DEPENSES ENERGETIQUES - Jussieu · Overview of experimental studies involving GPS l Downhill...
Transcript of DEPENSES ENERGETIQUES - Jussieu · Overview of experimental studies involving GPS l Downhill...
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DEPENSES ENERGETIQUESDes Changements depuis le
XXème siècle ?• Principes nouveaux ?
• Mesures nouvelles ?
• Équations (algorithmes de calcul)?
• Utilisations nouvelles
• Idées nouvelles ?
Yves SCHUTZ LAUZANNE Mai 2005
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PlanPlan
•1) Introduction: calorimétrie
•2) Études récentes : marche, course à pied, cyclisme, ski…
•3) Conclusions
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Overview of experimental studies involving GPS
l Downhill skiing: trajectory & speed
l (Estimate of VO2max based on running speed and heart rate)
l Analysis of displacement and speed profile during a soccer game
l Assessment of gait parameters (speed, step length & frequency, walk ratio).
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Overview of energy expenditure studies on cycling
l 1000 km cycling study
l Energy expenditure & substrate oxidation in the chamber
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RemerciementsCollaborateurs + investigateurs
• Dr P. Terrier, Lausanne• Pre-doc V. Lecoultre, Lausanne• Pr H. Tanaka, Dr H. Kumahara, Fukuoka • Pr J-M Oppert, Paris• Dr U. Maeder, Macolin• M O. Pasche, Lausanne• M A. Biciato, Vevey• M F. Fuso, Lausanne
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Calorimètre indirecte
Fixe
Labo Terrain
Portable
Objectif
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Chambres calorimétriques
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The “old” (XXth century) respiration chamber of Lausanne
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Mesures sur le terrain
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DDéépense pense éénergnerg..+ Quotient Resp.+ Quotient Resp.
(VCO2 / VO2)(VCO2 / VO2)
•VO2
•VCO2
• Nu
MesurMesuréé CalculCalculéé CalculCalculéé
Oxidationdes substrats(CHO/Lip/Prot.)
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RecentlyRecently proposedproposed equationequation for for thethe calculationcalculation ofof carbohydratecarbohydrate(CHO) (CHO) ofof oxidationoxidation fromfrom gasgas exchangeexchange measurementsmeasurements
((JeukendrupJeukendrup, 2004), 2004)
1
2
Low intensity exercise (40-50% VO2 max)
Moderate intensity exercise (50-75% VO2 max)
CHO ox = 4.344 x VCO2 – 3.061 x VO2 - 0.4 Nu(50% Gluc / 50% Glycog.)
CHO ox = 4.21 x VCO2 – 2.962 x VO2 - 0.4 Nu(20% Gluc / 80% Glycog.)
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Fat oxidation per unit distance vs speed of walking in obese & nonobese
2 2.8 3.5 4.20.03
0.04
0.05
0.06
0.07
0.08
0.09
Fat
oxi
dati
on(g
/kg•
km)
Speed (km/h)
Fat oxidation Obese
Fat oxidation Non-obese
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UTILISATION D’ISOTOPES STABLES
H2O doublement marquée
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Naturally enriched 13C-foods used in human tracer studies
13C abundances(%)
– Corn oil 1.095– Tropical fruits (pineapple) 1.097– Saccharose (cane sugar) 1.097– Corn 1.099
ReferenceReference value:value:EuropeanEuropean breathbreath = 1.085%= 1.085%
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Evaluation du métabolisme des CHO par utilisation des isotopes stables
• CHO « breakdown »= CHO ox – exog. CHO ox
• CHO « synthesis »= exog. CHO in – exog. CHO ox.
