the highest
intensity or velocity is paramount. For instance, RSA may be
decisive in the final stages of the game by giving the possibility to
win possession of the ball and increasing the chances of scoring
while preventing the opponents to do so (Billaut and Bishop,
2009; Girard et al., 2011). In this perspective, it is interesting to
note that, so far, all studies combining VHL with RS training
(including the present one), reported significant gains in RSA
(Trincat et al., 2017; Fornasier-Santos et al., 2018; Woorons et al.,
2019b). Conversely, RS training studies using simulated hypoxia
(the RSH modality) reported either positive gains (Faiss et al.,
2013, 2015) or no meaningful change (Gatterer et al., 2014;
Brocherie et al., 2017). However, it is noteworthy that the RS
training with VHL did not lead to greater improvement in a
longer activity than CTL, since maximal aerobic performance in
the 30-15IFT was improved similarly in both groups.
The efficacy of VHL training has mainly been ascribed to
a larger contribution from the anaerobic glycolysis (Trincat
et al., 2017). In the present study, the RSA gains in VHL were
concomitant with clear changes in muscle oxygenation patterns.
Peaks and nadirs of the [HHb] signal were clearly lower after
training in the VHL group only. The lower [HHb]max indicates
a lower O2extraction at the muscle level during the sprints
and may suggest (when analyzed in conjunction with better
RSA) a metabolic shift toward anaerobic activity to produce
ATP and sustain mechanical power (Woorons et al., 2011, 2017).
This superior glycolytic activity should have resulted in larger
lactate accumulation in the blood after the sprints. However,
like others (Fornasier-Santos et al., 2018; Woorons et al., 2019b),
we only reported trivial changes in [Lac−] between groups. The
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Lapointe et al. Breath-Hold Training During Sprints
FIGURE 5 | Changes in normalized EMG amplitude (RMS) (A) and median power frequency (MPF) (B) of the biceps femoris and gastrocnemius muscles during 12
sprints with normal breathing (CTL) and voluntary hypoventilation at low lung volume (VHL) before and after 4 weeks of training. Data are presented as means ±SD,
expressed as a percent of sprint 1. †Large effect between groups. The RMS values decreased from 0.45 ±0.15mV to 0.35 ±0.13 mV in Pre- and from 0.43 ±
0.17 mV to 0.31 ±0.11mV in Post- in the CTL group. In VHL, RMS decreased from 0.41 ±0.11mV to 0.31 ±0.14 mV in Pre- and from 0.41 ±0.11 mV to 0.32 ±
0.14 mV in Post-. Average MPF values decreased from 105.5 ±25.2 Hz to 99.2 ±23.8 Hz in Pre- and from 104.6 ±25.3 Hz to 91.4 ±25.4 Hz in Post- in CTL group.
In VHL, MPF decreased from 112.3 ±17.0 Hz to 108.4 ±16.3Hz in Pre- and from 106.6 ±17.4 Hz to 100.1 ±18.1 Hz in Post-.
discrepancy between studies may be related to exercise duration
and subsequent contribution from energy systems. While Trincat
et al. (2017) used 25-m swim sprints of ∼14-s, we and others
(Fornasier-Santos et al., 2018; Woorons et al., 2019b) investigated
running sprints of ∼5-s. Longer sprints typically require greater
contribution from the lactic glycolysis, probably explaining the
higher [Lac−] post-training. It may also be caused by a greater
clearance during recovery phases between sprints.
We observed a lower [HHb]min during recovery periods after
VHL training, whereas it increased in CTL, showing the very
different effects of the two training regimens. This indicates
a better reoxygenation capacity between sprints (Billaut and
Buchheit, 2013) after VHL training. Such local adaptation in
active locomotor muscles is reported here for the first time in
the scientific literature and may explain the greater systemic VO2
observed during recovery phases between repeated sprints after
VHL training (Woorons et al., 2019b). Alternatively, the greater
muscle reoxygenation could be the consequence of greater
cardiac output and arterial inflow to the muscles purported
to occur after VHL (Woorons et al., 2019b). This assumption
is supported by a recent study which shows that a high-
intensity VHL training in cycling induces transferable benefits for
running RSA (Woorons et al., 2020). Whatever the case, these
avenues will have to be disentangled in future investigations.
