ArticlePDF Available


This investigation examined the effect of partial-body cryostimulation (PBC) performed in the recovery time between a strength training and an interval running (IR). Nine rugby players [age 23.7±3.6, BMI 28.0±2.6 kg/m2] were randomly exposed to two different conditions: i) PBC: 3-min at -160°C; ii) passive recovery at 21°C. We recorded the bioelectrical impedance analysis (BIA), temperature, and cardiac autonomic variables in three moments: at baseline, after strength training (R0) and after 90-min of recovery (R90). Additionally, the blood lactate concentration was measured 1-min before and 2.5-min after the IR. The heart rate, energy cost, minute ventilation, oxygen uptake and metabolic power were assessed during the IR. The homeostatic hydration status was affected by the execution of intense strength training sub-session. Then, after PBC the BIA vector was restored back, close to normohydration status. Autonomic variables changed over time in both conditions, although the mean differences and effect sizes were higher in the PBC condition. During IR, the heart rate was 3.5% lower after PBC, and the same result was observed for the oxygen uptake (~4.9%) and ventilation (~6.5%). The energy cost measured after cryotherapy was ~9.0% lower than after passive recovery. Cryotherapy enhances recovery after a single strength training, while during the subsequent interval running it shows a reduction in cardiorespiratory and metabolic parameters. PBC may be used in those athletes who compete or train more than once in the same day to improve recovery between successive training sessions or competitions.
Submitted to Applied Physiology, Nutrition, and Metabolism
Title: Physiological responses to partial-body cryotherapy performed during a
concurrent strength and endurance session
Authors: Alessandro Piras; Francesco Campa; Stefania Toselli; Di Michele Rocco;
Milena Raffi,
Affiliation: Department of Biomedical and Neuromotor Sciences University of
Author’s correspondence:
Dr. Alessandro Piras,
Department of Biomedical and Neuromotor Sciences
University of Bologna
Piazza di Porta S. Donato, 2
40126 Bologna – Italy
Ph: (0039) 051 - 2091740
Fax: (0039) 051 - 2091737
Running head: Cryotherapy and concurrent training
Number of pages: 24
Number of words in abstract: 241
Number of figures: 3
Number of tables: 4
Number of references: 38
Word count: 4329
Page 1 of 33
This investigation examined the effect of partial-body cryostimulation (PBC)
performed in the recovery time between a strength training and an interval running
(IR). Nine rugby players [age 23.7±3.6, BMI 28.0±2.6 kg/m
] were randomly
exposed to two different conditions: i) PBC: 3-min at -160°C; ii) passive recovery at
21°C. We recorded the bioelectrical impedance analysis (BIA), temperature, and
cardiac autonomic variables in three moments: at baseline, after strength training
(R0) and after 90-min of recovery (R90). Additionally, the blood lactate
concentration was measured 1-min before and 2.5-min after the IR. The heart rate,
energy cost, minute ventilation, oxygen uptake and metabolic power were assessed
during the IR. The homeostatic hydration status was affected by the execution of
intense strength training sub-session. Then, after PBC the BIA vector was restored
back, close to normohydration status. Autonomic variables changed over time in both
conditions, although the mean differences and effect sizes were higher in the PBC
condition. During IR, the heart rate was 3.5% lower after PBC, and the same result
was observed for the oxygen uptake
(~4.9%) and ventilation (~6.5%). The energy
cost measured after cryotherapy was ~9.0% lower than after passive recovery.
Cryotherapy enhances recovery after a single strength training, while during the
subsequent interval running it shows a reduction in cardiorespiratory and metabolic
parameters. PBC may be used in those athletes who compete or train more than once
in the same day to improve recovery between successive training sessions or
Keywords: baroreflex sensitivity; energy cost; heart rate variability; interval
Page 2 of 33
Page 3 of 33
A recent strategy used for post-exercise recovery in sports is cryotherapy,
which involves local, partial-body (PBC), and whole-body exposures (WBC). The
major differences in the two systems are the temperatures (-110°C for WBC and -
160°C during PBC), the head exposure (only during WBC), and the source of cold
stimulation (compressor for WBC and nitrogen gas during PBC) (Hausswirth et al.,
2013). The cryotherapy has a vasoconstrictive effect during recovery after exercise,
reducing the inflammation responses through a decrease of the cell metabolism,
leading to improvements in blood and oxygen supply if performed between two
consecutive training sessions. Moreover, stimulates the autonomic nervous
parasympathetic activity favouring acute recovery (Hausswirth et al. 2013). Instead,
performed before submaximal exercise reduces heart rate leading to higher stroke
In sports, athletes combine strength and endurance training within the same
training cycle, a procedure defined ‘concurrent training’ (Leveritt et al. 1999). As
pointed out by Leveritt et al. (1999), some studies have addressed the issue of
assessing the inhibition in strength development after concurrent strength and
endurance training with respect to strength training alone. This matter is still
controversial (Fyfe and Loenneke 2018). A recent systematic review and meta-
analysis (Sabag et al. 2018) has showed that high intensity interval training (HIIT)
can be performed with resistance exercise without negatively impacting hypertrophy,
and that any attenuation of lower body muscular strength might be improved by
prescribing running instead of cycling, with adequate rest between HIIT and
resistance sessions. Possible causes of the above-mentioned interferences could be
the residual fatigue in the neuromuscular system and the overtraining produced by
imbalances in the athlete recovery processes. Rugby players, one time a week,
Page 4 of 33
perform two-a-day workouts, where the interval between training sessions represents
their actual recovery time. Deficiency of proper recovery may result in the athlete
being unable to train at the required intensity or complete the required load in extra
time (Barnett 2006). Therefore, during these training sessions, a key issue is the
recovery modalities that should be followed by the athletes. Until now, only two
studies have investigated the effects of cryotherapy on recovery between two training
sessions. Schaal et al. (2013) demonstrated that WBC yields a significant increase in
vagal-related heart rate variability (HRV) indices and a decrease in heart rate (HR)
during 70 min of recovery between two synchronized swimming performances.
Ferreira-Junior et al. (2014) found a significant increase, after 40 min of strength
recovery, on eccentric peak torque and total work when subjects were exposed to
PBC with respect to passive recovery.
Partial-body cryotherapy has become a popular mode of cryotherapy
(Hausswirth et al. 2013), but only few studies have investigated this method on
recovery ( Ferreira-Junior et al. 2014; Hausswirth et al. 2013; Holmes and
Willoughby 2016). Moreover, no study has examined the influence of cryotherapy
during concurrent training in team sports. Therefore, the present study aimed to
evaluate the effect of cryotherapy performed during the recovery time between a
strength training and an interval running in a group of rugby players. We
hypothesized that the physiological responses to this treatment will accelerate
strength recovery, improving the subsequent interval running in athletes who train
more than once on the same day. The rationale of our hypothesis is that, cryotherapy
would induce lower submaximal heart rate due to lower thermal stress, as well as the
increase of cardiac parasympathetic activity (Stanley et al. 2014), favouring acute
recovery after strength training. In addition, cryotherapy causes a peripheral
vasoconstriction that leads to improvements in blood and oxygen supply in the
Page 5 of 33
working musculature (Krüger et al. 2015) improving the cardiorespiratory efficiency
or less cardiovascular stress during the subsequent intermittent exercise. From a
practical perspective, PBC might speed up recovery in those athletes who compete or
train more than once in the same day.
An a priori power analysis was conducted to determine the sample size for the
study (G*Power, Germany). The following design specifications were
considered: α = 0.05; (1-β) = 0.8; effect size f = 0.5; test family = F test and
statistical test = ANOVA repeated measures, within-between interaction. The sample
size estimated according to these specifications was 8 subjects. Thus, we selected 9
rugby league players who volunteered to participate in this study (Table 1). All
subjects were instructed to continue normal daily activities and to refrain from
training the day before testing. Additionally, all the exclusion criteria suggested by
Podbielska et al. (2006) were respected. This study was approved by the Bioethic
Committee of the University of Bologna, and all participants were informed of the
benefits and risks of the investigation prior to signing an institutionally approved
informed consent document to participate in the study.
Testing procedure
The athletes visited the laboratory 4 times. All tests were performed at the
same time of the day (9:00 12:00 AM), in a quiet room with stable temperature
(21°C; 52% of humidity). During the first visit, the athletes completed an
incremental running test to determine their maximal oxygen uptake (V’O
max) and
to familiarize with the interval running on treadmill. The second visit was used to
Page 6 of 33
determine their maximal whole-body muscular strength (1-RM). The recording
sessions were performed during the third and fourth visits when the athletes were
tested in a randomized, counterbalanced, crossover design (Figure 1).