Calo. Ind. C13
Apports C13
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Labelled Carbohydrates
0
0.001
0.002
0.003
0.004
0.005
0.006
08:00
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
Clock Time (hh:mm)
Ex
pir
ed
13C
en
ric
hm
en
t (D
elt
a %
)
Lean
obese
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Measuring oxidation of ingested glucoseC6H12O6 + 6O2 6CO2+ 6H2O + 36ATP
Ingestion of a 13C-labeled CHO drink (13C-glucose/12C-glucose)
Digestion AbsorptionOxidation
Collection of breath samples for 13CO2/12CO2 ratio
Jeukendrup. 2005
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Exogenous CHO oxidation studies
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.0 1.0 2.0 3.0
GlucoseFructoseGalactoseSucroseMaltoseMDStarch
Jeukendrup and Jentjens Sports Med 29 (6): 407-424, 2000
Exogenous CHO oxidation rate (g/min)
CHO ingestion rate (g/min)Jeukendrup. 2005
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Exogenous CHO oxidation is limitedExogenous CHO oxidation is limited
Muscle
BloodGlucose
Liver
Gastrointestinal tract
Glucose ingestion
> 2.0 g/min
glycogen
~1.0 g/min
~1.0 g/min
CO2
Jeukendrup and Jentjens Sports Med 29 (6): 407-424, 2000
~1.0 g/min
Jeukendrup. 2005
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DDéépense Energpense Energéétiquetique
CalculCalculééee EstimEstimééee
• Calo. indirecte• Calo. directe
• Fréquence card.• Accelérométrie• Autres
Validation
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« Proxy » values ofindirect calorimetry
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Daily Physical Activities
Segmental body Movements
Postures and transitions
Locomotion
Upper limbs movement
Lower limbs movement
Walk
Run
Bike
Lie
Sit
Stand
Trunk Movements
Transitions
IDEAL Model
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0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Lying down sitting standing
Effect of posture on energy expenditure
Excess EE
Basal EE
+20% +50%
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Home made accelerometer:
« self contained activity monitor »
SCAM
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Analysis of data
0 2 4 60
0.05
0.1
1c. Speed vs. RMS calibration
thr. 0= 0.02
thr. 1= 0.04
thr. 2= 0.09
r= 0.99
speed [km/h]
RMS [g]
0 2 4 6 8 100
0.01
0.02
0.03
0.04
frequency [Hz]
PSD
1.72Hz
1d. Stride frequency determination
0 5 10 15-0.2
0
0.21a. Raw accelerometric signal
time [s]
acc. [g]
0 20 40 60 80 1000
0.05
0.11b. Raw RMS
time [min.]
RMS [g]
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Pattern of physical activity
10 15 20 25 30 350
0.02
0.04
0.06
0.08
1e. Activity level during the day
Time in hours (17 hrs recorded)
RMS [g] thr. 0 = 0.02
thr. 1 = 0.04
thr. 2 = 0.09
83.4 % inactive7.0 % low7.8 % medium1.7 % high
Total percentage of activity at each level
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1 2 3 4 5 6 7 80
0.05
0.1
0.15
0.2
0.25
RMS (g)
Speed (km/h)
Relationship between speed and RMS
SPEED (km/h)
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Relationship between speed of walking & acceleration (Henriksen, 2004)
Vs= vector sum, V= vertical, ML= medio-lateral, AP= anteroposterior
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10 min. Walking: 3 different patterns
0
2
4
6
8
spee
d (k
m/h
)10 min. continuous walking
0
2
4
6
8
spee
d (k
m/h
)
5 x 2 min. discontinuous walking
0 20 40 60 80 100 1200
2
4
6
8
spee
d (k
m/h
)
time (min.)