Surprisingly however, that latter study did not observe any
alteration of muscle reoxygenation during a similar repeated-
sprint training intervention. The difference between these
findings may be explained by the methodological analysis. While
the authors examined averages in the [HHb] signal over several
seconds, we determined peaks and nadirs from single values
which more accurately detects maximal metabolic perturbations
(Rodriguez et al., 2018). The different physiological profiles of the
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Lapointe et al. Breath-Hold Training During Sprints
TABLE 2 | Mean changes in blood parameters following the RSA test after repeated-sprint training performed with voluntary hypoventilation at low lung volume (VHL) or
normal breathing (CTL).
CTL VHL Difference between groups
Pre- Post- Pre- Post- % D Cohen’s Probability (%)
pH 7.22 ±0.04 7.25 ±0.06 7.22 ±0.08 7.23 ±0.09 −0.4 ±0.5 –0.38 ±0.14 4/23/73
PCO2(mmol·L–1) 31.95 ±3.10 30.88 ±3.85 31.36 ±5.11 32.46 ±2.60 8.5 ±11.2 0.61 ±0.79 82/14/5
PO2(mmol·L–1) 88.53 ±2.33 88.85 ±5.04 92.64 ±11.60 89.81 ±8.34 −3.0 ±7.7 −0.33 ±0.8 13/26/61
[Na+] (mmol·L−1) 144.00 ±1.67 144.67 ±2.25 144.75 ±4.68 144.00 ±1.77 −0.9 ±2.5 −0.44 ±1.15 17/19/65
[K+] (mmol·L−1) 5.02 ±0.3 5.67 ±1.33 6.73 ±2.64 5.93 ±1.41 −17.5 ±31.2 −0.67 ±0.94 5/13/80
[Ca++] (mmol·L−1) 1.25 ±0.02 1.25 ±0.05 1.29 ±0.08 1.29 ±0.06 −0.7 ±4.4 −0.13 ±0.86 25/30/44
[Cl−] (mmol·L−1) 112.83 ±2.56 113.00 ±3.58 114.00 ±6.57 113.75 ±4.17 −0.3 ±5.3 −0.06 ±1.25 36/22/42
[Glu] (mmol·L−1) 8.53 ±1.27 8.35 ±1.22 7.49 ±0.89 7.33 ±0.91 −0.2 ±4.7 −0.01 ±0.30 12/74/14
[Lac−] (mmol·L−1) 13.49 ±1.51 12.12 ±1.53 14.03 ±2.38 12.98 ±2.97 2.1 ±12.4 0.11 ±0.63 40/40/19
Hct (%) 45.67 ±2.94 47.33 ±3.93 46.13 ±5.94 46.88 ±4.70 −1.5 ±4.4 −0.15 ±0.41 8/51/41
[cHCO3−] (mmol·L−1) 13.05 ±1.99 13.65 ±1.78 12.98 ±2.92 13.79 ±2.72 1.7 ±13.7 0.09 ±0.69 39/38/23
[cTCO2] (mmol·L−1) 14.02 ±2.04 14.58 ±1.82 13.93 ±2.99 14.78 ±2.72 2.2 ±13.8 0.12 ±0.73 42/36/21
BE(ecf) (mmol·L−1)−14.70 ±2.54 −13.52 ±2.48 −14.74 ±3.86 −13.79 ±4.07 −0.2 ±1.9 −0.07 ±0.55 20/47/33
BE(b) (mmol·L−1)−13.47 ±2.45 −12.10 ±2.51 −13.46 ±3.75 −12.61 ±4.07 −0.5 ±1.8 −0.15 ±0.53 13/43/43
SpO2(%) 94.85 ±0.45 95.35 ±0.89 95.28 ±1.44 95.14 ±0.75 −0.7 ±1.1 −0.61 ±1.04 9/15/76
cHgb (g·dL−1) 15.48 ±0.96 16.05 ±1.30 15.65 ±2.03 15.83 ±1.59 −2.0 ±4.5 −0.20 ±0.43 6/44/49
Data are presented as means ±SD. Cohen’s effect size ±90% confidence limits. Clear changes between groups are indicated in bold.