Maximal oxygen consumption assessment (VO
max). The expired gas analysis
(Quark CPET, Cosmed, Italy) was performed on motor-driven treadmill (Cosmed,
Italy) at 8 km/h for 3-min as a warm-up, followed by 1 min at 10 km/h with 1% of
incline, and an instantaneous increase of 0.5 km/h every min until exhaustion. The
maximal exercise test lasted until attainment of oxygen uptake (V’O
) plateau or the
attainment of at least one of the two additional criteria: (i) a plateau of heart rate
despite an increased velocity, or (ii) exercise cessation due to substantial fatigue.
plateau was defined as an increase in V’O
50 ml min-1 during the last 30 s
despite increased velocity (Yoon et al. 2007). The highest V’O
values reached
during the exercise phase of the incremental test were considered as the V’O
Strength assessment (1-RM). Maximal whole-body muscular strength was assessed
using the following five multiarticular exercises: bench press, squat, barbell row,
deadlift, and overhead press. The participants first completed ten warm-up
repetitions, and after a suitable rest period, one repetition maximum (1-RM) values
were assessed according to the following equation: 1-RM=weight lifted/[1.0278-
(0.0278 x N° repetitions)] (Brzycki 1993). It has been easy to establish with accuracy
their 1-RM as they were athletes accustomed to strength exercises. Proper exercise
execution was followed and enforced by one of the investigators who supervised and
documented each testing session.
Recording sessions. During the third and fourth visits, separated by one-week, the
athletes were tested in a randomized, counterbalanced, crossover design (Figure 1):
1) PBC; partial body cryotherapy: 3-min at -160°C during 90-min of recovery; 2)
CON; control: 90 min of passive recovery at 21°C. We measured bioelectrical-
Page 7 of 33
impedance standards, temperature, and cardiac autonomic regulation parameters in
three moments: at baseline, after strength training (start of recovery - R0), and after
90-min of recovery (R90). Additionally, the blood lactate concentration (La) was
measured 1-min before and 2.5-min after the IR sub-session, while heart rate (HR),
energy cost (EC), minute ventilation (VE), oxygen uptake (V’O
), and metabolic
power (Pmet) were assessed during the IR sub-session (Figure 1). PBC was
performed 15 minutes after strength training in a head-out cryochamber using
gaseous nitrogen (Space Cabin Cryomed, Slovakia) at -160°C for 3-min. Participants
wore bathing suits, gloves, socks and shoes with thermic protection for their
extremities. For the remaining recovery period, athletes seated at the laboratory with
a temperature of 21°C. The CON condition consisted of passive recovery, during
which athletes remained seated on a chair in the laboratory at 21°C. During the entire
procedure (exercise and recovery), drinking or eating was forbidden.
Body temperature (head, right hand, right foot) was measured by an infrared
thermometer (Tecnimed, Italy) in three moments: at baseline, after strength training
(R0), and after 90-min of recovery (R90). The measurement areas were marked with
a pen before each condition.
*****Figure 1 near here*****
Exercise Programs
Strength protocol. Each sub-session started with a 5-min warm-up. The conditioning
phase involved the same five resistance exercise stations used for the maximal
whole-body muscular strength assessment. The program involved performing five
sets of progressively heavier weights and lower reps, separated by 3 min of rest. It
was an “ascending pyramid” program (increase weight, decrease reps), and consisted
of performing a light set (50% of 1RM) for 10 reps, followed by 8 reps at 60%, 6
Page 8 of 33
reps at 70%, 4 reps at 80%, and 2 reps at 90% of 1RM (Brown and National Strength
& Conditioning Association (U.S.), 2007).
IR protocol. Each sub-session was performed on the same motor-driven treadmill
used during the V’O2max test and monitored through the expired gas analysis and
HR monitoring. It consisted of 1-min sprints at 95% of V’O
max followed by1-min
of active rest at 45% of VO
max repeated for a total of 10-min of running (Denadai
et al. 2006). Blood lactate samples were performed 1-min before and 2.5-min after
interval running. Both the strength and IR sessions were supervised by three
Body composition assessment
All body composition measurements were performed in resting conditions.
Body height was measured by a wall stadiometer to the nearest 0.1 cm and body
mass was measured using a balance to the nearest 0.1 kg. Fat-free mass and fat mass
were determined with the equation of Kotler et al.(1996).
Bioelectrical impedance vector analysis (BIVA), studied and validated for
healthy population, as well as for specific patient subgroups and athletes (Campa and
Toselli 2018; Lukaski 2013; Micheli et al. 2014) was performed with a phase-
sensitive impedance plethysmograph (BIA-101, Akern-RJL Systems, Italy) at
baseline; after strength training; and after 90 min of recovery. The electrodes were
placed on the right hand and foot dorsum while the subjects lied in a supine position.
The bioelectrical-impedance vector analysis calculates the body composition
considering the impedance components like resistance (R) that depends on lean
tissue mass and tissue hydration, and reactance (Xc), associated with cell size and
integrity of the cell membranes (Lukaski, 2013). We standardized R and Xc by the
subjects’ height (H) to remove the effect of conductor length, thus expressing values
Page 9 of 33
in Ohm/m. The combination of R and Xc return an impedance vector (arc tangent of
Xc/R expressed in degrees), and its direction is defined as the phase angle (PA°).
PA° is an indicator of cellular health and an index of fluid distribution between the
intracellular and extracellular compartments. A main advantage of the use of PA° is
that it can be applied even under unstable tissue hydration conditions (Selberg and
Selberg 2002), because it indicates progressive changes in tissue hydration; from
dehydration to hyperhydration with apparent edema (Lukaski 2013).
Cardiac autonomic regulation assessment (HRV and BRS)
Athletes were asked to stay in a supine position for 15 min, in a comfortable
bed, with a respiratory frequency at 12-15 breaths/min. Only 5 min, from 10’ to 15’
were used for analysis (Camm et al. 1996). Participants underwent non-invasive
continuous blood pressure monitoring using the servo-controlled infrared finger
plethysmography (Portapres device; TNO/BMI) for analysis of HRV and baroreflex
sensitivity (BRS) (Piras et al. 2017; Piras and Gatta 2017).
HRV analysis. The Portapres recordings were used to extract time series of R-R
intervals and systolic as well as diastolic pressures, to analyse HRV and BRS. Data
were analysed with Kubios HRV software (v. 3.0, 2017, Finland), in which all time
series were filtered to exclude artefacts. Time domain indices for HRV analysis were
the standard deviation of the R-R interval (SDNN) and the square root of the mean
squared differences of successive R-R intervals (RMSSD). The power spectrum
density of HRV was estimated by an autoregressive method with model validation.
Powers in the bands of low frequency (LF, 0.04–0.15 Hz) and high frequency (HF,
0.15–0.4 Hz) were calculated. It has been shown that the HF spectral component of
HR variability (HFRR) is an index of the vagal tone, whereas both sympathetic and
vagal activities contributed to the LF (LFRR) spectral component of HRV (Camm et
Page 10 of 33
al. 1996). Both indices were expressed in absolute and normalized units. Such
normalized units are obtained by dividing the power of each component by total
variance from which the very-low-frequency component (below 0.04 Hz) had been
subtracted and multiplying this value by 100 (Pagani et al. 1986).
BRS analysis. Baroreflex sensitivity was computed from RR intervals and systolic
blood pressure sequence subtracted from the finger arterial pressure waveform.
These data were then used to define the oscillations in both heart rate and systolic
arterial pressure measures. Beatscope version 1.1a (TNO/BMI, The Netherlands) was
used to evaluate spontaneous BRS, with a BRS add-on module that computes the
time-domain cross correlation BRS.
Energy cost assessment during IR
In both running conditions, HR, V′O
, V′E and respiratory exchange ratio
were collected breath by breath (Quark CPET, Cosmed, Italy). A blood sample was
obtained from the index finger to determine La (Lapre; Lapost) (Lactate Scout,
Germany) 1-min before and 2.5-min after running.
Figure 2 shows a typical tracing of a subject’s oxygen uptake as a function of
time during IR in both CON and PBC conditions. V′O
increases during each bout of
exercise at about 95%VO
max and decreases during active recovery at about
max. Metabolic data collected during the working phase were averaged and
used in the following analysis.
