The document presents a study analyzing the relationship between estimated cardiorespiratory fitness (VO2max) and real-life running performance in free-living individuals. The study: 1) Built VO2max estimation models using heart rate and running data collected from wearable devices. 2) Deployed the models to estimate VO2max in over 500 free-living runners. 3) Found strong correlations between estimated VO2max and reference running performance times over 10km, half marathon, and marathon distances, validating that estimated VO2max can serve as a useful proxy for endurance performance.

1. Relation Between Estimated Cardiorespiratory
Fitness and Running Performance in Free-
Living: an Analysis of HRV4Training Data
International Conference on Biomedical and Health Informatics. Orlando, 2017!
HRV4Training.com!
Marco Altini, Chris Van Hoof and Oliver Amft!

2. 2!
MEASURING BEHAVIOR VS MEASURING HEALTH &
PERFORMANCE
BHI, 2017! HRV4Training.com!
Research as well as consumer products have been mainly
focusing on measuring behavior (steps, calories, activities
performed, etc.)!
!
!
These approaches have limitations, behavioral aspects are
important (what we do) but to implement effective
interventions and provide relevant feedback we should
quantify changes in our health and performance
(potentially resulting from behavioral interventions)!

3. 3!
HOW DO WE QUANTIFY HEALTH AND
PERFORMANCE?
BHI, 2017!
Cardiorespiratory fitness is a key health parameter and
performance indicator in endurance sports
!
It refers to the ability of the cardiorespiratory system to
provide oxygen to muscles during physical activity!
!
Regular exercise improves these processes (bigger heart
muscle which reflects into more blood being pumped with
each beat, more arteries in trained skeletal muscles, etc.)!
HRV4Training.com!

4. 4!
HOW DO WE MEASURE CARDIORESPIRATORY
FITNESS?
BHI, 2017! HRV4Training.com!
VO2max tests: gold standard,
maximal oxygen uptake during
incremental exercise!
!
Impractical: infrastructure and
personnel required!
!
Submaximal tests: limited effort,
typically still require a certain
exercise to be performed (e.g. run at
a certain intensity)!
!

5. 5!
SUBMAXIMAL AND NON-EXERCISE TESTS
BHI, 2017! HRV4Training.com!
Recent developments showed that VO2max can be
estimated with good accuracy during activities of daily living!
!
However, we typically stop here!
!

6. 6!
SUBMAXIMAL AND NON-EXERCISE TESTS
BHI, 2017! HRV4Training.com!
Recent developments showed that VO2max can be
estimated with good accuracy during activities of daily living!
!
However, we typically stop here!
!
Many questions remain unanswered. Is the sub-maximal
estimate sufficiently accurate? What does it mean in practical
terms? Can we use estimated VO2max as a proxy of
performance? How do we validate the usefulness and
practical applicability of our estimates? !

7. 7!
BHI, 2017! HRV4Training.com!
1. Build VO2max estimation models relying on data that
can be acquired in free-living without specific protocols:
no effort required on the subject/user side. Validate these
models in the lab.!
2. Deploy VO2max estimation models in free-living on a
large set of study participants (500+)!
3. Collect reference data related to human performance to
evaluate the relation between performance and estimated
VO2max and determine it’s usefulness in unsupervised
free-living settings
OUR APPROACH

8. 8!
1. BUILD VO2MAX ESTIMATION MODELS
BHI, 2017! HRV4Training.com!
48 participants (22 male, 26 female), ECG and indirect
calorimetry were acquired while running at different speeds
and during a VO2max test on a cycle ergometer. To keep
speed unconstrained we included as predictor the running
speed to heart rate ratio in our VO2max estimation model
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R=0.72
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Predicted VO2max
ReferenceVO2max
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ReferenceVO2max
Training − VO2max (ml/kg/min)
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Mean, (Reference + Fitted)/2
Residuals
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Residuals
Bland−Altman − Training − VO2max (ml/kg/min)

9. 9!
2. DEPLOY VO2MAX ESTIMATION MODELS
BHI, 2017! HRV4Training.com!
HRV4Training app: spot check for resting
physiological data (heart rate, heart rate
variability). Camera based, low cost, low
barrier. Currently 14K+ users!
!
Training data: HRV4Training links to Strava
and can collect workouts data (running
pace, speed, heart rate, etc.)
!
Models built in the lab were deployed to
users meeting certain criteria (app link to
Strava, training with a heart rate monitor, 6
weeks of data and 12 workouts available)

