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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

PlanPlan

•1) Introduction: calorimétrie

•2) Études récentes : marche, course à pied, cyclisme, ski…

•3) Conclusions

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).

Overview of energy expenditure studies on cycling

l 1000 km cycling study

l Energy expenditure & substrate oxidation in the chamber

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

Calorimètre indirecte

Fixe

Labo Terrain

Portable

Objectif

Chambres calorimétriques

The “old” (XXth century) respiration chamber of Lausanne

Mesures sur le terrain

DDéépense pense éénergnerg..+ Quotient Resp.+ Quotient Resp.

(VCO2 / VO2)(VCO2 / VO2)

•VO2

•VCO2

• Nu

MesurMesuréé CalculCalculéé CalculCalculéé

Oxidationdes substrats(CHO/Lip/Prot.)

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.)

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

UTILISATION D’ISOTOPES STABLES

H2O doublement marquée

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%

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

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

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

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

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

DDéépense Energpense Energéétiquetique

CalculCalculééee EstimEstimééee

• Calo. indirecte• Calo. directe

• Fréquence card.• Accelérométrie• Autres

Validation

« Proxy » values ofindirect calorimetry

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

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%

Home made accelerometer:

« self contained activity monitor »

SCAM

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]

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

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)

Relationship between speed of walking & acceleration (Henriksen, 2004)

Vs= vector sum, V= vertical, ML= medio-lateral, AP= anteroposterior

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

Accelerometer(SCAM)

Energyexpenditure

Activityprofile

Acceleration(RMS)

Activity detection

Walking Other activities

Continuouswalking

Discontinuouswalking

Walkingspeed

Walkingduration

Walkingdistance

Incline

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)

A new approach to dissect walking activities in free-living conditions

Daily physical activity pattern in 8 subjects during 8 hours: red=inactivity

ACCELEROMETRIE:Etudes de validation

Overview of experimental studies in the metabolic chamber

Validation of 2 diff. Accelerometers

lTritrac/CaltraclLifecorder

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

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 .

Accelerometers usedLifecorder, Japan; 40g

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

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

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

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)

Two Accelerometers usedLifecorder, Japan; 40g

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

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

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.

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).

Global positioning system(GPS)

– speed of displacement outdoor

– distance walked

– ∆ altitude

– trajectory of displacement

GPS receivers

• 1) Modèles PRO: - Leica (CH) , Topcon-Javad (USA)…

- sampling: 10-100 Hz

• 2) Modèle de loisirs: - Garmin,Magellan…-sampling: 0.5-1Hz.

GPS differentiel

CoordinateX, Y, Z

CoordinateX’, Y’, Z’

Data correction

(post-processing)

Receiver 2Moving individual (roverreceiver)

Receiver 1Fixed base reference station

GPS satellites

GPS equipement

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)

Utilisation du positionnement par satellites (GPS) pour l’évaluation et l’amélioration de la performance des athlètes lors d’exercices dynamiques:

Yves.Schutz@unil.ch

Crans-Montana

Lauberhorn

Application au ski de descente

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

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

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

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)

Variations de vitesse et distance cumulée lors d’un match de football

Variations de vitesse et fréquence cardiaque lors d’un match de football

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

)

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

)

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).

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

Assessment of gait parameters

GPS de haute précision

En plan

altitude

Overview of experimental studies on cycling

- 1000 km cycling study

- Energy expend. & substrate ox. in the chamber

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

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

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

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

Biomechanical characterisation of cycling

and calculated metabolic heat production

Mechanicalpower

Metabolicpower

Total EnergyExpenditure

Resting metab. rate + Thermogenesis

Torque

Cadence

ηsubjectbicycle

E balance calculation

Food Intake Total E Intake

MechanicalPower output

Total E Exp.

E balance

∆ Body composition (fat vs lean tissues)

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

Macronutrient intakes during the event

% Energy

Cyclists Protein CHO Fat

A* 7 66 27

B 7 68 25

C 7 63 30ARES project*vegetarian

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

∆ 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

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

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

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

Overview of experimental studies on cycling

- 1000 km cycling study

- Energy expend. & substrate ox. in the chamber

Sosie de Pantani

Sosie d’ ARMSTRONG

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

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)

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)

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!

SENSE WEAR ARMBAND

QuickTime™ et undécompresseur TIFF (LZW)sont requis pour visionner cette image.

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…

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

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

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