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Heart rate variability, training & performance

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Heart Rate Variability, Training & Performance @marco_alt Lead Data Scientist @ Bloom Technologies Maker HRV4Training.com PhD Candidate applied Machine Learning @ TU/e [Marco Altini]
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Page 1: Heart rate variability, training & performance

Heart Rate Variability, Training & Performance

@marco_alt Lead Data Scientist @ Bloom Technologies

Maker HRV4Training.com PhD Candidate applied Machine Learning @ TU/e

[Marco Altini]

Page 2: Heart rate variability, training & performance

2012 - 2015

“Runner” / Scientist

Page 3: Heart rate variability, training & performance

2012 - 2015

“Runner”

Page 4: Heart rate variability, training & performance
Page 5: Heart rate variability, training & performance

Genetics?

Page 6: Heart rate variability, training & performance

Yeah, genetics

Page 7: Heart rate variability, training & performance

Almost there

Page 8: Heart rate variability, training & performance

2012 - 2015

Scientist

Page 9: Heart rate variability, training & performance

2009

Page 10: Heart rate variability, training & performance

Cardiorespiratory Fitness Estimation (VO2max)

Energy Expenditure Estimation (kcals) Activity Recognition

PhD (defense next week!) Applied Machine Learning

Eindhoven University of Technology

Page 11: Heart rate variability, training & performance

Making it smaller

Prediction of pregnancy

complications Labour detection

Load Data Scientist Bloom Technologies

Page 12: Heart rate variability, training & performance

Making it smaller

Heart Rate + Heart Rate Variability + Electrohysterography +

Blood Pressure Gestational hypertension prediction

Labour detection Preterm birth

Head of Data Science Bloom Technologies HRV4Training

Page 13: Heart rate variability, training & performance

60 Seconds PPG Measurements

Page 14: Heart rate variability, training & performance

Adapted  from  Tamura  et  al.  Wearable  Photoplethysmographic  Sensors—Past  and  Present  

Page 15: Heart rate variability, training & performance

Adapted  from  Tamura  et  al.  Wearable  Photoplethysmographic  Sensors—Past  and  Present  

Page 16: Heart rate variability, training & performance

•  Accessibility – camera-based data acquisition

•  User generated data & research – Pushing the boundaries on what we

know about the relations between training, lifestyle, physiology and performance

– More users, more parameters, more stratifications (lifestyle factors)

HRV4Training

Page 17: Heart rate variability, training & performance

•  What is heart rate variability (HRV)?

•  How to get the most out of HRV (best practices)

•  What can we do with the data

•  Opportunities from user generated data

Quick outline

Page 18: Heart rate variability, training & performance

2012 - 2015

What is HRV?

Page 19: Heart rate variability, training & performance

Beat to Beat Variation

Page 20: Heart rate variability, training & performance

Heart Rate Variability (HRV) •  Regulated by sympathetic /

parasympathetic branches of the ANS

•  Clear proxy to parasympathetic activity / recovery / body functions at rest – Understand how we react to stressors

Autonomic Nervous System

Page 21: Heart rate variability, training & performance

Higher HRV

Less physiologically stressed

Ready to perform

Lower HRV

More physiologically stressed

Tiredness

This slide is an oversimplification

Page 22: Heart rate variability, training & performance

•  What is heart rate variability (HRV)?

•  How to get the most out of HRV (best practices)

•  What can we do with the data

•  Opportunities from user generated data

Quick outline

Page 23: Heart rate variability, training & performance

2012 - 2015

How to get the most out of HRV measurements?

Page 24: Heart rate variability, training & performance

60 Seconds PPG Measurements

•  Quick snapshot of your physiology (HR+HRV) – Parasympathetic activity

•  Low barrier (fast, convenient, no sensors)

•  Insightful – day to day variability due to external stressors

(training, travel, etc.), long term baseline changes (physical condition, chronic stress)

–  If done properly!

