ChapterPDF Available

Energy systems in swimming

Authors:
  • National Institute of Physical Education of Catalonia (INEFC), Universitat de Barcelona
In: World Book of Swimming: From Science to Performance ISBN: 978-1-61668-202-6
Editors: L. Seifert, D. Chollet and I.Mujika ©2010 Nova Science Publishers, Inc.
Chapter 11
ENERGY SYSTEMS IN SWIMMING
Ferran A. Rodríguez1 and Alois Mader2
1Institut Nacional d’Educació Física de Catalunya, Universitat de Barcelona, Spain
2Deutsche Sporthochschule Köln, Cologne, Germany
ABSTRACT
Swimming performance can be described as the result of the transformation of the
swimmer’s metabolic power into mechanical power with a given energetic efficiency.
Most of the energy produced by the swimmer is utilized to overcome water resistance or
drag, and the rate of energy expenditure theoretically increases with the cube of the
velocity. This energy is generated by the sum of the immediate (phosphagen), short-term
(anaerobic glycolysis) and long-term (oxidative phosphorilation or aerobic) energy
delivery systems. The relative contribution of each system has been frequently
determined on research developed in other types of exercise activities or from linear
calculations. The modeling of the energy metabolism behavior using computer
simulation, combined with physiological field measurements, offers new insights and
improved estimations on the relative contribution of the energy delivery systems.
Key words: Energy metabolism, bioenergetics, aerobic/anaerobic energy expenditure,
maximal oxygen uptake, computer simulation
1. INTRODUCTION
This chapter (i) briefly reviews the bases of the energy delivery systems during exercise,
(ii) presents a computer simulation model of the dynamic behavior of energy metabolism
during swimming, (iii) describes the relative contribution of the aerobic and anaerobic
systems to energy expenditure during swimming in different events, and (iv) summarizes the
practical applications of swimming bioenergetics for performance and training.
Ferran A. Rodríguez and Alois Mader
2
2. ENERGY METABOLISM DURING EXERCISE
In swimming, as in all forms of human locomotion, muscles generate the energy or power
to propel the body through the water. Thus, swimming performance can be described as the
result of the transformation of the swimmers metabolic power into mechanical power with a
given energetic efficiency [19]. As in any form of exercise, chemical processes transform the
chemical energy stored within the muscle or borne by the blood into mechanical energy.
Energy for any biological function is obtained from the breakdown (catabolism) of food
into three basic chemical compounds: carbohydrates, lipids, and proteins. These can be stored
and ultimately transformed into another chemical compound, adenosine triphosphate (ATP),
which is the only fuel that can be used directly for muscle force generation or for any cellular
function. In muscle, energy from the hydrolysis of ATP by the enzyme ATPase activates
specific sites on the force-developing elements, which allows the muscle filaments
(myofibrils) to generate force. ATP is also needed to re-uptake calcium ions for muscle fiber
relaxation. There are three mechanisms involved in the breakdown and resynthesis of ATP
[2,10]:
1. Phosphagen system. Phosphocreatine (PCr) is broken down enzymatically to creatine
(Cr) and Pi which is transferred to ADP to re-synthesize ATP. This is in turn broken
down enzymatically to ADP (adenosine diphosphate) and inorganic phosphate (Pi) to
yield energy for muscle activity. This mechanism is commonly called phosphagen or
anaerobic alactic (i.e. does not use oxygen nor produces lactate) system and is the
sole source of energy for muscles lasting only a few seconds (up to 3-5 s at maximal
intensity). Only two thirds of phosphagen can be depleted without the activation of
glycolysis.
2. Glycolytic system. Glucose 6-phosphate, derived from muscle glycogen or blood-
borne glucose, through anaerobic glycolysis is converted to lactate and re-synthesizes
ATP by substrate-level phosphorylation reactions. This mechanism is named the
glycolytic or anaerobic lactic (i.e. lactate producing) system and represents a
medium-term energy delivery system. This system needs a few seconds to reach
near maximal rate and delivery of ATP plateaus after ~1 min at maximal power.
3. Aerobic system. The products of carbohydrate, lipid, protein, and alcohol metabolism
can enter the tri-carboxylic acid (TCA or Krebs) cycle in the mitochondria and be
oxidized to carbon dioxide and water in the presence of oxygen. This mechanism is
known as oxidative or aerobic (i.e. oxygen using) system and can be seen as a long-
term source of energy. This system takes about 40s-1.5 min to reach maximal power
but energy delivery can be maintained for about 5-7 min at that rate and almost
indefinitely at submaximal rates of exercise.
Figure 1 presents an overview of the main metabolic pathways of energy supply from
carbohydrate, lipid, and protein substrates, as well as the three mechanisms of energy
delivery.
Energy Systems in Swimming
3
Figure 1. Overview of the main pathways of energy metabolism with indication of the three metabolic
energy delivery systems: (1) phosphagen or anaerobic alactic, (2) glycolytic or anaerobic lactic, and (3)
oxidative or aerobic (3). The purpose of the three metabolic systems is to continuously re-synthesize
ATP to avoid a significant fall of intramuscular ATP concentration.
3. METABOLIC POWER PRODUCTION DURING SWIMMING
In physiological conditions ATP concentration does not decrease much during muscular
contraction. We will consider the rates of ATP splitting and resynthesis equal for all practical
purposes. Therefore, the overall energy output per unit of time (
E
) can be expressed by the
following simple equation:[2]
2
OVcabLrCPPTAE
++=
(1)
where variables (note the dot above meaning ‘per unit of time’) indicate the net rates of ATP
and PCr splitting, lactate production and O2 consumption (and thus the rate of energy
expenditure by the three mechanisms for energy supply), and the constants b and c, the
amount of ATP re-synthesized per unit of lactate formed or O2 consumed. This equation helps
us to understand the notion of a continuum of energy supply to the working muscles, and how
the rates of energy expenditure can be estimated via measurement of PCr stores (estimated as
a function of the swimmer’s body mass), muscle lactate formation and elimination (estimated
Ferran A. Rodríguez and Alois Mader
4
as blood lactate accumulation), and oxygen uptake. For the sake of simplicity we will express
equation 1 as follows:
aerlacalacmet PPPP ++=
(2)
where Pmet is total metabolic power, and Palac, Plac, and Paer, metabolic power from anaerobic
alactic (phosphagen), lactic (glycolytic), and aerobic (oxidative) sources. However, this
classification is somewhat simplistic because exercise requires the simultaneous delivery of
more than one type of energy source, and must be viewed as a continuum of energy supply.
Figure 2 shows a diagram of the total energy output (i.e. Pmet) and absolute contribution of the
three energy systems during maximal swimming, as a function of time in top male swimmers
obtained by computer simulation. The diagram illustrates the concept of simultaneous
activation of the metabolic mechanisms for the maintenance of the high energy output needed
to swim at maximal speed over the different competitive distances.