40 x 15sec. walking bursts
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Accelerometer(SCAM)
Energyexpenditure
Activityprofile
Acceleration(RMS)
Activity detection
Walking Other activities
Continuouswalking
Discontinuouswalking
Walkingspeed
Walkingduration
Walkingdistance
Incline
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Analysis of walking by 3D accelerometry
1) ”Continuous” walking: > 1 minute
2) “Discontinous walking: < 1 minute (splitted)
3) Non-locomotor activ.: non-rythmic, low level
4) Inactivity: by delta = total time - (1+2+3)
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A new approach to dissect walking activities in free-living conditions
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Daily physical activity pattern in 8 subjects during 8 hours: red=inactivity
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ACCELEROMETRIE:Etudes de validation
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Overview of experimental studies in the metabolic chamber
Validation of 2 diff. Accelerometers
lTritrac/CaltraclLifecorder
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Etude Paris_Lausanne
Compa rative eval uatio n of day -time energy expend iture by
uni- and tri-axial acc elerometry vs . room calori met ry
JEAN-MICHEL OPP ERT 1, AN NE LLUCH 1,2, PH ILIPPE TERR IER2,
DOMIN IQU E DUR RER 2, BER NA RD GUY-G RAND1, YVE S SCH UTZ2
1Depa rtment of Nutrition, Hôte l-D ieu H ospital, Un ive rs ity Pierre-et-Mar ie
Cu rie (Par is VI) , Pa ris, France;
2Inst itu te of P hysiology , University o f Lausanne , Lausanne, Swi tzerland
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RESULTATS
T ab le 3 . T o t a l ( E E tot ) a n d act iv ity - re la te d ( EE a ct ) en e r g y ex pe n d it u r e
ass e ss e d by r o o m ca lo r ime t r y a n d acc ele ro met ry
E E tot
( k J ⋅9 h -1 )
E E a ct
( k J ⋅9 h -1 )
R oo m cal o r im e te r
T r it rac
C a lt r ac
T r it rac m in us ca lor im e te r
C a lt r ac mi n u s cal o r im ete r
44 8 7 ± 762
41 8 9 ± 618
47 6 7 ± 110 1
- 2 98 ± 482
28 0 ± 1154
20 0 5 ± 618
15 2 1 ± 398
20 9 2 ± 102 8
- 4 85 ± 442
86 ± 1 219
Va lu es ar e m e a n s ± S D .
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Accelerometers usedLifecorder, Japan; 40g
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Basal Metabolic Rate (kcal/4sec)
Physical Activity Related EE(kcal/4sec)
Total Daily EE (kcal/day)
Anthropometric data Age, Sex, Height, Weight
-Vertical (z) direction-Sampling rate=32Hz-Acceleration range= up to 1.94G
Activity levels (11-levels)
x Time (duration)
Accelerometer features
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Accelerometer output vs METSM
ETs
Activity levels of the accelerometer
FIGURE 5.
1
2
3
4
5
6
7
8
9
0 1 2 3 4 5 6 7 8 9
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500
1000
1500
2000
2500
3000
TE
E
(kca
l/d
ay)
Male(N=48)
Female(N=67)
1.0
1.2
1.4
1.6
1.8
2.0
PA
L F
ree-l
ivin
g
1.0 1.2 1.4 1.6 1.8 2.0
PAL Chamber
Male
Female
r=0.747, p<0.001
x=y
TEE measured in the chamber vs.TEE infree-living assessed by accelerometry
P<0.001
P<0.001
1.5
3
PA
L=
1.4
6
1.5
1
1.4
6
Ch
am
ber
Ch
am
ber
Fre
e-l
ivin
g
Fre
e-l
ivin
g
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Relationship between activity level & energyexpenditure (EE) by periods of 15 min.
FIGURE 3.
EE
Activity level of the accelerometer
1
2
3
4
5
6
7
8
9
0 1 2 3 4 5 6 7 8 9
5
15
10
25
20
30
35
(kcal/kg/h) (kJ/kg/h)
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Two Accelerometers usedLifecorder, Japan; 40g
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Effect of moderate fidgeting* while watching TV in young women
0.2
0.4
0.6
0.8
1
1.2
1.4
En
erg
y e
xp
en
dit
ure
20
40
60
80
Heart ra
te(kcal/min) (bpm)
No Fidg. Fidg.No
Fidgeting increased EE by 20% and HR by 10% (Schutz, 1989)
(n=6)
* agitation/tonique
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ACwristACwaist
1
2
3
4
5A
ctiv
ity levels
of
wais
t &
wri
st
0
20
40
60
80
100
% o
f A
ctiv
ity
1
2
3
4
5
En
erg
y e
xp
en
dit
ure
(kca
l·kg
-1·h
-1)
9:00
10:00
11:00
12:0013
:0014
:0015
:00
16:0017
:00
18:0019
:0020
:00
21:0022
:00
23:008:30(hours)
% activity (radar)Energy Expend.