athletes volunteering in the two studies (team-sport athletes vs.
endurance cyclists) and the exercise mode (running vs. cycling)
might also have come into play. Nonetheless, we interpret
our data to suggest that the better reoxygenation facilitated
the resynthesis of phosphocreatine (PCr) during short recovery
periods (McMahon and Jenkins, 2002). This hypothesis could
explain the gain in RSA without concomitant changes in the
typical markers of “lactic” metabolism ([Lac−] and [HCO3−]).
It is further supported by the fact that PCr availability is highly
critical to RSA and that aerobic oxidations and PCr become the
major sources of energy as sprints are repeated while anaerobic
glycolysis contribution progressively fades (for review see Billaut
and Bishop, 2009; Girard et al., 2011). In addition, RSH training
with 14.5% O2leading to similar hypoxemia has been shown to
significantly increase the intramuscular PCr content as measured
with P-magnetic resonance spectroscopy in sprinters compared
to training in normoxia (Kasai et al., 2019). Unfortunately, P-
MRS does not allow distinguishing between fiber types, and
it is currently unknown whether type-II fibers better adapt to
VHL than type-I fibers (as might be the case in RSH, Faiss
et al., 2013, 2015). Nonetheless, knowing that fast-twitch fibers
are fully recruited at all-out intensity and that, in the present
study, the EMG power spectrum was maintained toward higher
stimulation frequencies (see EMG section below), we could
reasonably propose that fast-twitch fibers preferentially benefited
from the better reoxygenation during recovery and maintained a
relatively high contribution to mechanical power in latter sprints.
In fact, the cumulated completion time of the last 4 sprints
was clearly lower after training in VHL (Figure 2), supporting
the hypothesis of a delayed fatigue. Further investigations using
magnetic resonance imaging or muscle biopsy are required to
assess fiber-specific intramuscular PCr content and resynthesis
rate after VHL training to support this adaptative mechanism.
In the RSA literature, reductions in EMG-derived indices
RMS and MPF have been widely described (Billaut and Bishop,
2009; Girard et al., 2011) and are typically taken as reduction
in total motor unit recruitment and increased reliance on
slow, fatigue-resistant type-1 motor units, respectively, due to
the development of neuromuscular fatigue. There is no data
on electromyographic behavior of active skeletal muscles after
breath-hold training, so the current study highlights for the
first time the marked impact of VHL training on these neural
strategies (Figure 5). While training with normal breathing did
not change muscle recruitment patterns, training with VHL
led to a better maintenance of the initial muscle activity over
subsequent sprints (+16.5% RMS) and the recruitment of higher-
frequency motor units (+7.7% MPF) concomitant to enhanced
sprint endurance in later repetitions. The most likely explanation
would be that the better reoxygenation during recovery phases
improved the metabolic milieu of contracting muscles and
attenuated the reflex inhibition originating from group III and
IV afferents, thereby maintaining neural drive to skeletal muscles
(Amann and Dempsey, 2008).
Another speculative alternative, which will need to be
examined in future studies, may include the following. Breath-
hold exercise induces a sharp accumulation of CO2in blood
and tissues (Woorons et al., 2017), which is a potent signaling
molecule. Although the direct effects (if any) of hypercapnia on
central motor command are unknown in exercising humans, an
increase in arterial CO2increases cerebral blood flow (Hoiland
et al., 2019) which could alter the central motor command (Nybo
and Rasmussen, 2007). Greater increases in cerebral blood flow
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Lapointe et al. Breath-Hold Training During Sprints
have been observed during apnea in breath-hold divers than
in controls and interpreted as a protection of the brain against
the alteration of blood gas (Joulia et al., 2009). However, we
must remember that cerebrovascular reactivity to CO2is a highly
modifiable response that may be altered by hypoxia, changes in
blood pressure, and exercise intensity (Hoiland et al., 2019).