Figure 2. Total energy output (
tot
E
) and share of the three energy delivery systems during maximal
swimming as a function of time. Data (expressed as mLO2·kg-1·min-1) correspond to absolute values
for 50 to 1,500 m freestyle swimming at competitive speed in top male swimmers as obtained by
computer simulation.
Swimming can be interpreted as a simple thermodynamic process in which chemical
energy (E) is transformed into mechanical work (W in joules) with a given efficiency (e);
since W (J) per unit of time (s-1) is mechanical power (Pw in watts, W):
E/We;WE =
(3)
Energy Systems in Swimming
5
That implies that the energy required to swim at a certain speed does not depend only on
the metabolic power developed by the swimmer but also on his or her swimming efficiency,
which is known to be the most relevant factor in swimming performance.[19]
All mechanical power output (P0) is delivered by the transformation of metabolic power
(Pm) into mechanical work. In this process, a large part of the chemical power contained in
the muscle is transformed into heat, with a given metabolic efficiency (em), which does not
vary much between subjects:
mmomom ePP;e/PP ==
(4)
On the other hand, a considerable part of the mechanical power is used to overcome
water resistance or drag forces (Pd in watts),[3] which is theoretically dependent on the cube
of swimming velocity:[19]
(5)
where K is a constant incorporating the density of water, the drag coefficient, and the greatest
cross-sectional area - the last two factors largely depending on individual swimmers
characteristics. This relationship implies that small increments in swimming velocity will
dramatically increase the mechanical power needed, and thus the metabolic power that the
swimmer must generate. For example a 2% increase in velocity will require an 8% increase in
mechanical power.
But in reality, the total mechanical power output (Po) produced by the swimmer equals
not only power to overcome drag (Pd), but also power expended in giving pushed away
masses of water a kinetic energy change (Pk). The ratio of the useful power (to overcome
drag) to the total power output has been defined as the propelling efficiency (ep), and thus:
[19,20]
poop e/vKP;P/vKe 33 ==
(6)
Hence, rearranging equations 4, 5, and 6, the metabolic power that a swimmer must
generate (Pm) is directly proportional to the velocity cubed times the constant K (basically
depending on the drag coefficient and cross sectional area), and inversely proportional to his
or her propelling and metabolic efficiency:
mpm ee/vKP =3
(7)
Since metabolic efficiency is quite homogeneous among individuals, we will assume it is
a constant. This leaves propelling efficiency as the major denominator in the equation. This
factor must be taken into account when assessing the metabolic capacity of swimmers, since
the energy cost of swimming for submaximal intensities has often been expressed as a linear
function, yet it theoretically increases with v3.
pm e/vKP 3
=
(8)
Ferran A. Rodríguez and Alois Mader
6
Another parameter expressing the relationship between energy and propulsion (i.e.
propulsive efficiency) is the energy cost of swimming (Cs), which can be defined as the
amount of metabolic energy spent in transporting the body mass (mb) of the swimmer over a
unit of distance.[3] Energy cost is usually reported in J per m per kilogram (J·m-1·kg-1) or
simply as kJ·m-1.
d/EC;dm/EC sbs ==
(9)
Swimming performance (vmax) may then be quantified as:
msmax P·Cv =
(10)
At submaximal intensities (i.e. below 80% of
2max
oV
), almost the total mechanical power
output is generated by the aerobic metabolism (Paer), and since oxygen uptake can be
measured, we may establish the following relationship:
3
2vKoVP
aer =
(11)
The rate of anaerobic lactic energy expenditure (Plac, mLO2·min-1) can be calculated from
the oxygen energy equivalent of net blood lactate accumulation after exertion during
swimming using the 2.7 mLO2·mmol-1·kg-1 of body mass (mb) proportionality constant
calculated by di Prampero et al. (1978):[2,4]
( )
t/m]La[]La[.P bbrestbex erlac 72
(12)
In high velocity swimming, the rate of alactic anaerobic energy contribution (Palac,
mLO2·min-1) can also be estimated according to the constant calculated by di Prampero et al.
(1978) for front crawl swimming (18 mLO2·kg-1):[4]
t/mP balac 18
(13)
According to equation 4, the rate of total energy expenditure (Pm,
tot
E
, mLO2·min-1) in
high velocity swimming can be estimated from
2
oV
and blood lactate measurements after free
swimming and the two energy equivalent constants:[16,17]
)t/m()t/La.(oVEP bbtotm++=1872
2
Δ
(14)
Another means of estimating the anaerobic contribution to swimming is based on the
calculation of the accumulated oxygen deficit as described by Medbø et al. (1988),[11] using
equation 10 and extrapolating to speeds higher than 80% of
max
oV 2
. However, this estimation
relies on the assumption that the high velocity swimming speed is proportional to v3 in its
total range of variation, which is not completely in agreement with experimental
results.[12,13,16,17]
Energy Systems in Swimming
7
4. THE ENERGY COST OF SWIMMING
Swimming performance depends on the swimmer’s metabolic power attainable at
competitive speed and the energy cost to swim at that speed (equations 9-10). Thus, the
energy cost of swimming (Cs) can be used to quantify propulsive efficiency, a major
determinant of swimming performance.
At competitive speeds, Cs is least in freestyle and greater in backstroke, butterfly and
breaststroke, respectively.[1] As can be seen in Figure 3 in a wide range of submaximal
speeds, breaststroke is the least economical stroke, and Cs increases linearly with velocity.
This relationship is probably due to wide intracycle variations in speed (i.e. the substantial
amount of energy spent accelerating the body during the pushing phase to compensate for the
loss of speed occurring in the non-propulsive phase). The other three strokes show
exponential increases in Cs with increasing velocity, with butterfly reaching a minimum at a
speed of about 1 m·s-1, probably due to the tendency of the body to sink at lower speeds.[1]
These results are highly correlated to maximal competitive speeds and time records in the
four strokes.