Time course of measured indices during day-time
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CONCLUSION
- Movements of the upper limb are proportionally more important than that of the whole body for sedentary activities, however, its contribution to EE is lower.
- The high inter-individual variability of the ratio (Wrist/Waist) in the former situation confirms that fidgeting like activitieslargely vary among subjects, despite performing similar tasks.
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Overview of experimental studies involving GPS
l Downhill skiing: trajectory & speed
l (Estimate of VO2max based on running speed and heart rate)
l Analysis of displacement and speed profile during a soccer game
l Assessment of gait parameters (speed, step length & frequency, walk ratio).
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Global positioning system(GPS)
– speed of displacement outdoor
– distance walked
– ∆ altitude
– trajectory of displacement
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GPS receivers
• 1) Modèles PRO: - Leica (CH) , Topcon-Javad (USA)…
- sampling: 10-100 Hz
• 2) Modèle de loisirs: - Garmin,Magellan…-sampling: 0.5-1Hz.
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GPS differentiel
CoordinateX, Y, Z
CoordinateX’, Y’, Z’
Data correction
(post-processing)
Receiver 2Moving individual (roverreceiver)
Receiver 1Fixed base reference station
GPS satellites
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GPS equipement
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Overview of experimental studies involving GPS
l Downhill skiing: trajectory & speed
l (Estimate of VO2max based on running speed and heart rate)
l Analysis of displacement and speed profile during a soccer game
l Assessment of gait parameters (speed, step length & frequency, walk ratio)
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Utilisation du positionnement par satellites (GPS) pour l’évaluation et l’amélioration de la performance des athlètes lors d’exercices dynamiques:
Crans-Montana
Lauberhorn
Application au ski de descente
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BUT & METHODE• But
– Mesurer le profil de vitesse instantanée et la trajectoire d’un skieur lors d ’une descente ou d’un super-G
• Méthode– Système de positionnement par satellite GPS en mode
différentiel– 5 mesures par seconde (vitesse, position)
0 500 1000 1500 2000 2500 3000 35000
20
40
60
80
100
120
Vite
sse
(km
/h)
Distance (m)
Profil de vitesse
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Deux profils de trajectoire à ski
2 9 5 5 2 9 6 0 2 9 6 5 2 9 7 0 2 9 7 5 2 9 8 0 2 9 8 53 8 0
3 9 0
4 0 0
4 1 0
4 2 0
4 3 0
4 4 0
6 6
6 5 . 6
6 5 . 3
6 3 . 6
6 4
6 4 . 4
6 5 . 7
6 7 . 1
6 7 . 4
6 8
6 6 . 8
6 6 . 3
6 8 . 9
6 7 . 56 3 . 3
6 6 . 7
6 1 . 4
6 3 . 1
6 0 . 7
6 2 . 3
6 1 . 7
6 1 . 6
6 1 . 2
6 1 . 1
5 9 . 7
6 0 . 2
6 1 . 6
5 9 . 5
6 0 . 8
6 2 . 56 2 . 7
6 4 . 16 3 . 7
5 8
5 8 . 2
6 0
5 8 . 8
5 7 . 96 0 . 2
6 0 . 96 1 . 1
6 1 . 3
X ( m )
Y (m
)
C o m p a r a i s o n d e t r a j e c t o i r e s
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Importance pour l’entraîneur
• Une fois miniaturisé, le système GPS permettra de mieux comprendre les facteurs -liés à l’individu ou au matériel- qui permettent d’optimaliser les performances lors d’une compétition de descente ou de super-G
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Overview of studies involving GPS in Lausanne
l Analysis of displacement and speed profile during a soccer game: a pilot test
l Downhill skiing: trajectory & speed
l Assessment of gait parameters (speed, step length & frequency, walk ratio).
