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Quadrant analysis: Quadrant analysis: theory theory Andrew R. Coggan, Ph.D.
19

Webinar on qa

Jan 14, 2015

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Webinar for USA Cycling Coaching Education program.
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Page 1: Webinar on qa

Quadrant analysis:Quadrant analysis:theorytheory

Andrew R. Coggan, Ph.D.

Page 2: Webinar on qa

What is quadrant analysis?What is quadrant analysis?

Quadrant analysis is a graphical tool for analyzing powermeter data to provide insight into the neuromuscular demands of a particular race or training session. A better understanding of such demands can be helpful not only for optimizing training but also behaviors during races themselves.

Page 3: Webinar on qa

Quantifying the neuromuscular Quantifying the neuromuscular demands of training and racing: demands of training and racing:

AEPF and CPVAEPF and CPV

Average effective pedal force (AEPF) =(power • 60)/(cadence • 2 • Pi • crank length)

Circumferential pedal velocity (CPV) =(cadence • 2 • Pi • crank length)/60

Page 4: Webinar on qa

Frequency distribution histogram of Frequency distribution histogram of AEPF during a level 3 training rideAEPF during a level 3 training ride

Page 5: Webinar on qa

AEPF-CPV relationshipAEPF-CPV relationshipduring a level 3 training rideduring a level 3 training ride

Page 6: Webinar on qa

AEPF-CPV-time relationshipAEPF-CPV-time relationshipduring a level 3 training rideduring a level 3 training ride

Page 7: Webinar on qa

Statement of the problemStatement of the problem

Simply plotting AEPF and CPV, even against each other and/or time, primarily tells you what you actually did during a particular race or training session, and provides only limited insight into the impact that had/is likely to have upon you from a physiological perspective.

Page 8: Webinar on qa

Muscle force-velocity andMuscle force-velocity andpower-velocity relationshipspower-velocity relationships

Maximal force (Fo)

Maximal velocity(Vmax)

Maximal power (Pmax)

Page 9: Webinar on qa

AEPF-CPV andAEPF-CPV andpower-CPV relationshippower-CPV relationship

Maximal AEPF (= Fo)

Maximal CPV(= Vmax)

Maximal power (Pmax)

Page 10: Webinar on qa

Maximal AEPF-CPV and Maximal AEPF-CPV and submaximalsubmaximal power power

Page 11: Webinar on qa

Fiber type recruitment as a function of Fiber type recruitment as a function of exercise intensityexercise intensity

0

20

40

60

80

100

25 50 75 100

% f

ibe

rs r

ec

ruit

ed

at

on

se

t o

f e

xe

rcis

e

% of VO2max

Type I

Type IIa

Type IIb

Total

Vollestad et al. Acta Physiol Scand 125:395-405, 1985

Page 12: Webinar on qa

EMG activity as a function of cadenceEMG activity as a function of cadence

MacIntosh, Neptune, and Horton, Med Sci Sports Exerc 2000; 32:1281-1287

Page 13: Webinar on qa

Fiber type recruitment as a Fiber type recruitment as a function of cadencefunction of cadence

Ahlquist et al., Eur J Appl Physiol 1992; 65: 360-364.

Page 14: Webinar on qa

Maximal AEPF-CPV and powerMaximal AEPF-CPV and power

Page 15: Webinar on qa

AEPF vs. CPV during flat time trialAEPF vs. CPV during flat time trial

Page 16: Webinar on qa

AEPF vs. CPV during flat time trialAEPF vs. CPV during flat time trial

Page 17: Webinar on qa

QA of flat time trialQA of flat time trial

Page 18: Webinar on qa

QA of 6 x 1 km from standing startQA of 6 x 1 km from standing start

Page 19: Webinar on qa

QA with data from different PMsQA with data from different PMsRide #1

Ride #2