Figure 3. Mean values of the energy cost of swimming (Cs) in the four strokes as a function of speed.[1]
Ferran A. Rodríguez and Alois Mader
8
5. CONTRIBUTION OF THE ENERGY DELIVERY SYSTEMS DURING
MAXIMAL SWIMMING
Competitive pool events include races from 50 up to 1,500 m. The metabolic power
needed to swim at maximal speed and the relative contribution of the three energy systems
vary depending on the distance and, thus, on the swimming time at maximal intensity. On the
other hand, the power and capacity of the three energy systems are individual factors
determining performance capacity in swimming. A large part of training is devoted to the
improvement of the different energy production mechanisms.[19] However, there is a
remarkable disparity in the technical and scientific literature as to how each of these systems
is activated and their proportional contribution to the total energy output in the different
events. Table 1 summarizes studies estimating the relative contribution of the energy delivery
systems during freestyle swimming events from 50 to 1,500 m. A very large disparity
between estimates is evident, particularly in the shorter events, where the anaerobic
contributions are obviously under- or overestimated. In contrast the disparity in longer events
(800-1,500 m) is comparably smaller, presumably reflecting more accurate quantification of
the aerobic contribution due to the practicality of oxygen uptake measurements. In previous
reports, the relative contribution of each system has frequently been suggested from
estimations based on other types of exercise, on linear calculations, or assuming a linear
increase of metabolic power in supra-maximal speed (e.g. maximal accumulated oxygen
uptake estimations of anaerobic contribution). Differences on the mechanical efficiency of the
swimmers investigated may also account for the disparity.
Table 1. Suggested relative contribution of the energy systems during swimming. Data
(in percentage) are a summary of the literature and are expressed the range of values
from different authors.[1,5,9,12-14,18,21]
Distance*
Phosphagen (%)
Glycolytic (%)
Aerobic (%)
50 m
15-80
2-80
2-26
100 m
5-28
15-65
5-54
200 m
2-30
25-65
5-65
400 m
0-20
10-55
25-83
800 m
0-5
25-30
65-83
1,500 m
0-10
15-20
78-90
*For male freestyle swimmers. Relative energy contribution is assumed to be similar in females for a
given distance.
Based on experimental results during free swimming, we calculated the rates of energy
expenditure (
tot
E
) during 50, 100, 200, and 400-m crawl swimming events along a wide
range of speeds (i.e. circa 1.1-2.2 m·s-1) (figure 4). The metabolic requirements, calculated
using equation 14, increased exponentially with an exponent close to 3. This outcome is
consistent with the mechanical power requirements to overcome water resistance and drag
forces (see Equation 5), theoretically dependent on the cube of swimming velocity.[19]
Interestingly, when compared with computer simulation values based on measurements
obtained in sprinters by Ring, et al.,[14] this exponent seems to be somewhat lower for high-
velocity swimming (i.e. over 1.9 m·s-1), and can also be observed in Figure 4 as the two
Energy Systems in Swimming
9
values corresponding to male sprinters over 2 m·s-1. This outcome may be explained by the
greater body height of male sprinters, which is related with faster swimming at high speed,
and/or by other biomechanical factors such as the hydrodynamic lift.
Figure 3. Rate of total energy demands (
tot
E
) during front crawl swimming in the range of submaximal
and maximal speeds (ca. 1.1-2.2 m·s-1). Values (filled circles) have been calculated using equation 13
from free swimming experimental data. Empty triangles (and dashed line) correspond to computer
simulation results in 50-m sprinters.[14] See text for further details.
6. MODELING OF THE AEROBIC AND ANAEROBIC ENERGY
YIELD AS A FUNCTION OF SWIMMING SPEED: A NEW APPROACH
In recent years, a model of the dynamics of energy muscle metabolism has been
developed by Mader.[6,8] This model assumes that the dynamic changes of the
phosphorylation state of the high-energy phosphate system, and the adjustment of the rate of
glycolysis and oxidative phosphorylation as a result of contraction, as well as the lactate
distribution from muscle to a passive compartment, can be calculated by a system of
differential equations. To summarize, Mader’s model is based on the regulation of ATP
production in muscle cells by oxidative phosphorylation (OxP) and glycolysis as a function of
the phosphorylation state of the cytosolic high-energy phosphate system. In this model, the
activation of OxP can be established including free cytosolic [ADP] as substrate and a second
driving force which results from the difference of free energy between mitochondria
(ΔGOXap ~ (1+ n)*Δp) and cytosol (ΔGATPcyt). Glycolysis is regulated at the level of PFK
Ferran A. Rodríguez and Alois Mader
10
mainly by free [ADP] and [AMP]. PFK is inhibited by a decreasing pH resulting from lactate
accumulation. The steady state characteristics of the activation control exhibit sigmoid types
of kinetics. The ATP/PCr equilibrium is calculated by algebraic equations. The dynamic
behavior of the metabolic control of ATP production as function of ATP consumption is
calculated by a system of two first order non-linear differential equations, which include the
steady state characteristics of OxP and glycolysis as well as a time delay for oxygen transport.
Lactate distribution and elimination is calculated using a two compartment model with an
active lactate space (lactate production) and a passive space, which includes lactate oxidation
and glucose resynthesis. After translation into a computer simulation model, the simulation of
the dynamics of the metabolic behavior is performed by a stepwise solution of the differential
equation with a Runge-Kutta-Fehlberg-method. The model has been applied to the computer
simulation analysis of energy supply during 50-m swimming[13,14], and 100, 200, and 400-
m crawl.[12,13,18]
Based on this computer simulation analysis (a detailed description and assumptions are
beyond the scope of this chapter but can be found elsewhere[6]) a much more precise picture
of metabolic processes involved during a race can be reproduced. Figure 5 displays an output
diagram resulting from the computer simulation of metabolic parameters during rest, exercise,
and recovery for 400 m freestyle swum at 3 min 45 s. Input parameters were adjusted to meet
the expected metabolic pattern of an elite 400-m specialist (i.e. very high oxidative and
relatively low glycolytic power). Figure 6 shows the corresponding time-dependent relative
contribution of the three energy delivery systems.
Figure 5. Computer simulation of metabolic parameters during rest, exercise, and recovery for a 400-m
freestyle race (3 min 45 s). See further details in the text.
Energy Systems in Swimming
11
Figure 6. Share of the three energy delivery systems during a 400-m race (3 min 45 s) as calculated by
dynamic computer simulation. Values are percentage of energy output from aerobic, alactic
(phosphagen), and glycolytic (lactic) processes, respectively.
To quantify the energy share during swimming at maximal speed, the dynamic behavior
of the energy metabolism during 50 to 1,500-m events has been simulated and a summary of
computed results are presented in Table 3. Input parameters (i.e.
max
OV 2
, maximal glycolytic
power, maximal ATP-PCr availability in the active muscles, percentage of active muscle
mass, and space for lactate distribution) were specified to meet the expected swimmer’s
power output (according to equation in Figure 4) and specific metabolic profile (e.g.
relatively high glycolytic power and low aerobic power in sprinters, high aerobic power, and
low glycolytic power in long-distance swimmers).
Table 3. Share of energy systems during freestyle swimming competitive events in top-
level swimmers obtained by computer simulation. Data are in percentage of total energy
output (Etot). See text for further details.