While changes in EMG indices may be used as surrogates
of neural drive, they can also be influenced by sarcolemma
excitability and thereby reflect changes in conduction velocity
of action potentials. Membrane excitability is impaired during
intense fatiguing exercise as a result of a lower activity of the
sodium(Na+)/potassium(K+)-adenosine triphosphatase (NKA)
activity to maintain transmembrane ionic gradient caused by
the decline in pH and accumulation of inorganic phosphates.
This ultimately results in a K+ion efflux out of the interstitium
that impairs peripheral contractile function (Juel et al., 2000;
Fraser et al., 2002). Interestingly, we observed a lower capillary
blood [K+] after training in the VHL group only, which was
significantly correlated with the enhancement in RSA. This
is the first report of ionic concentrations after VHL training,
and we may speculate that the combination of training at
very high intensity with respiratory blockage at low lung
volume creates favorable conditions for metabolic by-products
accumulation and ionic perturbations, both of which are
potent stimuli for promoting adaptations in skeletal muscle K+
regulation (Christiansen, 2019). Along this line of reasoning,
Christiansen et al. (2019) demonstrated that high-intensity
interval training with blood-flow restriction (leading to 90%
tissue deoxygenation assessed via NIRS during complete arterial
occlusion) reduces the net K+release from contracting muscles
during intense exercise, due to a training-induced increase
in Na+, K+-ATPase-isoform abundance in the sarcolemma
and T-tubuli. Near-maximal levels of muscle deoxygenation
have also been reported during repeated sprints with VHL
(Woorons et al., 2017), suggesting that the current VHL training
probably led to similar metabolic perturbations conducive
to K+regulation improvement. The re-establishment of the
transmembrane K+gradient could also explain in part the
higher RMS and MPF observed after VHL training in the
present study. However, we must acknowledge that systemic K+
levels may inaccurately reflect locomotor muscle K+homeostasis
(Juel et al., 2000), indicating the need to directly assess
K+efflux from exercising musculature to clarify the role of
VHL with respect to regulating K+homeostasis in human
skeletal muscle.
Future experiments will need to ascertain some of these
findings to distinguish the mechanisms underlying VHL from
other hypoxic training methods and, potentially, to explore
combination of modalities.
CONCLUSION
The current study demonstrated that 8 sessions of VHL training
including changes of direction enhanced performance during
straight-line repeated sprints more than the same training with
unrestricted breathing. Such training strategy could therefore
be implemented in various sports settings as a practical way
to induce arterial hypoxemia. Physiological responses measured
after training suggested that the gain in RSA may be attributed
to greater muscle reoxygenation, enhanced muscle recruitment
strategies, and improved K+regulation.
DATA AVAILABILITY STATEMENT
All datasets generated for this study are included in the
article/supplementary material.
ETHICS STATEMENT
The studies involving human participants were reviewed
and approved by ethics committee of Laval University. The
patients/participants provided their written informed consent to
participate in this study.
AUTHOR CONTRIBUTIONS
JL and FB conceived and designed the experiments and analyzed
the data. JL and PP-D performed the experiments. JL, FB, XW,
and FL interpreted the results of research. JL, FB, PP-D, XW,
and FL critically revised the paper and approved the final version
of manuscript.
ACKNOWLEDGMENTS
The authors thank the basketball players, their coaches and
graduate students for their assistance.
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Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Copyright © 2020 Lapointe, Paradis-Deschênes, Woorons, Lemaître and Billaut.
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Frontiers in Sports and Active Living | www.frontiersin.org 11 April 2020 | Volume 2 | Article 29