The energy cost (EC) of interval running was calculated based on values of
net and of blood lactate concentration (Zamparo et al. 2015):
1. The breath-by-breath net oxygen uptake (V’O
net, ml/kg/min), was
calculated by subtracting the resting V’O
from V’O
values. The energy
Page 11 of 33
derived from aerobic energy sources (EO
, ml/kg) was calculated by
multiplying V′O
net for the total exercise duration (min).
2. The energy derived from anaerobic lactic energy sources (ELa, ml/kg)
was calculated by multiplying La
(mM), e.g. the difference between the
largest value of La recorded at the end of the test and La recorded at rest,
by an energy equivalent of 3.3 ml/kg/mM (Di Prampero and Ferretti
3. The net energy cost of interval running was then calculated as follows:
EC = [ EO2 + ELa ] / d, (1)
where d is the total distance covered. EC was expressed in J m/kg using an
energy equivalent (J ml/O
) which considers the respiratory exchange ratio.
Moreover, the instantaneous P
expressed in W/kg, was obtained
multiplying EC by the running speed (expressed in m/s).
*****Figure 2 near here*****
Data Analysis
Shapiro-Wilk tests were used to check the normal distribution of data.
Measures with skewed distribution were log transformed (Ln) before analysis.
Time (baseline; R0; R90) x condition (PBC; CON) repeated measures
ANOVAs were performed to analyse temperature, HRV, and BRS.
For all metabolic variables recorded during IR sub-sessions, the mean values
of the PBC vs. CON condition were compared with Student’s t test for paired data.
Effect sizes were calculated as the mean difference standardised by the between-
subject standard deviation and interpreted according to the following thresholds:
trivial, <0.20; small, >0.20-0.60; moderate, >0.60-1.20; large, >1.20-2.00; very large,
>2.00-4.00; extremely large, >4.00 (Hopkins et al. 2009). Statistical significance was
set at p < 0.05. Post hoc tests were corrected with the Bonferroni procedure. Data
Page 12 of 33
were analysed with SPSS v22.0 (SPSS, Chicago, IL, USA). Intra-class correlation
coefficient was used to test the reliability of mean speed of both IR tests.
The mean speed maintained by the athletes during both IR sub-sessions was
2.76±0.17 m/s, with high degree of reliability between measurements, in which the
average measure ICC was 0.959 with a 95% confidence interval from 0.819
to 0.991.
*****Table 1 near here*****
Body composition and temperature
Repeated measure analysis indicated no significant differences between
conditions at baseline and after strength training (Table 2, all P>0.05). After 90 min
of recovery, a significant time x condition interaction effects was observed. Post-hoc
tests showed that, after PBC, R/H (P<0.001, d=0.78, moderate), Xc/H (P<0.001,
d=0.90, moderate), and PA (P=0.013, d=0.52, small) increased, meanwhile, hand
(P=0.000, d=-11.95, extremely large) and foot temperature (P<0.001, d=-14.19,
extremely large) decreased. From baseline to R0 the vector decreased in both PBC
and CON condition (P<0.001), meanwhile, a significant increase was observed
between R0 and R90 only after PBC (Table 2).
*****Table 2 near here*****
Cardiac autonomic regulation
ANOVAs showed a significant time main effect for all autonomic variables
investigated (P<0.05), meaning that variables changed over time in both CON and
PBC condition. In addition, mean differences and effect sizes were higher on PBC in
all cardiac autonomic regulation parameters (Table 3).
Page 13 of 33
*****Table 3 near here*****
Energy cost analysis
The metabolic data obtained from the IR are reported in Table 4. Respiratory
exchange ratio, La, and E’O
were not significantly affected by cryotherapy (0.469 <
P > 0.116; 0.63 < d > 0.15), while all other metabolic parameters were lower during
IR performed after PBC (0.006 < P > 0.000; 1.40 < d > 0.44). Heart rate was 3.5%
lower during IR performed after PBC than in the CON condition, and the same result
was observed for V’O
(~4.9%) and V’E (~6.5%). The EC measured after
cryotherapy was ~9.0% lower than after passive recovery (P<0.001, d=-1.40, large).
Figure 3 displays the EC of the athletes during IR in the two testing conditions, in
which individual differences ranged from -3.98 to -17.27%. Although the variable of
main interest in this study was EC, a comparison of P
mean values was also
performed, and analysis showed that P
was higher in CON than in PBC (~6.7%).
*****Figure 3 and Table 4 near here*****
In the present study we investigated, in rugby players, the influence of a
single session of cryotherapy performed during the 90-min of recovery between a
strength training and a high-intensity interval running sub-sessions on body
composition, temperature, and cardiac autonomic responses, and its effects on
energetic cost during the subsequent interval running. The main findings of this study
were as follows: (i) Bioelectric impedance analysis showed that strength training
affected hydration parameters and PBC enhanced recovery compared to passive rest.
(ii) PBC after strength training influenced the pattern of autonomic function
recovery, in which indexes reflecting tonic cardiac vagal outflow such as SDNN,
RMSSD, and HF power reflected moderate to large effect sizes. Furthermore,
consistent changes were observed in BRS, which is a measure of reflex cardiac vagal
Page 14 of 33
responsiveness (Piras et al. 2017; Piras et al. 2015; Piras and Gatta, 2017). (iii)
Cardiorespiratory and metabolic parameters were reduced during a single bout of IR
after PBC, indicated by lowered HR, V’O
, V’E, EC, and PMET with respect to
Bioelectrical impedance analysis
The bioelectrical impedance analysis is commonly used to monitor changes in
hydration and body composition induced by training (Piccoli et al. 1995). In our
study, the mean of the impedance vector between baseline and R0 differed in the
same way in both conditions, returning to normal when repeated 90-min later only
after PBC. An intense physical training may affect cellular membrane stability, and
passive recovery is unable to restore homeostasis (Korthuis 2011). Immediately after
strength training, we found a decrease of the phase angle in both conditions, a
situation characterised by an increase in body fluid volume, maybe due to muscle
swelling. Then, only after PBC the PA° was restored close to normohydration status.
Because the rate of fluid movement across the microcirculation initially exceeds the
drainage capacity of the lymphatic system, interstitial fluid volume can almost
double within 15 min of the onset of intense rhythmic exercise (Korthuis 2011).
Intense training could induce muscle damage and subsequent inflammation indicated
by muscle soreness, swelling, and prolonged loss of muscle function. It has been
already demonstrated that PBC stimulated physiological reactions of an organism
which result in analgesic, anti-swelling, antalgic immune and circulatory system
reactions and then could improve recovery after muscle injury from muscular trauma
(Ferreira-Junior et al. 2015). A possible reason for these results may be related to a
decrease in core, muscle, and skin temperatures after cryotherapy exposure (Bleakley
et al. 2014). This physiological response may lead to increased vasoconstriction,
Page 15 of 33
reducing blood vessel permeability and thus decreasing the cellular inflammatory
process (Ferreira-Junior et al. 2015; Hausswirth et al. 2011).
In our study, temperature decreased after cryotherapy exposure. We are aware
that the lack of muscle and core temperatures is a limitation because such
measurements may have provided useful information on the body heat variations
during each recovery procedure. However, skin temperature of hand and foot in the
present study dropped respectively 3.4±0.8 and 4.2±0.6 °C immediately after PBC
compared to the basal level.
Autonomic responses
Regardless of the great sympathetic response necessary to support maximal
strength production rates during exercise, we demonstrated that autonomic function
recovered fully at the cardiac level within 90-min in both CON and PBC conditions.
Furthermore, we found higher effect sizes after cold treatment in all cardiac
autonomic regulation parameters, mainly on vagal-mediated HRV and BRS indices
(Table 3). Schaal et al. (2013), examining the influence of WBC during recovery
between two training sessions, showed that swimmers were able to repeat the same
maximal workload with similar autonomic, metabolic, and subjective responses.
Hausswirt et al. (2013) determined whether PBC was as effective as a WBC in
stimulating a parasympathetic activation. Whatever the cryotherapy technique used,
results showed that a single 3-min cryostimulation induced a strong autonomic
response. Same results were found by Westerlund et al. (2006) on how an extreme
cold air exposure influences cardiac autonomic regulation and its adaptation effects
on healthy women.