Distance
Time* (min:s)
Phosphagen (%)
Glycolytic (%)
Aerobic (%)
50 m
0:22.0
38
58
4
100 m
0:48.0
20
39
41
200 m
1:45.0
13
29
58
400 m
3:45.0
6
21
73
800 m
7:50.0
4
14
82
1,500 m
14:50.0
3
11
86
* Reference times for top-level male freestyle swimmers (2008). The relative energy patterns in female
swimmers are assumed to be relatively similar for a given distance.
Ferran A. Rodríguez and Alois Mader
12
The prevalence of anaerobic processes during sprinting events (i.e. 22 to 48 s ca.), leads
to a progressive predominance of the aerobic processes in middle- (i.e. 200 and 400 m) and
long-distance events (i.e. 800 and 1,500 m).
In 50m events a large muscle mass with a high percentage of fast twitch fibers (i.e. with
high glycolytic power) is required to produce a remarkably high energy output (over 200
mLO2·kg-1·min-1). ATP and PCr stores are rapidly depleted and glycolysis is almost
immediately activated to maintain energy output and becoming the most important source of
energy for muscle contraction. However, the short duration of these events prevents a high
level of acidosis from occurring, and maximal blood lactate will typically be at the range of
12-14 mmol·L-1. The activation of the aerobic system can be neglected because the race can
be completed without breathing.
100-m events, contrary to traditional views, require the complete and rapid activation of
both the glycolytic and aerobic energy delivery processes, as well as the capacity to sustain
high lactate concentrations in the active muscles. These high rates of activation (with short
time constants of oxygen uptake and glycolysis) must also be maintained to sustain the high
energy output needed to swim at maximal speed. Average values for the time constant τ = 22
s (ranging from 12 to 32 s) have been measured using breath-by-breath gas analysis.[15] In
fact, the simulations show that τ decreases when a fast PCr depletion takes place. Muscle
lactate will rapidly accumulate to values in excess of 30 mmol·L-1 causing acidosis (pH
reduction) and decreasing glycolysis probably through the inhibition of phosphofructokinase,
a key enzyme in the glycolytic pathway. This sequence of events will cause in turn a decrease
of the muscular rate of contraction and the onset of fatigue if the aerobic processes are not
able to sustain energy output during the last two thirds of the race. Blood lactate during
competition would typically rise up or exceed 20 mmol·L-1. Interestingly, during 100-m
maximal swims, peak
2
OV
correlated significantly with swimming speed (r = .79) and to 400
m (r = .75), confirming that both a high aerobic power and a fast activation of the aerobic
mechanisms are needed.
Middle-distance events require very high
max
OV 2
values (i.e. maximal aerobic power), as
well as moderate (400 m) to high (200 m) glycolytic power. The rate of activation of the
aerobic system is lower in 400-m events as compared to 100-m (average time constant equals
about 28 s),[15] but top-level specialists show the highest
max
OV 2
among swimmers, with
values in the range of 70-75 mL·kg-1·min-1 (60-65 for females) and a large body mass.
Maximal blood lactate values are typically in the range of 16-18 mmol·L-1 (200 m) and 14-16
mmol·L-1 (400 m). Interestingly, the fastest swimmers will also be able to swim faster at low
blood-lactate concentrations.[7]
Long-distance events are characterized by a predominance of the aerobic energy delivery
processes. Long-distance specialists show very high
max
OV 2
values, many in excess of 75
mL·kg-1·min-1 (65 for females), and low glycolytic power. A metabolic balance is required,
with muscle glycogen oxidation occurring at a high rate and
2
OV
reaching values close to
maximal. Glycolysis is in turn activated, reaching a steady state at a higher level of muscle
lactate. Maximal blood lactate values are typically in the range of 8-12 mmol·L-1.
Figure 7 displays graphically the percentage relative contribution of the three energy
delivery systems and the simplified aerobic-anaerobic share during swimming at maximal
speed (50 to 1,500 m) as a function of time obtained by computer simulation.
Energy Systems in Swimming
13
Figure 7. Share of the three energy delivery systems (A) and simplified aerobic-anaerobic contribution
(B) during freestyle swimming at maximal speed as a function of time. Data (in percentage of total
energy demands,
tot
E
) were obtained by computer simulation. Symbols denote values corresponding to
50, 100, 200, 400, 800, and 1,500 m freestyle, respectively. See text for further details.
7. PRACTICAL APPLICATIONS
For performance:
1) Comprehension of the metabolic energy demands in various swimming events may
help the coach to determine which ones (i.e. sprint, middle-distance, or distance) best
match the individual metabolic capacities of a swimmer.
Ferran A. Rodríguez and Alois Mader
14
2) Computer simulations of the dynamic metabolic behavior, together with individual
metabolic data collection, may help the coach determining the optimal race (pacing)
strategy during competition.
For training:
1) A large amount of training is devoted to improve the metabolic capacities of the
swimmer. Knowledge of the metabolic requirements of the different swimming
events and strokes may help the coach to develop training plans to enhance the
underlying metabolic capacities.
2) Metabolic testing may identify which metabolic capacities are being improved,
maintained or decreased through training, and how the swimmer’s metabolic profile
corresponds to the optimal energy system development for given events and strokes.
8. CONCLUSION
Swimming performance is the result of the transformation of metabolic power into
mechanical power with a given energetic efficiency. Most of the energy produced will be
utilized to overcome drag, and the rate of energy expenditure will increase approximately
with the velocity cubed. Energy is generated by the sum of the immediate (ATP-PCr), the
short-term (anaerobic glycolysis), and the long-term (oxidative phosphorilation or aerobic)
energy delivery systems.
The energy cost of swimming is used to quantify propulsive efficiency, a major
determinant of swimming performance. At competitive speeds, propulsive efficiency is
greater in freestyle and lower in backstroke, butterfly, and breaststroke, respectively.
To quantify the energy share during swimming at maximal speed, the dynamic behavior
of the energy metabolism has been simulated. In 50-m events ATP and PCr stores are rapidly
depleted and glycolysis is almost immediately activated to maintain energy output. 100-m
events require the complete and rapid activation of both the glycolytic and aerobic energy
systems, since the decreasing glycolytic energy supply is compensated in part by increasing
oxidative ATP production during the last two thirds of the race. Middle-distance events
require very high
max
OV 2
values, as well as moderate to high glycolytic power. Long-
distance events are characterized by a predominance of the aerobic energy delivery processes.
REFERENCES
[1] Capelli, C., D. R. Pendergast, and B. Termin (1998). Energetics of swimming at
maximal speeds in humans. Eur J Appl Physiol Occup Physiol 78: 385-93.
[2] di Prampero, P. E. (1981). Energetics of muscular exercise. Reviews of Physiology,
Biochem Pharmacol 89: 143-222.
[3] di Prampero, P. E. (1986). The energy cost of human locomotion on land and in water.