l (Estimate of VO2max based on running speed and heart rate)
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Variations de vitesse et distance cumulée lors d’un match de football
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Variations de vitesse et fréquence cardiaque lors d’un match de football
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Combined measurements: Portable indirect calorimeter (Energy Expenditure) and GPS receiver (speed)
0 500 1000 15000
5
EE
(K
cal/m
in)
0 500 1000 15000
20
Time (s)
Spe
ed (
km/h
)
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Isolated sprint during a soccer game
1 1.5 2 2.5 3 3.5 4 4.5 5 5.50
5
10
15
20
25
Time (s)
Spe
ed (
km/h
)
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Overview of experimental studies involving GPS
l Downhill skiing: trajectory & speed
l (Estimate of VO2max based on running speed and heart rate)
l Analysis of displacement and speed profile during a soccer game
l Assessment of simple gait parameters (speed, step length & frequency, walk ratio).
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Walking analysis by GPS !
• Duration• Speed (very accurate !)• Topography of terrain (uphill, downhill)• Localisation (inside/outside)/tracking/positioning• « Simple » biomechanical walking characteristics:
• stride frequency (SF)• stride length (SL)• walk ratio (SL/SF)• vertical lift• ∆ speed during gait cycle
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Assessment of gait parameters
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GPS de haute précision
En plan
altitude
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Overview of experimental studies on cycling
- 1000 km cycling study
- Energy expend. & substrate ox. in the chamber
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ARES ARES projectproject**: : 1000 km 1000 km cyclingcycling aroundaround thethelakelake ofof GenevaGeneva (6 laps(6 laps))
– 3 amateur male cyclists performing > 48 hoursof exercise almost continuously (ultra-endurance)
– Departure: Friday p.m./ Arrival: Sunday pm (i.e. 48 hours later)
– Opportunity to organize a study involving severalmotivated investigators, with almost zero budget
* Association pour la Recherche Enfant et Sida
ANECDOTAL study
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ARES projectObjectives
1) To assess the magnitude of energyexpenditure during an ultra-enduranceevent
2) To explore whether energy balance canbe achieved at this extremely highduration of physical activity and to better understand the control of foodintake in these conditions
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MEASUREMENTS (1)1) DURING THE RACE:
– Total food intake at each round
– Power/cadence of cyclists (système EPFL, SRM)
– Speed (odometer)
– Heart rate (Polar)
– Urinary output (per round)
– Body weight, body temperature, blood pressure
– Blood samples
– GPS (topography, total distance, etc…)ARES project
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MEASUREMENTS (2)
2) BEFORE vs AFTER THE RACE:
– Fitness level (VO2max)
– Body weight, somatotyping
– Body composition:
« BODPOD » plethysmography, +BIA, + skinfolds
– Resting energy expenditure / Respiratory Quotient / Heart rate
ARES project
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Biomechanical characterisation of cycling
and calculated metabolic heat production
Mechanicalpower
Metabolicpower
Total EnergyExpenditure
Resting metab. rate + Thermogenesis
Torque
Cadence
ηsubjectbicycle
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E balance calculation
Food Intake Total E Intake
MechanicalPower output
Total E Exp.
E balance
∆ Body composition (fat vs lean tissues)
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ResultsSpontaneous energy intake over 24 h
A 7’690 7’437
B 8’164 8’846
C 7’455 6’949
Cyclists Day 1 Day 2
kcal/d
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Macronutrient intakes during the event
% Energy
Cyclists Protein CHO Fat
A* 7 66 27
B 7 68 25
C 7 63 30ARES project*vegetarian
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Amount of Carbohydrates spontaneouslyingested during the event
A 1’295 1’193
B 1’398 1’443
C 1’237 1’028
Cyclists Day 1 Day 2(g/d)
ARES project
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∆ Body weight & body fat
During the race Before vs after race
∆ kg BW ∆ kg BFCyclist
A -0.5 kg -0.8 kg (-0.9 %)
B -0.3 kg -0.4 kg (-0.6 %)
C -1.1 kg -0.7 kg (-1 %)
ARES project
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Energy balance calculationEx: cyclist B
1) E intake (kcal/d) 8’500
2) E exp. (kcal/d) 12’800
1) - 2) E Balance (kcal/d) - 4’300
3) ∆ Fat stores (kcal/d) - 3’600
Ein – Eout = ∆ E stores
8’500 - 12’800 - 3’600
- 4300ARES project
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Highest Energy Expenditurepublished in the literature
Event Authors Methods EnergyExp. (kcal/24 h)
– Tour de France Saris et al. (1989) 2H2018 7’744
– 24 h. relay running Irwing et al. (1989) Estimation 10’248
– Cross-country skiers Sjödin et al. (1994) 2H2018 7’218
– Australian run Hill et al. (2001) 2H2018 6’550
– ARES project Schutz et al. (subm.) bicycle crank 12’800 dynanometer
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Conclusions1) All three cyclists were not able to maintain energybalance during this extreme prolonged physiologicaldemand. As a result, all subjects lost body weight, explained by a loss of fat tissue.