Perhaps, the high level of training and endurance at high loads of our athletes
resulted in an immediate recovery of the cardiac autonomic parameters. Therefore,
Page 16 of 33
parasympathetic reactivation after maximal exercise was not a limiting factor to
recovery but could have affected the subsequent high intensity exercise capacity,
seen that a link was found between the magnitude of parasympathetic reactivation
and the cardiorespiratory and metabolic parameters recorded during subsequent
interval running after PBC compared to passive recovery.
Oxygen uptake
Cryotherapy had induced a reduction of the cardiorespiratory and metabolic
parameters recorded during IR. Heart rate was about 3.5% lower after PBC than
CON condition, and the same result was observed for V’O
(~4.9%), V’E (~6.5%),
EC (~9.0%) and PMET (~6.7%). These results are in agreement with those of Krüger
et al. (2015) who found, after 3-min of WBC at -110°C, lowered values of heart rate,
, rate of perceived exertion, and a higher muscle oxygenation during running at
submaximal intensity. The beneficial effects of cold treatment are commonly
believed to be associated with rapid reduction in core temperature, which in turn may
reduce fatigue associated with hyperthermia and suppressed muscle blood flow and
metabolic activity (Holmes and Willoughby 2016). Schmidt and Bruck (1981)
claimed that decreasing the body temperature at the onset of exercise, the critical
environmental heat stress limits for exercising would decrease. This may result in
performance enhancement of both endurance time and increased work rate (Ferretti
et al. 1995). Metabolic load was reduced during running after PBC, indicated by
lower V’O
, energy cost, and metabolic power. We observed an average additional
cost of 0.34 J/kg/m during running after passive recovery. Reduced submaximal
suggests that running after cold treatment seems somewhat less energy
demanding than after passive recovery, with less effort needed to complete the
intermittent exercise or a lower V’O
of the passive muscles due to peripheral
Page 17 of 33
vasoconstriction and therefore lower blood and oxygen directed to non-working
musculature (Krüger et al. 2015). Ferretti et al. (1995) found that the minimum
mechanical power necessary to elicit V’O
max during cycling is about 21 W lower at
31°C than at 36°C. Stanley et al. (2014) found that V’O
kinetics and muscle oxygen
utilization were reduced after cold water immersion compared with passive recovery.
Schaal et al. (2013) found and equal or greater VO
on WBC in
comparison to passive recovery, where swimmers were able to repeat the same
maximal workload with similar autonomic, metabolic, and subjective responses.
Conversely, Drust et al. (2000) found no significant differences for the oxygen
consumption or heart rate under normal (20°C), heated (26°C) or pre-cooled (cold
shower at 24°C) conditions during intermittent exercise in soccer players, although
there was a tendency for heart rate to be lower during the pre-cooled condition.
These data therefore suggest that cold treatment might improve oxygen uptake
efficiency at muscle level with respect to passive recovery, possibly through different
mechanisms. First, cooling results in reduced muscle perfusion and edema formation,
all factors that reduce the transit distance between capillaries and muscle fibers
facilitating oxygen delivery to the muscle cells (Ihsan et al. 2013). Second, decreased
peripheral blood flow may increase central blood volume and enhance blood delivery
to the working muscles (Lee and Haymes 1995), resulting in a greater contribution of
the aerobic system to energy supply, combined with the low level of blood lactate
that we have found at the end of the IR effort. Third, the increase in muscle blood
flow redistribution and reduction in maximal heart rate, together with the left shift of
the oxygen dissociation curve known to occur when temperature is decreased, can
explain the observed lower V’O
during running (Ferretti et al. 1995).
Page 18 of 33
In conclusion, cryotherapy enhances recovery after a single strength training
sub-session, while during the subsequent interval running it shows a reduction in
cardiorespiratory and metabolic parameters. These findings agree with the suggested
mechanisms by which cooling between successive workouts has been recommended
to enhance muscle recovery and as such it can be used in sports. Therefore, from a
practical perspective, cryotherapy may be used in those athletes who compete or train
more than once in the same day (i.e. soccer, rugby) to improve recovery between
successive trainings or competitions.
Conflict of Interests: The author(s) declare(s) that there is no conflict of interests
regarding the publication of this article.
Barnett, A. 2006. Using recovery modalities between training sessions in elite
athletes. Sports Med. 36(9), 781–796.
Bleakley, C. M., Bieuzen, F., Davison, G. W., and Costello, J. T. 2014. Whole-body
cryotherapy: empirical evidence and theoretical perspectives. Open Access J.
Sports Med. 5, 25–36.
Brown, L. E., and National Strength & Conditioning Association (U.S.). 2007.
Strength training, Human Kinetics.
Brzycki, M. 1993. Strength Testing-Predicting a One-Rep Max from Reps-to-
Fatigue. JOPERD, 64(1), 88–90.
Camm, A., Malik, M., Bigger, J., and Günter, B. 1996. Task force of the European
Society of Cardiology and the North American Society of Pacing and
Electrophysiology. Heart rate variability: standards of measurement,
Page 19 of 33
physiological interpretation and clinical use. Circulation, 93(5), 1043–1065.
Campa, F., and Toselli, S. 2018. Bioimpedance Vector Analysis of Elite, Sub-Elite
and Low-Level Male Volleyball Players. Int. J. Sports Physiol. Perform. 1–13.
Denadai, B. S., Ortiz, M. J., Greco, C. C., and de Mello, M. T. 2006. Interval training
at 95% and 100% of the velocity at V O 2 max : effects on aerobic physiological
indexes and running performance. Appl. Physiol. Nutr. Metab. 31(6), 737–743.
Di Prampero, P. E., and Ferretti, G. 1999. The energetics of anaerobic muscle
metabolism: A reappraisal of older and recent concepts. Respir. Physiol. 118(2–
3), 103–115.
Drust, B., Cable, N. T., and Reilly, T. 2000. Investigation of the effects of the pre-
cooling on the physiological responses to soccer-specific intermittent exercise.
Eur. J. Appl. Physiol. Occup. Physiol. 81(1–2), 11–17.
Ferreira-Junior, J. B., Bottaro, M., Vieira, A., Siqueira, A. F., Vieira, C. A., Durigan,
J. L. Q., et al. G. 2015. One session of partial-body cryotherapy (-110°C)
improves muscle damage recovery. Scand. J. Med. Sci. Sports, 25(5), e524–
Ferreira-Junior, J. B., Bottaro, M., Vieira, C. A., Soares, S. R. S., Vieira, A., Cleto,
V. A., et al. 2014. Effects of Partial-body Cryotherapy ( − 110 ° C ) on Muscle
Recovery between High-intensity Exercise Bouts. Int. J. Sports Med. 14(35),
Ferretti, G., Binzoni, T., Hulo, N., Kayser, B., Thomet, J. M., and Cerretelli, P. 1995.
Kinetics of oxygen consumption during maximal exercise at different muscle
temperatures. Respir. Physiol. 102(2–3), 261–268.
Page 20 of 33
Fyfe, J. J., and Loenneke, J. P. 2018. Interpreting Adaptation to Concurrent
Compared with Single-Mode Exercise Training: Some Methodological
Considerations. Sports Med. Springer International Publishing.
Hausswirth, C., Louis, J., Bieuzen, F., Pournot, H., Fournier, J., Filliard, J. R., et al.
2011. Effects of whole-body cryotherapy vs. far-infrared vs. passive modalities
on recovery from exercise-induced muscle damage in highly-trained runners.
PLoS one, 6(12), e27749.
Hausswirth, C., Schaal, K., Le Meur, Y., Bieuzen, F., Filliard, J. R., Volondat, M., et
al. 2013. Parasympathetic Activity and Blood Catecholamine Responses
Following a Single Partial-Body Cryostimulation and a Whole-Body
Cryostimulation. PLoS one, 8(8).
Holmes, M., and Willoughby, D. S. 2016. The Effectiveness of Whole Body
Cryotherapy Compared to Cold Water Immersion: Implications for Sport and
Exercise Recovery. International Journal of Kinesiology and Sports Science,
Hopkins, W. G., Marshall, S. W., Batterham, A. M., and Hanin, J. 2009. Progressive
statistics for studies in sports medicine and exercise science. Med. Sci. Sports
Ihsan, M., Watson, G., Lipski, M., and Abbiss, C. R. 2013. Influence of Postexercise
Cooling on Muscle Oxygénation and Blood Volume Changes. Med. Sci. Sports
Exerc. 45(5), 876–882.