Int J Sports Med 7: 55-72.
Energy Systems in Swimming
15
[4] di Prampero, P. E., D. R. Pendergast, D. W. Wilson, and D. W. Rennie (1978). Blood
lactic acid concentrations in high velocity swimming. In Eriksson, B. and B. Furberg,
eds., Swimming Medicine IV. Baltimore: University Park Press, 249-261.
[5] Houston, M. E. (1978). Metabolic response to exercise, with special reference to
training and competition in swimming. In Eriksson, B., Furberg, B., eds., Swimming
Medicine IV. Baltimore: University Park Press, 207-232.
[6] Mader, A. (2003). Glycolysis and oxidative phosphorylation as a function of cytosolic
phosphorylation state and power output of the muscle cell. Eur J Appl Physiol 88: 317-
38.
[7] Mader, A., H. Heck, and W. Hollmann (1978). Evaluation of lactic acid anaerobic
energy contribution by determination of postexercise lactic acid concentration of ear
capillary blood in middle-distance runners and swimmers. In Landry, F. and W. Orban,
eds., Exercise physiology. Miami, FL: Symposia Specialists, 187-200.
[8] Mader, A., H. Heck, and W. Hollmann (1983). A computer simulation model of energy
output in relation to metabolic rate and internal environment. In Knuttgen, J. A.
//Vogel, J. //Poortmans, J., eds., Biochemistry of Exercise. Champaign, IL: Human
Kinetics, 263-279.
[9] Maglischo, E. (2003). Swimming fastest. Champaign, IL, Human Kinetics.
[10] Maughan, R., M. Gleeson, and P. L. Greenhaff (1997). Biochemistry of exercise and
training. Oxford: Oxford University Press.
[11] Medbo, J. I., A. Mohn, I. Tabata, R. Bahr, O. Vaage, and O. M. Sejersted (1988).
Anaerobic capacity determined by maximal accumulated O2 deficit. J Appl Physiology
64: 50-60.
[12] Olbrecht, J. (1989). Metabolische Beanspruchung bei Wettkampfschwmmern
unterschiedlicher Leistungsfähigkeit. Doctoral dissertation. Cologne: Deutschen
Sporthochshule Köln.
[13] Ring, S. (1997). Energiestoffwechsel im Sprintschwimmen. Cologne: Deutschen
Sporthochschule Köln.
[14] Ring, S., A. Mader, W. Wirtz, and K. Wilke (1996). Energy metabolism during sprint
swimming. In Troup, J. P., Hollander, A. P., Strasse, D. et al., Biomechanics and
Medicine in Swimming VII. London: E. & F. N. Spon, 177-184.
[15] Rodríguez, F. A., K. L. Keskinen, O. P. Keskinen, and M. Malvela (2003).Oxygen
uptake kinetics during free swimming: a pilot study. In Chatard J. C., ed., Biomechanics
and Medicine in Swimming IX. Saint-Étienne: Publications de l’Université de Saint-
Étienne, 379-384.
[16] Rodríguez, F. A. (1997). Metabolic evaluation of swimmers and water polo players.
Kinesiology. Journal of Biology of Exercise 2: 19-29.
[17] Rodríguez, F. A. (1999). Cardiorespiratory and metabolic field testing in swimming and
water polo: from physiological concepts to practical methods. In Keskinen, K. L., P. V.
Komi, and A. P. Hollander, eds., Biomechanics and Medicine in Swimming VIII.
Jyväskylä: Gummerus Printing, 219-226.
[18] Rodríguez, F. A. and A. Mader (2003). Energy metabolism during 400 and 100-m
crawl swimming: computer simulation based on free swimming measurement. In
Chatard, J.-C., Biomechanics and Medicine in Swimming IX. Saint-Étienne:
Publications de l'Université de Saint-Étienne, 373-378.
Ferran A. Rodríguez and Alois Mader
16
[19] Toussaint, H. M. and A. P. Hollander (1994). Energetics of competitive swimming.
Implications for training programmes. Sports Med 18: 384-405.
[20] Toussaint, H. M., W. Knops, G. De Groot, and A. P. Hollander (1990). The mechanical
efficiency of front crawl swimming. Med Sci Sports Exerc 22: 402-8.
[21] Troup, J. (1984). Energy systems and training considerations. Journal of Swimming
Research 1: 13-16.
... Swimming performance can be described as the result of the transformation of the swimmer's metabolic power into mechanical power with a given energetic efficiency. Most of the energy produced by the swimmer is utilized to overcome water resistance or drag, and the rate of energy expenditure theoretically increases with the cube of the velocity [6]. Nevertheless, swimming performance is determined by physiological, psychological and anatomical factors [7]. ...
... Swimming performance can be described as the result of the transformation of the swimmer's metabolic power into mechanical power with a given energetic efficiency. Most of the energy produced by the swimmer is utilized to overcome water resistance or drag, and the rate of energy expenditure theoretically increases with the cube of the velocity [6]. One of the most popular masters' sports is swimming, which is well-suited for lifelong participation [12]. ...
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Introduction: Knowing the oscillations in the speed of the athletes that swim different distances during training or competition is one of the most important directions for predicting performing times over different distances. Aim: The aim of the present study was to analyze the speed fluctuations in swimming, from round one to the next. We also aimed to determine the rounds with the best and the worst performance, precisely in order to optimize the athletes' physical training. Material and Methods: During the 9th edition of the 24h AquaChallenge swimming marathon, the speed fluctuation was analyzed on 34 swimmers, 10 of them were females and 24 males, aged between 16 and 74. Each swam 6 laps of 30 minutes. The Timisoara Masters Swimming Club, in collaboration with the Timis County Directorate for Sport and Youth and the Faculty of Physical Education and Sport, processed the demographic data of the participants and timed them during each round. Results: The results showed that the best performance was recorded in the first round (34.2%), with swimming speed decreasing during each round. In round 5 (61.8%) the lowest performance was determined. As time went by in the competition, the fatigue increased and the athletes could no longer maintain the same speed they started with. Conclusions: In conclusion, the functional capacity and the maintaining of the same level of speed can be negatively influenced by an increased level of fatigue.
... Successful open-water swimming is often defined as achieving the fastest time to cover a given distance or minimizing the cost of swimming at a specific intensity (22,25). Reducing the energetic cost of swimming is analogous to improving the swimming economy and is operationally defined as the rate of oxygen consumption or energy expenditure at a particular swim pace (5,25). ...
... Successful open-water swimming is often defined as achieving the fastest time to cover a given distance or minimizing the cost of swimming at a specific intensity (22,25). Reducing the energetic cost of swimming is analogous to improving the swimming economy and is operationally defined as the rate of oxygen consumption or energy expenditure at a particular swim pace (5,25). It plays a pivotal role in not only influencing swimming performance but also impacting subsequent performance in cycling and running (20,21,26). ...