2) The limit of upper energy expenditure may be higherthan previously reported, but this was at the expense ofalmost continuous exercise over 24 hours involvingtherefore sleep deprivation. This cannot be sustained for more than a couple of days.
3) A huge amount of exogenous carbohydrates (up to 1.4 kg/d) was necessary to avoid depletion of glycogenstores during the event. ARES project
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Overview of experimental studies on cycling
- 1000 km cycling study
- Energy expend. & substrate ox. in the chamber
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Sosie de Pantani
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Sosie d’ ARMSTRONG
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Energy expenditure of cycling (60 min) measured in a respiration chamber
D? pense Energ? tique
0
5
10
15
20
25
W-U 15 30 45 60 Rectemps (min)
kcal/min
Puissance mécanique
0
50
100
150
200
250
300
W-U 15 30 45 60 Rec
temps (min)
W
W-U= warm up
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Heart rate & Respiratory quotient duringendurance cycling
Fréquence cardiaque
0
50
100
150
200
W-U 15 30 45 60 Rectemps (min)
bpm
Quotient Respiratoire
0
0.2
0.4
0.6
0.8
1
1.2
W-U 15 30 45 60 Rectemps (min)
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Energy metabolism during cycling in a calorimetric chamber
-Mean Power : 250 ± 27 W (range : 216-293 W)
-Mean HR : 165 ± 6 bpm (range : 158-174 bpm)
-Mean VO2 : 3727 ml/min (range : 3479-4213 ml/min)
-Mean VO2/kg : 49.4 ml/min/kg (range : 46.3-54.6 ml/min/kg)
-Est. %VO2max : 80-85%
-CHO oxidation: 4.1 ± 0.1 g/min (range : 3.9-4.2 g/min)
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ConclusionsIndirect calorimetry, a 3 century oldtechnique, remains useful for researchbut still relatively expensive.
Cheap instruments seem worthless!
Proxy measurements (heart-rate, + accelero, + GPS,…) are very useful for field work but it seems unrealistic to accurately track EE with thesesystems!
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SENSE WEAR ARMBAND
QuickTime™ et undécompresseur TIFF (LZW)sont requis pour visionner cette image.
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GPS Heart-rateAltimeterAccelerom.
Walking analysis: combination of sensors
+ ++
- Velocity (V) - Distance
- Step Frequency (SF)- Incline -Cardio-vascular
strain- Step Length (SL)
(SL = V / SF)
AllOutside AllAll
Energy expend. ~-body weight, body composition-speed, incline…
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Combinaison de capteurs
200 400 600 800 1000 1200 1400 1600 1800 2000 22000
2
4
6
8vmoy= 4.5909km/h
Fréquence cardiaque moyenne= 134 BPM
RMS Accel (g)
temps (min)
Accélération (Prototype DMC)
10 20 30 40 50 600
0.1
0.2
1) Speed
1) Acceleration
2) Heart-rate
3) Altimetry
4) Positioning
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What is the future ?
SORTIR DU LABO !• Oxydation des substrats exogènes• Mesure de la dépense et de l’oxidation
sur le terrain (conditions réelles)• Modèles biomécaniques & énergétiques
combinés• Utiliser les nouvelles technologies