Korthuis, R. J. 2011. Microvascular, Fluid and Solute Exchange in Skeletal Muscle.
In Skeletal Muscle Circulation (pp. 1–144). Morgan and Claypool Life
Kotler, D. P., Burastero, S., Wang, J., Pierson Jr, R., and Pierson, R. N. 1996.
Page 21 of 33
Prediction of body cell mass, fat-free mass, and total body water with
bioelectrical impedance analysis: effects of race, sex, and disease. Am. J. Clin.
Nutr. 64(3 Suppl), 489S–497S.
Krüger, M., de Mareés, M., Dittmar, K.-H., Sperlich, B., and Mester, J. 2015. Whole-
Body Cryotherapy’s Enhancement of Acute Recovery of Running Performance
in Well-Trained Athletes. Int. J. Sports Physiol. Perform. 10(5), 605–612.
Lee, D. T., and Haymes, E. M. 1995. Exercise duration and thermoregulatory
responses after whole body precooling. J. Appl. Physiol. 79(6), 1971–6.
Leveritt, M., Abernethy, P. J., Barry, B. K., and Logan, P. A. 1999. Concurrent
strength and endurance training. A review. Sports Med. 28(6), 413–427.
Lukaski, H. C. 2013. Evolution of bioimpedance: a circuitous journey from
estimation of physiological function to assessment of body composition and a
return to clinical research. Eur. J. Clin. Nutr. 67 Suppl 1(S1), S2-9.
Micheli, M. L., Pagani, L., Marella, M., Gulisano, M., Piccoli, A., Angelini, F., et al.
2014. Bioimpedance and impedance vector patterns as predictors of league level
in male soccer players. Int. J. Sports Physiol. Perform. 9(3), 532–539.
Pagani, M., Lombardi, F., Guzzetti, S., Rimoldi, O., Furlan, R., Pizzinelli, P., et al.
1986. Power spectral analysis of heart rate and arterial pressure variabilities as a
marker of sympatho-vagal interaction in man and conscious dog. Circulation
Research, 59(2), 178–193.
Piccoli, A., Nigrelli, S., Caberlotto, A., Bottazzo, S., Rossi, B., Pillon, L., et al. 1995.
Bivariate normal values of the bioelectrical impedance vector in adult and
elderly populations. Am. J. Clin. Nutr. 61(2), 269–270.
Page 22 of 33
Piras, A., Cortesi, M., Campa, F., Perazzolo, M., and Gatta, G. 2017. Recovery time
profiling after short-, middle- and long-distance swimming performance. J.
Strength Cond. Res.
Piras, A., and Gatta, G. 2017. Evaluation of the Effectiveness of Compression
Garments on Autonomic Nervous System Recovery After Exercise. J. Strength
Cond. Res. 31(6), 1636–1643.
Piras, A., Persiani, M., Damiani, N., Perazzolo, M., and Raffi, M. 2015. Peripheral
heart action (PHA) training as a valid substitute to high intensity interval
training to improve resting cardiovascular changes and autonomic adaptation.
Eur. J. Appl. Physiol. 115(4), 763–773.
Podbielska, H., Stręk, W., and Biały, D. (Eds.). 2006. Whole body cryotherapy.
Kriotechnika Medyczna.
Sabag, A., Najafi, A., Michael, S., Esgin, T., Halaki, M., and Hackett, D. 2018. The
compatibility of concurrent high intensity interval training and resistance
training for muscular strength and hypertrophy: a systematic review and meta-
analysis. J. Sports Sci. 1–12.
Schaal, K., Le Meur, Y., Bieuzen, F., Petit, O., Hellard, P., Toussaint, J.-F., et al.
2013. Effect of recovery mode on postexercise vagal reactivation in elite
synchronized swimmers. Appl. Physiol. Nutr. Metab. 38(2), 126–133.
Schmidt, V., and Brück, K. 1981. Effect of a precooling maneuver on body
temperature and exercise performance. J. Appl. Physiol. (Bethesda, Md. : 1985),
50, 772–778.
Selberg, O., and Selberg, D. 2002. Norms and correlates of bioimpedance phase
angle in healthy human subjects, hospitalized patients, and patients with liver
Page 23 of 33
cirrhosis. Eur. J. Appl. Physiol. 86(6), 509–516.
Stanley, J., Peake, J. M., Coombes, J. S., and Buchheit, M. 2014. Central and
peripheral adjustments during high-intensity exercise following cold water
immersion. Eur. J. Appl. Physiol. 114(1), 147–163.
Westerlund, T., Uusitalo, A., Smolander, J., and Mikkelsson, M. 2006. Heart rate
variability in women exposed to very cold air (-110°C) during whole-body
cryotherapy. J. Therm. Biol. 31(4), 342–346.
Yoon, B. K., Kravitz, L., and Robergs, R. 2007. V’O2max, protocol duration, and the
V’O2 plateau. Med. Sci. Sports Exerc. 39(7), 1186–1192.
Zamparo, P., Bolomini, F., Nardello, F., and Beato, M. 2015. Energetics (and
kinematics) of short shuttle runs. Eur. J. Appl. Physiol. 115(9), 1985–1994.
Page 24 of 33
Table 1. Anthropometric, training (1-
RM) and physiological parameters
Mean SD
Weight (Kg)
91.94 11.36
Height (m)
BMI (kg/m
27.99 2.58
Training week (h)
8.50 1.80
Experience (yr)
max (ml/kg/min)
(95%) (km/h)
13.11 0.78
(45%) (km/h)
6.56 0.46
Bench Press (kg)
Squat (kg)
155.56 21.63
Barbell Row (kg)
Deadlift (kg)
142.11 26.04
Overhead Press (kg)
Page 25 of 33
Table 2. Mean
± SD of body
Abbreviations: FM, fat mass; FFM, fat free mass; R/H, resistance divided by body height; Xc/H, reactance divided by body height;
PA, phase angle.
*Significant time x condition interaction effect (P<0.05) after 90 min of recovery.
Baseline R0 R90
FM (kg) 15.35±5.39 16.42±5.14 13.84±5.25 13.42±4.68 15.84±4.53 15.43±4.58
FFM (Kg) 75.50±7.84 75.32±7.15
77.29±8.54 78.32±7.90
76.92±10.38 75.10±8.65
R/H (Ohm/m) 218.99±22.18 220.78±19.46 211.68±22.61
Xc/H (Ohm/m) 31.52±3.76 31.54±3.40 29.38±3.48 28.78±3.55 30.89±4.24 32.19±4.64*
PA (degrees) 8.20±0.60 8.13±0.52
7.90±0.60 7.90±0.62
8.10±0.34 8.23±0.74*
Head temperature (°C) 36.38±0.40 36.38±0.28 36.20±0.28 36.06±0.35 36.46±0.33 35.76±0.83
Hand temperature (°C) 33.94±2.51 33.40±2.64 35.21±0.59 35.24±0.62 34.94±0.52 30.03±0.44*
Foot temperature (°C) 34.45±1.87 34.17±1.67
35.03±0.35 34.73±0.47
34.96±0.41 30.10±0.51*
Page 26 of 33
Page 27 of 33
Table 3. Mean differences (with Cohen’s d) of autonomic nervous system parameters after recovery (R0 vs. R90) in both conditions
LF/HF LF (nu) HF (nu) HR (bpm) SDNN (ms) RMSSD (ms) BRS (ms/mmHg)
CON -1.08 (-0.75) -11.77 (-0.72) 11.81 (0.72) -8.75 (-1.15) 23.36 (0.95) 17.41 (1.01) 5.86 (0.78)
PBC -1.19 (-0.95) -12.11 (-0.73) 12.14 (0.73) -9.20 (-1.21) 24.50 (1.00) 21.13 (1.34) 9.41 (0.96)
Abbreviations: LF, low frequency; HF, high frequency; HR, heart rate; RMSSD, root mean square of standard deviations;
BRS, baroreflex sensitivity.