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Lim, B, Villalobos, A, Mercer, JA, and Crocker, GH. Energetics and basic stroke kinematics of swimming with different styles of wetsuits. J Strength Cond Res 38(10): 1793–1799, 2024—This study investigated the physiological responses and basic stroke kinematics while wearing different styles of wetsuits during submaximal intensity front-crawl swimming. Fourteen subjects (6 men and 8 women) completed a swimming-graded exercise test to determine maximal aerobic capacity (V̇O 2 max) and four 4-minute submaximal front-crawl swims at a pace that elicited 80% of V̇O 2 max with different wetsuits: regular swimsuit (no wetsuit [NWS]), buoyancy shorts (BS), sleeveless wetsuit (SLW), and full-sleeve wetsuit (FSW). The rate of oxygen consumption (V̇O 2 ), rate of carbon dioxide production (V̇CO 2 ), minute ventilation (V̇ E ), heart rate (HR), respiratory exchange ratio, and cost of swimming (CS) were determined as the average for the last minute of each trial. The rating of perceived exertion was assessed after each swimming bout. In addition, stroke length and index were determined from swimming pace and stroke rate. V̇O 2 , V̇CO 2 , V̇ E , HR, and CS differed significantly among wetsuit conditions ( p < 0.01). Respiratory exchange ratio and rating of perceived exertion also varied by wetsuit conditions ( p < 0.05). However, stroke rate, length, and index were not significantly different across wetsuit conditions ( p > 0.05). No differences existed between SLW and FSW for any dependent variable ( p > 0.05). Results from this study suggest that swimming at the same pace without a wetsuit is the least economical, and both SLW and FSW are most and equally economical without significant kinematic changes. In addition, BS could be beneficial during training and racing in terms of less physiological demands than a regular swimsuit but not as economical as the SLW or FSW.
... Maximal oxygen consumption (VȮ 2max ) is a critical success factor in most endurance sports, 1,2 including competitive swimming, especially in races beyond 100-m. 3 VȮ 2max reflects how well the cardiovascular and respiratory systems deliver oxygen to the muscles involved, as well as their ability to utilize this oxygen in producing the energy required for competitive performance. [4][5][6] Measuring VȮ 2max is therefore an indispensable tool for researchers, coaches and athletes striving toward excellence in training and performance. ...
... 24 Based on these indications the 1500-m distance was chosen to relate to VȮ 2max , as it is the longest indoor swimming event with the highest aerobic contribution to the overall performance. 3 The final finish time was determined through video analysis (Panasonic HCX1000, HD, 50fps). The start time was determined by capturing the light located on the start system and the end time was determined by capturing the final touch of the fingers on the pool wall. ...
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Objectives: This study aims to identify the optimal method for determining V̇O2max in competitive swimmers in terms of validity and test–retest reliability. Design: Controlled experiment. Methods: Twenty competitive swimmers performed four maximal incremental exercise tests: cycling, arm cranking, ergometer swimming, and tethered swimming. Gas analysis was conducted to estimate V̇O2max. Validity was assessed in terms of the amount of variance of the performance on a 1500-m time trial explained by the estimated V̇O2max . Test–retest reliability was evaluated using the intraclass correlation coefficient (ICC). Results: V̇O2max obtained from tethered swimming, ergometer swimming, and cycling explained a similar amount of variance of the 1500-m performance (R2 = 0.64, 0.64 and 0.65, respectively). However, ergometer swimming yielded significantly lower V̇O2max estimates (40.54 ± 6.55 ml/kg/min) than tethered swimming (54.40 ± 6.21 ml/kg/min) and cycling (54.39 ± 5.63 ml/kg/min). Arm cranking resulted in both a lower explained variance (R2 = 0.41) and a significantly lower V̇O2max (43.14 ± 7.81 ml/kg/min). Tethered swimming showed good reliability (ICC = 0.81). Conclusions: Bicycle and tethered swimming tests demonstrated high validity with comparable V̇O2max estimates, explaining a large proportion of differences in endurance performance. Choosing between these two methods involves a trade-off between a higher practical applicability and reliability of the bicycle test and the more sport-specific nature of the tethered swimming test. Keywords: Endurance capacity, Exercise testing, V̇O2peak, Athletes, Test-retest reliability, Reproducability
... The performance of short-term, progressive workload, high-intensity, exhaustive aerobic exercises, such as middle-distance running (800, 1500 m) or swimming (200, 400 m), is largely dependent on the glycolytic system and lactate oxidation. Future work is required to study the potential ergogenic effect of Brussels chicory on different types of exercises, particularly high-intensity exhaustive aerobic exercises [47][48][49]. Given that Brussels chicory contains multiple nutrients and phytochemicals, such as flavonoids (anthocyanin, catechin, quercetin glucuronide) and terpenes (lactucin, lactucopicrin, guaianolide glycosides), it remains unclear whether these compounds also play a role in the ergogenic effect of the Brussels chicory [26,50,51]. ...
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Background: Brussels chicory affluent in phenolic acids could inhibit atherosclerosis; however, its effects on exercise performance and post-exercise recovery are unknown. We hypothesized that Brussels chicory could enhance exhaustive aerobic exercise performance and post-exercise recovery by promoting lactate oxidation. Methods: This is a single-blind, randomized, placebo-controlled two-way cross-over trial involving 32 untrained college students (men 18) who consumed either Brussels chicory juice (100 g of Brussels chicory containing ~130 mg phenolic acids and 180 mL fresh milk) or placebo (180 mL fresh milk) for 7 days with a 2-week washout period. On the 7th day, participants received a short-term, progressive workload, high-intensity, exhaustive aerobic exercise with the Bruce protocol. Time to exhaustion and blood lactate were evaluated after exercise. C2C12 myotubes were treated with Brussels chicory phenolic acids (0.625–10 μM) to evaluate these effects on lactate metabolism and lactate dehydrogenase A (LDHA) and B (LDHB), two enzymes responsible for lactate biosynthesis and oxidation, respectively. Results: Brussels chicory consumption increased time to exhaustion by 8.3% and 12.2% for men and women participants, respectively. This administration also promoted post-exercise recovery, evidenced by a reduction in blood lactate (14.5% for men and 10.6% for women). In C2C12 myotubes, Brussels chicory protocatechuic acid and caffeic acid did not affect LHDA-mediated lactate production, whereas these compounds dose-dependently promoted LDHB-mediated lactate oxidation through an enrichment of mitochondria LDHB. Conclusions: Dietary supplementation with Brussels chicory may enhance short-term, progressive workload, high-intensity, exhaustive aerobic exercise performance and post-exercise recovery in humans, possibly by accelerating LDHB-mediated lactate oxidation.