10. 10!
BHI, 2017! HRV4Training.com!
Real life running performance was determined as the best
time over “standard” running distances, such as the
10km, half marathon and full marathon. Running times were
acquired from HRV4Training via the Strava integration over a
period of one to 8 months
!
Runners were also clustered in categories based on running
time over the three distances (fast, average, slow)!
!
!
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3. COLLECT REFERENCE DATA

11. 11!
BHI, 2017! HRV4Training.com!
RELATION BETWEEN ESTIMATED VO2MAX AND
REAL-LIFE RUNNING PERFORMANCE
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R=−0.6
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0.6 0.8 1.0
<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
Category
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Fast
Average
Slow
Gender
● Female
Male
a) Best 10km time in relation to VO2max
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R=−0.56
60
70
tedVO2max
b) Best half marathon time in relation to VO2max
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R=−0.61
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60
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
c) Best marathon time in relation to VO2max
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60
70
tedVO2max
d) Runner category and VO2max (all users)

12. 12!
BHI, 2017! HRV4Training.com!
RELATION BETWEEN ESTIMATED VO2MAX AND
REAL-LIFE RUNNING PERFORMANCE
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R=−0.6
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
Category
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Fast
Average
Slow
Gender
● Female
Male
a) Best 10km time in relation to VO2max
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R=−0.56
60
70
tedVO2max
b) Best half marathon time in relation to VO2max
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R=−0.61
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60
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
Gender
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Male
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
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Fast Average Slow
EstimatedVO2max
d) Runner category and VO2max (all users)

13. 13!
BHI, 2017! HRV4Training.com!
RELATION BETWEEN ESTIMATED VO2MAX AND
REAL-LIFE RUNNING PERFORMANCE
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
Category
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Average
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Gender
● Female
Male
a) Best 10km time in relation to VO2max
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R=−0.56
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tedVO2max
b) Best half marathon time in relation to VO2max
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R=−0.61
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)
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EstimatedVO2max
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EstimatedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
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EstimatedVO2max
d) Runner category and VO2max (all users)
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EstimatedVO2max
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Gender
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a) Best 10km time in relation to VO2max
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tedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)

14. 14!
BHI, 2017! HRV4Training.com!
RELATION BETWEEN ESTIMATED VO2MAX AND
REAL-LIFE RUNNING PERFORMANCE
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EstimatedVO2max
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a) Best 10km time in relation to VO2max
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tedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)
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EstimatedVO2max
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EstimatedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
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EstimatedVO2max
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EstimatedVO2max
Category
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Gender
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Male
a) Best 10km time in relation to VO2max
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R=−0.56
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tedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)
Moderate to strong correlation for all running
distances (r = 0.56-0.61)

15. 15!
BHI, 2017! HRV4Training.com!
RELATION BETWEEN ESTIMATED VO2MAX AND
REAL-LIFE RUNNING PERFORMANCE
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<− Faster −−− Time (hours) −−− Slower −>
EstimatedVO2max
Category
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Average
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Gender
● Female
Male
a) Best 10km time in relation to VO2max
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R=−0.56
60
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tedVO2max
b) Best half marathon time in relation to VO2max
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R=−0.61
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EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)
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EstimatedVO2max
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EstimatedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
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EstimatedVO2max
d) Runner category and VO2max (all users)
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EstimatedVO2max
Category
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Gender
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Male
a) Best 10km time in relation to VO2max
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tedVO2max
b) Best half marathon time in relation to VO2max
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EstimatedVO2max
c) Best marathon time in relation to VO2max
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tedVO2max
d) Runner category and VO2max (all users)
Moderate to strong correlation for all running
distances (r = 0.56-0.61)

16. 16!
BHI, 2017! HRV4Training.com!
RELATION BETWEEN ESTIMATED VO2MAX AND
REAL-LIFE RUNNING PERFORMANCE
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− Time (hours) −−− Slower −>
hon time in relation to VO2max
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Fast Average Slow
EstimatedVO2max
d) Runner category and VO2max (all users)

17. 17!
BHI, 2017! HRV4Training.com!
CONCLUSIONS AND FUTURE WORK
We could provide confirmative insights on the feasibility of!
using sub-maximal HR to estimate fitness level in free-
living, and use such estimated fitness level as a metric
representative of running performance !
!
Estimated VO2max can potentially be used to track
individual performance outside laboratory settings,
driving motivation and helping athletes of all levels keep
track of progress as well as adopt individualized training
plans based on a person’s physiological response to training!
!
Individual variance should be further investiaged!

18. Thank you
Marco Altini, PhD !
!
altini.marco@gmail.com!
@marco_alt!
International Conference on Biomedical and Health Informatics. Orlando, 2017!
HRV4Training.com!