Page 28 of 33
Table 4. Physiological data (mean ± SD) collected during the IR sub-sessions
CON PBC diff % P Cohen's d
35.94±3.81 34.23±3.12 -4.9 0.006* -0.49
VE (l/min) 88.75±12.44 83.41±11.91 -6.5 0.005* -0.44
HR (bpm) 142.62±10.98
137.71±9.76 -3.5 0.001* -0.47
RER 0.95±0.05 0.93±0.05 -2.3 0.469 -0.38
(mmol/l) 2.02±0.43 2.30±0.45 9.9 0.116 0.63
(mmol/l) 2.67±0.65 2.89±0.69 4.4 0.335 0.33
(ml/kg(min) 306.23±42.58
2.0 0.348 0.15
EC (J/Kg/m) 4.11±0.29 3.77±0.18 -9.0 0.000* -1.40
Pmet (W/Kg) 11.28±1.25 10.57±1.02 -6.7 0.006* -0.62
Abbreviations: V′O
, oxygen uptake; V′E, minute ventilation; HR, heart rate; RER,
respiratory exchange ratio; La, blood lactate concentration (pre- and post-IR); E′O
net energy expenditure derived from aerobic energy sources; EC net energy cost;
, metabolic power.
* Significant differences between conditions (P<0.05).
Page 29 of 33
Figure legends
Figure. 1 Graphical overview of the testing protocol with the timeline of events.
Exercise bout 1 (strength training), exercise bout 2 (IR), start of recovery (R0), end
of recovery (R90), heart rate variability (HRV), baroreflex sensitivity (BRS),
temperature (T°), bioelectric impedance (BIA), partial-body cryotherapy (PBC),
control condition (CON), energy cost (EC), minute ventilation (V’E), heart rate
(HR), oxygen consumption (V’O2), metabolic power (P
Figure. 2 Representative profile of an athlete’s oxygen uptake as a function of time
(sec) during IR in both CON (black) and PBC (grey) conditions. V′O2 increases
during each bout of exercise at about 95%V’O2max and decreases during active
recovery at about 45%V’O2max.
Figure. 3 Individual differences (9 subjects) in energetic cost (EC) between control
(CON) and partial-body cryotherapy (PBC) conditions.
Page 30 of 33
Figure. 1 Graphical overview of the testing protocol with the timeline of events. Exercise bout 1 (strength
training), exercise bout 2 (IR), start of recovery (R0), end of recovery (R90), heart rate variability (HRV),
baroreflex sensitivity (BRS), temperature (T°), bioelectric impedance (BIA), partial-
body cryotherapy (PBC),
control condition (CON), energy cost (EC), minute ventilation (V’E), heart rate (HR), oxygen consumption
(V’O2), metabolic power (PMET).
101x31mm (300 x 300 DPI)
Page 31 of 33
Figure. 2 Representative profile of an athlete’s oxygen uptake as a function of time (sec) during IR in both
CON (black) and PBC (grey) conditions. V′O2 increases during each bout of exercise at about 95%V’O2max
and decreases during active recovery at about 45%V’O2max.
80x49mm (300 x 300 DPI)
Page 32 of 33
Figure. 3 Individual differences (9 subjects) in energetic cost (EC) between control (CON) and partial-body
cryotherapy (PBC) conditions.
65x49mm (300 x 300 DPI)
Page 33 of 33
... HRV is the tool used to analyze the cardiac autonomic responses in combination with the baroreflex sensitivity (BRS), which is a reflex that adapts the heart period in response to variations in systolic blood pressure. These parameters have been used to evaluate the different adaptations to exercise and the recovery times after exercise [11][12][13][14][15]. Regardless of several research and medical applications, few studies have investigated the MENS effect before or after endurance exercise [7,16]. ...
... HRV is the tool used to investigate the cardiac autonomic responses in combination with the baroreflex sensitivity, which is a reflex that adapts the heart period in response to variations in systolic blood pressure. These parameters have been used to evaluate the different adaptations to exercise and the recovery times after exercise [11][12][13][14]. With a transition from exercise to passive recovery, there is a loss of central command and activation of the arterial baroreflex, resulting in a decrease in heart rate toward its pre-exercise level [45]. ...
Full-text available
Microcurrent electrical neuromuscular stimulation (MENS) is believed to alter blood flow, increasing cutaneous blood perfusion, with vasodilation and hyperemia. According to these physiological mechanisms, we investigated the short-term effects of MENS on constant-load exercise and the subsequent recovery process. Ten healthy subjects performed, on separate days, constant-load cycling, which was preceded and followed by active or inactive stimulation to the right quadricep. Blood lactate, pulmonary oxygen, and muscle deoxyhemoglobin on-transition kinetics were recorded. Hemodynamic parameters, heart rate variability, and baroreflex sensitivity were collected and used as a tool to investigate the recovery process. Microcurrent stimulation caused a faster de-oxyhemoglobin (4.43 ± 0.5 vs. 5.80 ± 0.5 s) and a slower VO2 (25.19 ± 2.1 vs. 21.94 ± 1.3 s) on-kinetics during cycling, with higher lactate levels immediately after treatments executed before exercise (1.55 ± 0.1 vs. 1.40 ± 0.1 mmol/L) and after exercise (2.15 ± 0.1 vs. 1.79 ± 0.1 mmol/L). In conclusion, MENS applied before exercise produced an increase in oxygen extraction at muscle microvascula-ture. In contrast, MENS applied after exercise improved recovery, with the sympathovagal balance shifted toward a state of parasympathetic predominance. MENS also caused higher lactate values, which may be due to the magnitude of the muscular stress by both manual treatment and electrical stimulation than control condition in which the muscle received only a manual treatment.
... Furthermore, WBC has been demonstrated to immediately increase and decrease blood pressure and heart rate respectively (Lubkowska & Szygula, 2010). More recent findings have supported these observations in reporting reduced heart rate and ventilation during an interval running session post-WBC compared to passive recovery (Piras et al., 2019). ...
Full-text available
Whilst Whole Body Cryotherapy (WBC) has become an emerging tool for sport and exercise recovery, its overall efficacy remains contentious. This thesis addressed a variety of issues concerning the practice. Firstly, the impact of single WBC interventions for treating exercise-induced muscle damage (EIMD) is unclear. Secondly, the influence of inter-individual factors on WBC outcomes post-exercise remains an under-investigated area. Therefore the first main study explored the effects of age and body fat content on responses to WBC following downhill running, a commonly utilised eccentric exercise model for inducing muscle damage. WBC participants underwent cryotherapy (3 minutes, −120°C) one hour post- downhill run and control (CON) participants passively recovered (20°C). Despite the presence of EIMD, WBC significantly blunted (p=0.04) the decrease in muscle torque 24 hours after the downhill run. This response was significantly influenced by age, with young participants (<40 years) retaining their muscle strength more than older participants (≥45 years). WBC may therefore attenuate EIMD and benefit muscle strength recovery following eccentrically biased exercise, particularly for young males. A subsequent downhill run study investigated the influence of WBC timing post-exercise, a factor that could clarify optimal treatment usage. An additional objective was to compare the effects of WBC with cold water immersions (CWI) since the verdict regarding which cold modality is superior for recovery remains an on-going area of controversy. It was revealed that WBC 4 hours post-exercise was ineffective in treating EIMD markers, so applying WBC within one hour after exercise may be preferable to delaying by several hours. However, WBC was no more effective than CWI, meaning that the cost vs. reward implications of WBC treatments would need further reviewing. Finally, the implications of repetitive WBC during training programmes require further evaluation due to the possibility of repetitive cold interfering with long term adaptations. The final study investigated the impact of two weekly WBC treatments on adaptations to a 6 week strength and endurance training programme. It was found that WBC participants significantly improved their muscle strength comparatively to the CON group. However WBC did not improve their jump height (p=0.23) in contrast to the CON group (p=0.01). In conclusion, repetitive WBC does not appear to blunt strength training adaptations, although there may be an interference effect in the development of explosive power.
... The study has shown that PBC (−180°C, 3 min) can significantly lower skin temperature (Ts) and core temperature (Tc; Hoshikawa et al., 2019). Another study reported that PBC could lower heart rate and boost post-training recovery (Piras et al., 2019). However, the physiological profile of PBC intervention after highintensity intervals training in hot and humid environments has not been well studied. ...