... On the other hand, the absence of association between SS LT and 400-m performance in females may be explained by the higher variability between swimmers when compared with the other distances performance (Table 2). Moreover, despite aerobic capacity also playing an important role in 400-m swimming, the aerobic power could be more decisive in this distance, 37 as the duration differs significantly between a 400-m (∼4 min) and a 10-km OW event (∼2 h). Therefore, despite some exceptions, the relationships between SS LT and most of the seasonal best performances suggest that LT may be a useful performance indicator in elite OW swimmers. ...
Article
Purpose : The assessment of lactate threshold (LT) and its relationship to open-water (OW) performance is crucial. This study aimed (1) to analyze LT in world-class OW swimmers, (2) to compare swimming speed at LT (SS LT ) and 4 mmol·L ⁻¹ of blood lactate concentration ([La ⁻ ]; SS 4 ), and (3) to examine the relationships between SS LT and swimming performance. Methods : Twenty world-class and elite (11 male, 26.4 [3.0] y; 9 female, 25.8 [3.6] y) OW swimmers voluntarily participated. A total of 46 (29 male and 17 female) intermittent incremental tests (7 × 400 m) conducted in a 50-m pool were analyzed. Seasonal best performances on 400-, 800-, and 1500-m and 10-km OW swimming events were obtained. Results : The SS LT was 1.62 (0.02) (3.8 [1.0] mmol·L ⁻¹ ) and 1.46 (0.04) m·s ⁻¹ (3.0 [0.7] mmol·L ⁻¹ ) in males and females, respectively, which corresponded to 97% of the peak speed reached in the tests. There were no differences ( P = .148) between SS LT and SS 4 in males; however, SS LT was lower ( P = .019) than SS 4 in females. The SS LT was negatively correlated with swimming performance, with the exception of 10-km OW and 400-m times in males and females, respectively. Conclusions : World-class and elite OW swimmers exhibited a greatly developed aerobic capacity with LT close to their maximum speed. The SS 4 could be used as an approximation to SS LT in males but overestimates true aerobic capacity in females. LT is a useful tool for assessing performance, as OW swimmers with higher SS LT showed better swimming performance.
... This study aimed to assess changes in anaerobic performance and anaerobic fatigue thresholds, determined through the velocimetry method, imposed by a training m swim velocity could be associated with an also augmented anaerobic capacity once, for the swimmer's age group into analysis, the anaerobic contribution for total energy expenditure in this event varies from 40 (Figueiredo et al., 2011) to 60% (Maglischo, 2003). This contribution could rise until 80% in the 50 m sprint (Rodríguez & Mader, 2011). ...
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Velocimetry is an indirect method that may be used to evaluate swimmers' performance and determine anaerobic fatigue thresholds related to metabolic needs. However, how training changes the performance monitored through anaerobic fatigue thresholds is still unknown. This study aimed to assess changes in anaerobic performance and anaerobic fatigue thresholds, determined through the velocimetry method, imposed by a training macrocycle. Thirteen swimmers (six males and seven females) performed a 200 m maximum and an all-out 50 m front crawl sprint before and after a six-month macrocycle. In the 50 m, the swimmers' waists were connected to a speedometer through a cable for instantaneous velocity measurement. The anaerobic fatigue threshold was determined through wavelets analysis of frequencies using a MatLab routine. A video camera was placed in the pool deck for sagittal image recording. Rest and post-effort blood lactate concentrations were measured by dry chemistry and ear-lob puncture. A Student t-test was computed to assess pre and post-test differences (p≤0.05). Results showed a decrease of ≈2s in the 50m performance time after the macrocycle and a lactate increase of ≈2 mmol.l-1, suggesting an improvement in the total metabolic anaerobic contribution. However, the fatigue threshold remained statistically unchanged with training (18.23±6.35 vs 16.38±4.98s, p>0.05). It can be concluded that anaerobic fatigue thresholds may not be good indicators of swimmers' anaerobic performance after a long training period. Key words: swimming, training control, anaerobic potential, anaerobic fatigue threshold
... According to Billat (2001a), aerobic HIIT is defined as interval training where the energy demand during the intervals elicits aerobic metabolism at a higher rate (i.e., ≥50%) than the anaerobic metabolism. Based on various studies focusing on the energy contribution of maximal efforts across various distances/ times, the crossover point where aerobic and anaerobic energy contributes equally occurs around 2 min (Åstrand et al., 2003) or 600 m respectively 75 s in running (Duffield et al., 2005;Laursen, 2010), 60-90 s in cycling (Gastin and Lawson, 1994a;Craig et al., 1995;Craig and Norton, 2001), and similar durations in swimming (Rodríguez and Mader, 2011). In accordance with Gastin (2001), we have therefore decided to set the cutoff between anaerobic and aerobic HIIT of classical interval-based HIIT at an interval duration of 75 s. ...
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There are various categorization models of high-intensity interval training (HIIT) in the literature that need to be more consistent in definition, terminology, and concept completeness. In this review, we present a training goal-oriented categorization model of HIIT, aiming to find the best possible consensus among the various defined types of HIIT. This categorization concludes with six different types of HIIT derived from the literature, based on the interaction of interval duration, interval intensity and interval:recovery ratio. We discuss the science behind the defined types of HIIT and shed light on the possible effects of the various types of HIIT on aerobic, anaerobic, and neuromuscular systems and possible transfer effects into competition performance. We highlight various research gaps, discrepancies in findings and not yet proved know-how based on a lack of randomized controlled training studies, especially in well-trained to elite athlete cohorts. Our HIIT “toolbox” approach is designed to guide goal-oriented training. It is intended to lay the groundwork for future systematic reviews and serves as foundation for meta-analyses.
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This study aimed to examine the effects of rest periods on physiological and mechanical parameters during interval training (IT) using critical swimming velocity (CV). Ten male national-level competitive swimmers (19.5 ± 1.1 years old) swam 20 × 100 m (100IT) and 10 × 200 m (200IT) depend on critical velocity under different rest conditions. Rest periods for each IT were 10 seconds (R1) and 20 seconds (R2) per 100 m repetitive swimming distance. Heart rate (HR), rating of perceived exertion (RPE), blood lactate concentration, stroke rate, and stroke length (SL) were measured during all IT sets. HR significantly differed between R1 (164.0–173.0 beats per minute [bpm]) and R2 (151.7–165.1 bpm) throughout the 100IT but did not during the 200IT (160.1–173.5 and 157.3–167.8 bpm, respectively) (p < .05). Moreover, the mean SL during the 100IT was significantly lower in R1 than in R2 (p < .05). However, the HR and RPE increased significantly in both 100IT and 200IT irrespective of rest periods (p < .05). Therefore, all IT sets were appropriate conditions for endurance training. Rest periods may have influenced the physiological and mechanical stimulation in the 100IT at CV, suggesting that aerobic metabolism differs between conditions.