Full-text available
This research aims to describe and compare the effects of partial-body cryotherapy (PBC) and cold-water immersion (CWI) on the physiological responses of soccer players after cycling in a hot and humid environment. Sixteen elite soccer players participated in three experiments, and received CWI (13°C for 15 min), PBC (110°C−140°C for 3 min), and CON (room temperature: 21°C ± 2°C), respectively, after aerobic and anaerobic cycling in a hot and humid environment (temperature: 35°C–38°C; humidity: 60%–70%). Heart rate (HR), blood lactate (BLa-), perfusion index (PI), oxygen saturation (SaO 2 ), core temperature (Tc), skin temperature (Ts), and rating of perceived exertion (RPE) were assessed at baseline and through 20 min (5-min intervals). HR was lower in CWI than CON after 20 min ( p < .05). SaO 2 was higher in CWI than PBC and CON between 10 and 20 min ( p < .05). Tc was lower from CWI and PBC than CON between 10 and 20 min ( p < .05). Ts was lower in PBC than CWI between 15 and 20 min ( p < .05). RPE was lower in PBC than CON 20 min after the exercise ( p < .05). No main group differences for BLa- and PI were observed. The physiological effects of PBC are generally similar to CWI. Compared with CON, both CWI and PBC could promote the recovery of physiological indexes within 20 min of exercise in a hot and humid environment. However, PBC can lead to a decrease in SaO 2 due to excessive nitrogen inhalation.
... During visit 1, we recorded an incremental test to exhaustion on a cycle-ergometer (H-300-R Lode), necessary to individualize the workload for the succeeding recording sessions through the detection of ventilatory threshold (VT) and peak oxygen consumption (VO2peak). Participants performed 5 min of warm-up cycling at 50 W, after which the work rate, starting at 80 W, was increased by 20 W/min until the volitional exhaustion [17,18]. Participants cycled at 70-80 rpm and this pedal rate was reproduced in subsequent constant-load exercises. ...
Full-text available
Pulsed electromagnetic fields (PEMFs) are used as non-invasive tools to enhance micro-circulation and tissue oxygenation, with a modulatory influence on the microvasculature. This study aimed to measure the acute effect of PEMF on muscle oxygenation and its influence on pulmonary oxygen kinetics during exercise. Eighteen male cyclists performed, on different days, a constant load exercise in both active (ON) and inactive (OFF) PEMF stimulations while deoxyhemoglo-bin and pulmonary oxygen kinetics, total oxygenation index, and blood lactate were collected. PEMF enhanced muscle oxygenation, with higher values of deoxyhemoglobin both at the primary component and at the steady-state level. Moreover, PEMF accelerated deoxyhemoglobin on-transition kinetic, with a shorter time delay, time constant, and mean response time than the OFF condition. Lactate concentration was higher during stimulation. No differences were found for total oxygenation index and pulmonary oxygen kinetics. Local application of a precise PEMF stimulation can increase the rate of the muscle O2 extraction and utilization. These changes were not accompanied by faster oxygen kinetics, reduced oxygen slow component, or reduced blood lactate level. It seems that oxygen consumption is more influenced by exercise involving large muscle mass like cycling, whereas PEMF might only act at the local level.
... Indices of cardiac vagal outflow, that is SDNN, RMSSD and HF power, were clearly different in swimmers as compared to sedentary counterparts. Furthermore, differences were observed in BRS, which is a measure of reflex cardiac vagal responsiveness [17][18][19][20]. Loimaala et al. [10] suggest that, to obtain a clinically significant increase in HRV and BRS, exercise training should be practiced consistently for many years. ...
The aim of the present investigation was to assess the effect of long-term recreational swimming training on the cardiac autonomic responses in the healthy population. 70 habitual recreational swimmers (48.6±14.3 yrs.) and 60 sedentary adults (51.5±10.4 yrs.) were recruited. Arterial blood pressure was recorded with participants in supine position for 10 min, and the last 5 min were used to assess heart rate variability, baroreflex sensitivity, and hemodynamic analysis. The analysis of the questionnaire showed that the swimmers had practiced swimming for a mean of 14 years and 207 min/week. No difference was detected for body mass index between groups. Heart rate variability showed significant differences between groups both in the time and frequency domain analysis. We also found significant differences for baroreflex sensitivity. At rest, cardiac output and stroke volume were higher, whereas, heart rate, mean arterial pressure and total peripheral resistances were lower in the swimmers than in the sedentary subjects. Since heart rate variability measures are independent predictors of mortality, the present findings suggest that habitual recreational swimming may be protective against sudden cardiovascular events and, more in general, have a positive impact on cardiovascular health.
... The search for the optimal physical condition and the monitoring of physiological parameters in athletes have always been topics of study for researchers, trainers and coaches [1,2]. Water immersion has been used in both sports and rehabilitation for several decades and its effects on several physiological parameters, including inflammatory and metabolic markers, blood flow and nerve transmission are well-documented in the literature [3][4][5][6][7][8]. ...
Full-text available
Muscle contractile properties in clinical practice are often measured using either subjective scales or high-cost, inaccessible equipment. In this randomised cross-over study, we aimed to explore the use of tensiomyography (TMG) to assess changes in muscle contractile properties after cold-and warm-water immersion. The muscle contractile properties of the biceps femoris (BF) were assessed using TMG in 12 healthy active men (mean age 23 ± 3 years, Body Mass Index 22.9 ± 1.3 kg/m 2) before and after a 20-min warm-or cold-water immersion over a period of 40 min. Muscle displacement (Dm) and contraction time (Tc) were registered as the main variables of the study. There was a significant condition by time interaction for Dm (p < 0.01). Post hoc analysis showed that, compared to the baseline, there was an increase in Dm 40 min after warm-water immersion (p < 0.01) and a decrease at 10 min after cold-water immersion (p < 0.01). No significant effect was found for Tc. Our results indicate that muscle contractile properties are affected by water temperature and time after the immersion; therefore, these factors should be taken into account when water-immersion is used as a recovery strategy.
Full-text available
Recovery after exercise is a crucial key in preventing muscle injures and in speeding up processes to return at the homeostasis level. There are several ways of developing a recovery strategy with the use of different kinds of traditional and up-to date techniques. The use of cold has traditionally been used after physical exercise for recovery purposes. In the recent years, the use of whole-body cryotherapy/cryostimulation (an extreme cold stimulation lasting 1-4 min and given in a cold room at a temperature comprised from -60 to -195°C) has tremendously increased for such purposes. However, there are controversies about the benefits that the use of this technique may provide. Therefore, this paper describes what is whole body cryotherapy/cryostimulation, reviews and debates the benefits that its use may provide, presents practical considerations and applications, and emphasizes the need of customization depending on the context, the purpose, and the subject characteristics. This review is written by international experts from the working group on whole body cryotherapy/cryostimulation from the International Institute of Refrigeration.
Background: Muscle injuries represent a great part of athletic injuries. The repairing of skeletal muscle after injury is highly influenced by its regenerative response that may be affected by thermotherapy. Aim: This research examined the consequence of heat therapy on muscle recovery after skeletal muscle injury in rats. Materials and methods: Forty-five male adult albino rats were classified into three groups: control, cardiotoxin-injected without heat (nonheating group), and cardiotoxin-injected with heat (heating group). Muscle injury was caused by the injection of cardiotoxin intramuscularly into the tibialis anterior muscles. Heating treatment (40°C for 20 min) was started immediately after the injury. Subsequent observations were performed at day 1, 3, and 7 after injury, including histological imaging and vimentin immunostaining expression. Results: In the heating group, the regenerating myotubes, having two or more central nuclei, first looked at 3 days after muscle injury, while in the nonheating group, the regenerating fibers were first observed at 7 days after muscle injury. Immunohistochemically, the vimentin reactions were absent in control muscle fibers but were identified in regenerating muscle fiber of the heating group earlier than in the nonheating group. Conclusion: Starting of heat treatment immediately after muscle injury promoted the regeneration of muscle fibers.
Full-text available
Incorporating both endurance and resistance training into an exercise regime is termed concurrent training. While there is evidence that concurrent training can attenuate resistance training-induced improvements in maximal strength and muscle hypertrophy, research findings are often equivocal, with some suggesting short-term concurrent training may instead further enhance muscle hypertrophy versus resistance training alone. These observations have questioned the validity of the purported ‘interference effect’ on muscle hypertrophy with concurrent versus single-mode resistance training. This article aims to highlight some methodological considerations when interpreting the concurrent training literature, and, in particular, the degree of changes in strength and muscle hypertrophy observed with concurrent versus single-mode resistance training. Individual training status clearly influences the relative magnitude and specificity of both training adaptation and post-exercise molecular responses in skeletal muscle. The training status of participants is therefore likely a key modulator of the degree of adaptation and interference seen with concurrent training interventions. The divergent magnitudes of strength gain versus muscle hypertrophy induced by resistance training also suggests most concurrent training studies are likely to observe more substantial changes in (and in turn, any potential interference to) strength compared with muscle hypertrophy. Both the specificity and sensitivity of measures used to assess training-induced changes in strength and muscle hypertrophy also likely influence the interpretation of concurrent training outcomes. Finally, the relative importance of any modulation of hypertrophic versus strength adaptation with concurrent training should be considered in context with the relevance of training-induced changes in these variables for enhancing athletic performance and/or functional capacity. Taken together, these observations suggest that aside from various training-related factors, additional non-training-related variables, including participant training status and the measures used to assess changes in strength and muscle hypertrophy, are important considerations when interpreting the outcomes of concurrent training interventions.