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RODRIGUEZ F.A. Metabolic Evaluation of Swimmers and Water Polo Players. Kinesiology, Vol. 2, No. 1, pp. 19-29, 1997. The evaluation of the metabolic capacity of swimmers and water polo players has experienced considerable change in the last years, mainly because of more specific field methods. Lactate testing is a paradigm of this development. However, certain restrictions in measuring the aerobic energy expenditure are still imposed by the apparatus required to collect expired gases (free swimming) or by the modifications ot the swimming mechanics (flume or tethered swimming). Even if these difficulties did not prevent to investigate many aspects of the physiological response of the swimming man, they obviously restrict the full expression of performance capacity in specific pool conditions. In order to overcome these barriers, an evaluation procedure based on the combination of oxygen uptake and blood lactate measurements in field conditions for the comprehensive metabolic evaluation of swimmers and water polo players has been developed. The procedure is based on simultaneous measurement of oxygen uptake and blood lactate accumulation during free unimpeded swimming using breath by breath gas analysis and capillary blood samples during the immediate recovery period after three swims at different velocity over 400 and 100-m (Rodriguez 1994). Direct measurements during an experimental discontinuous swimming protocol helped in providing information about different aspects of the metabolic response of competitive aquatic athletes and the evidence has been used to implement the evaluation method. Aerobic power is evaluated from peak VO2 measurements after a maximal 400-m swim. Aerobic endurance capacity is evaluated from the relationship between blood lactate accumulation and swimming velocity in two 400-m swims Mader et al. 1976). The anaerobic contribution is estimated from the energy equivalent of lactate accumulation in blood (di Prampero et al. 1978). Swimming economy at different swimming velocities can also be explored taking into consideration total energy expenditure. Differential VO2 increase between two swims at maximal velocity (400 and 100-m) is taken as an indicator of individual oxygen kinetics. A calculation scheme based on individual swimming energetics allows for the estimation of the maximal rate of aerobic and anaerobic energy expenditure in middle and short distance swimming. The metabolic profile of male and female swimmers, and male water polo players during front crawl swimming using this method is compared and the practical applications and limitations of the testing procedure are presented and discussed.
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Recently, a respiratory snorkel (Toussaint et al. 1987) has been adapted for breath-by-breath gas analysis using a portable metabolic cart (Keskinen et al. 2000). The aim of this study was to characterize the oxygen uptake (VO2)1 kinetics during 100 and 400 m maximal swims in a group of trained athletes. Fourteen competitive swimmers aged 16-23 years (10 males; 4 females), performed two swims (100 and 400 m freestyle) at maximal speed breathing through the new respiratory snorkel. VO2 data, as analysed by a portable gas analyser, were averaged every 5 s and fitted to mono-exponential functions. Peak VO2 significantly correlated with swimming speed (p < .05) both in 100 m (r = .787) and 400 m (r = .752), but the time constant ( τ) did not. VO2 kinetics was faster during the 100-m as compared with the 400-m swim (p < .01). The procedure using the respiratory snorkel together with the portable metabolic cart was proven to be a feasible method for analysing VO2 kinetics during free swimming. The results clearly showed that VO2 kinetics depend on the swimming intensity, the response being faster in 100m. Peak VO2 showed to be a good predictor of swimming performance in 100 and 400 m. Further investigation is needed to better define VO2 kinetics in different groups of swimmers.
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We present a method for quantifying the anaerobic capacity based on determination of the maximal accumulated O2 deficit. The accumulated O2 deficit was determined for 11 subjects during 5 exhausting bouts of treadmill running lasting from 15 s to greater than 4 min. The accumulated O2 deficit increased with the duration for exhausting bouts lasting up to 2 min, but a leveling off was found for bouts lasting 2 min or more. Between-subject variation in the maximal accumulated O2 deficit ranged from 52 to 90 ml/kg. During exhausting exercise while subjects inspired air with reduced O2 content (O2 fraction = 13.5%), the maximal O2 uptake was 22% lower, whereas the accumulated O2 deficit remained unchanged. The precision of the method is 3 ml/kg. The method is based on estimation of the O2 demand by extrapolating the linear relationship between treadmill speed and O2 uptake at submaximal intensities. The slopes, which reflect running economy, varied by 16% between subjects, and the relationships had to be determined individually. This can be done either by measuring the O2 uptake at a minimum of 10 different submaximal intensities or by two measurements close to the maximal O2 uptake and by making use of a common Y-intercept of 5 ml.kg-1.min-1. By using these individual relationships the maximal accumulated O2 deficit, which appears to be a direct quantitative expression of the anaerobic capacity, can be calculated after measuring the O2 uptake during one exhausting bout of exercise lasting 2-3 min.
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In this study the gross efficiency of swimming was determined in a group of male (N = 6) and female (N = 4) competitive swimmers. The gross efficiency is defined as the ratio of the power output (W) to the power input (W). In a range of swimming velocities (0.95-1.6 m.s-1), the power input (rate of energy expenditure, 445-1137 W) was calculated from the oxygen uptake values (1.33-3.25 1 O2.min-1). The total power output (26-108 W) was directly measured during front crawl swimming using a system of underwater push-off pads instrumented with a force transducer (MAD-system). Using the MAD-system, the effect on total body drag due to the addition of the respiratory apparatus was evaluated to be negligible. The gross efficiency ranged from 5 to 9.5%. At equal swimming speed, the male competitive swimmers demonstrated a higher gross efficiency. However, this was due to the higher power output required by the male swimmers at a given speed. Gross efficiency was dependent on the absolute power output such that as power output increased so did the calculated gross efficiency. At the same power output, the values for the gross efficiency do not differ between the male and female competitive swimmers.
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The energy cost of the forms of locomotion discussed throughout this article is summarized in Table 9. This table, as well as the preceding sections of this article, are designed to provide a rather comprehensive and simple set of information for potential readers: medical doctors, who should be able to prescribe to their patients (obese, hypertensive, cardiac, etc.) the correct amount and type of exercise, thus making use of exercise as of any other drug, of which it is imperative to know posology and contraindications; athletes, trainers, and sportsmen in general, who should gear correctly their diet to the type and amount of physical exercise; physical educators, who should be aware of the specific characteristics of the exercise modes they propose to their pupils, as a function of their sex, age, and athletic capacity. However, besides these practical applications, the notions discussed throughout this article bear also a more general interest. Indeed, they allow a better understanding of the motion of man, that is, of the only machine, which besides moving about, also tries to understand how he does it.