Full-text available
The energy cost of shuttle running (C netSR), over distances of 10-20 m, was reported to increase with the shuttle speed and to decrease with the shuttle distance. The aims of this study were to assess C netSR over a shorter distance (5 m), at different speeds, and to estimate the energy cost based on a simple kinematic analysis (C netK). Ten subjects (six basketball players, BP; four non-basketball players, NBP) performed ten shuttle runs (SR) with 30 s of passive recovery in-between, over a distance of 5 + 5 m (with a 180° change of direction); these experiments were repeated at different speeds (range 2-3.5 m s(-1)). The values of average (v mean) and maximal (v max) speed during each run were determined by means of kinematic analysis and C netK was calculated as: 0.96[Formula: see text]. C netSR was calculated based on data of oxygen uptake, blood lactate concentration and distance covered. The relationships between C (J m(-1) kg(-1)) and v (m(.)s(-1)) are well described by C netK (all subjects) = 11.76v - 13.09, R (2) = 0.853; C netSR (BP) = 11.94v - 12.82, R (2) = 0.636; and C netSR (NBP) = 14.09v - 14.53, R (2) = 0.738. Hence C netSR ≈ C netK in BP, whereas C netSR > C netK in NBP (un-familiar with this specific motor task). The calculations proposed in this study allow to estimate C of short SR based on simple measures of v max and can be utilized to develop training protocols in basketball as well as in other team sports (characterized by repeated sprints over short distances).
The purpose of this systematic review and meta-analysis is to assess the effect of concurrent high intensity interval training (HIIT) and resistance training (RT) on strength and hypertrophy. Five electronic databases were searched using terms related to HIIT, RT, and concurrent training. Effect size (ES), calculated as standardised differences in the means, were used to examine the effect of concurrent HIIT and RT compared to RT alone on muscle strength and hypertrophy. Sub-analyses were performed to assess region-specific strength and hypertrophy, HIIT modality (cycling versus running), and inter-modal rest responses. Compared to RT alone, concurrent HIIT and RT led to similar changes in muscle hypertrophy and upper body strength. Concurrent HIIT and RT resulted in a lower increase in lower body strength compared to RT alone (ES = −0.248, p = 0.049). Sub analyses showed a trend for lower body strength to be negatively affected by cycling HIIT (ES = −0.377, p = 0.074) and not running (ES = −0.176, p = 0.261). Data suggests concurrent HIIT and RT does not negatively impact hypertrophy or upper body strength, and that any possible negative effect on lower body strength may be ameliorated by incorporating running based HIIT and longer inter-modal rest periods.
Purpose: The aim of this study was to establish a specific players profile on body composition (BC) parametres and to provide a data set of bioelectric impedances (BI) values for male volleyball players. Methods: The study included 201 athletes (age: 26.1±5.4 yr, height: 191.9±9.7 cm, weight: 86.8±10.8 kg) registered in the Italian volleyball divisions. The athletes were divided into 3 groups: the élite group constituted of 75 players participating in the first (Super Lega) division. The sub-élite group included 65 athletes performing in the second (Serie A2) division, and the low-level group included 61 players participating in the third (Serie B) division. Bioelectric impedance, body weight and height of the athletes were measured in the second half of the competitive season. In addition, bioelectrical-impedance vector analysis was performed. Results: The élite group showed a greater amount of fat free mass (FFM) and total body water (TBW), and a lower fat mass (FM) compared to the sub-élite group (P<0.05). In addition, the élite players were taller, heavier, and with a higher FFM, FM, TBW and body cellular mass than the low-level athletes (P<0.05). Finally, the mean impedance vectors of the élite group differed significantly from that measured in the normal population and in the other two groups (P<0.05). Conclusions: This study provides an original data set of BC and BI reference values parameters of élite male volleyball players. Our result might be useful for interpretation of individual bioimpedance vectors and for defining target regions for volleyball players.
Whole body precooling was hypothesized to reduce thermoregulatory and metabolic responses, thereby enhancing running time. Fourteen male runners completed two high-intensity running tests consisting of resting in 24 degrees C (normothermic condition; NC) or 5 degrees C (hypothermic condition; HC) for 30 min followed by 10–16 min of rest at 24 degrees C and then an exercise bout (24 degrees C) at 82% maximal aerobic capacity to exhaustion. Rectal temperature (Tre) before exercise was lower (by 0.37 degrees C; P < 0.005) and exercise duration was longer (by 121 +/- 24%; P < 0.05) in HC than in NC. Tre and mean skin (Tsk) and mean body (Tb) temperatures remained lower during HC (P < 0.01). Pre- and postexercise changes for Tsk, Tb, thermal gradient (Tre-Tsk), and heart rate (HR) were larger in HC than in NC (P < 0.05). Final Tre, Tre-Tsk, HR, and blood lactate were similar between HC and NC. During exercise, heat storage was greater (P < 0.01) in HC than in NC (173 +/- 46 and 143 +/- 38 W/m2, respectively) and subjects sweated more in NC than in HC (P < 0.01). O2 consumption was lower initially in HC than in NC (P < 0.05), but O2 pulse was not different. It was concluded that precooling results in greater exercise endurance with enhanced heat storage rate and less stress on metabolic and cardiovascular systems.
We investigated cardiac autonomic responses and hemodynamic parameters on recovery time following short-, middle- and long-swimming performance. Ten male regional-level swimmers were tested to estimate time and frequency domains of arterial baroreflex sensitivity and heart rate variability after 100-, 200-, and 400-m of front crawl. We found a BRS reduction for 90 min after a maximal 100- and 200-m front crawl event, meanwhile the reflex was restored back to the baseline value about 70 min after 400-m. The vagally mediated HF power of R-R intervals was significantly reduced for 30 min after 400-m, and more than 90 min after 100- and 200-m, with a concomitant increase of sympathetic modulation. After 400-m athletes have reduced their stroke volume for 50 min, which remained at the baseline level following 100- and 200-m. HR was restored back after 90 min in all conditions, whereas TPR was significantly reduced for 50 min after 200- and 400-m, with a persistent reduction after 100-m. Time course of autonomic recovery after 3 different swimming performances is influenced by exercise intensity and duration, showing a rapid recovery after 400-m, an intermediate recovery after 200-m, and a significantly delayed recovery after a more strictly anaerobic performance like 100-m of front crawl. These results could encourage coaches to consider that athlete might be affected by the specific recovery time of the previous exercise performed, suggesting that the management of the exercise intensity, and appropriate monitoring of cardiac autonomic parameters might be helpful to know the physical condition of each athlete.
The aim of this investigation was to evaluate the recovery pattern of a whole body compression garment on hemodynamic parameters and on ANS activity following a swimming performance. Ten young male athletes were recruited and tested in two different days, with and without wearing the garment during the recovery phase. After a warm-up of 15 minutes, athletes were instructed to perform a maximal 400m freestyle swimming event, and then time series of beat-to-beat intervals for heart rate variability (HRV), baroreflex sensitivity (BRS), and hemodynamic parameters were recorded for 90 minutes of recovery. The vagally mediated HF power of R-R intervals, NN50, and pNN50 showed a faster recovery due to the costume, meanwhile, the LFRR index of sympathetic modulation of the heart, as well as LF:HF ratio and BRS alpha index (αLF) were augmented in control than in garment condition. When athletes wore the swimsuit, cardiac output was increased and the returning of the blood to the heart, investigated as stroke volume, was kept constant due to the reduction of the total peripheral resistances. During control condition, HR was restored back to baseline value 20 minutes later with respect to garment condition, confirming that the swimsuit recover faster. The effectiveness of the swimsuit on ANS activity after a maximal aerobic performance has been shown with a greater recovery in terms of HRV and hemodynamic parameters. BRS was reduced in both conditions, maybe due to prolonged vasodilatation that may have also influenced the post-exercise hypotension.