Page 25: Heart rate variability, training & performance

Best Practices for 60 seconds PPG Measurements

•  When to take the measurement

–  Morning, during the day?, etc.

•  What type of measurement –  Lying down, sitting, orthostatic?

•  Paced breathing –  Constrained, unconstrained?

•  What metric to use?

–  Time domain, frequency domain?

•  Are 60 seconds really enough?

Page 26: Heart rate variability, training & performance

When to take the measurement

•  First thing after waking up – Relaxed physiological state – Limit all external stressors – Closest to what we do in research /

clinical studies – Don’t read your email before the

measurement!

Page 27: Heart rate variability, training & performance

What type of measurement

•  Lying down while still in bed – Limits other factors like not waiting

enough after standing up – Performed in clinical studies – Sitting/Standing also valid, however for

simplicity I’d recommend lying down

Page 28: Heart rate variability, training & performance

Paced Breathing (1/3)

•  Improves reliability and repeatability of the measurement – Breathing patterns and RSA have an

impact on HRV values – Using paced breathing provides more

consistent settings (same context!) – Use what works for you (8-12 breaths per

minute typically)

Page 29: Heart rate variability, training & performance

Paced Breathing (2/3)

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Paced Breathing (3/3)

Page 31: Heart rate variability, training & performance

Paced Breathing (3/3)

Page 32: Heart rate variability, training & performance

Consistency!

•  Choose: – A body position – A paced breathing rate – Waking time (more or less) / measurement

routine

Stick to those

Page 33: Heart rate variability, training & performance

What metric to use?

•  HRV is not a single number •  Use rMSSD or ln rMSSD – Marker of parasympathetic activity (only

thing you can reliably measure). There is no clear sympathetic marker

– HF, LF, HF/LF or other frequency domain features require more time (and are computed differently by everyone, difficult to generalize/compare)

Page 34: Heart rate variability, training & performance

Are 60 seconds really enough?

•  Yes. Just follow the best practices

Page 35: Heart rate variability, training & performance

HRV4Training - measurement

Camera view

PPG view

60 seconds timer Breathing bar for paced breathing

Instantaneous heart rate

Page 36: Heart rate variability, training & performance

•  What is heart rate variability (HRV)?

•  How to get the most out of HRV (best practices)

•  What can we do with the data

•  Opportunities from user generated data

Quick outline

Page 37: Heart rate variability, training & performance

2012 - 2015

What can we do with the data in the context of training &

performance?

Page 38: Heart rate variability, training & performance

What to do with HRV data

•  Acute HRV changes

•  Multi parameter trends

Page 39: Heart rate variability, training & performance

Acute HRV changes Day to day variability

Page 40: Heart rate variability, training & performance

Acute HRV changes Rest or easy trainings

Higher HRV

Page 41: Heart rate variability, training & performance

Acute HRV changes Average or intense trainings

Lower HRV

Page 42: Heart rate variability, training & performance

Acute HRV changes

Page 43: Heart rate variability, training & performance

Acute HRV changes

Page 44: Heart rate variability, training & performance

Acute HRV changes

Page 45: Heart rate variability, training & performance

Acute HRV changes

Page 46: Heart rate variability, training & performance

Multi-parameter trends

•  In the long term things get more complicated

•  Higher HRV not necessarily linked to better condition/performance

•  Understanding the big picture requires more parameters and context – Training load, other stressors

Page 47: Heart rate variability, training & performance

Multi-parameter trends

•  HRV baseline and variation

•  More variation could be indicative of maladaptation to training (weekly values all over the place)

Page 48: Heart rate variability, training & performance

Multi-parameter trends

•  Detects: –  Coping well –  Maladaptations –  Accumulated

fatigue

Page 49: Heart rate variability, training & performance

•  What is heart rate variability (HRV)?

•  How to get the most out of HRV (best practices)

•  What can we do with the data

•  Opportunities from user generated data

Quick outline

Page 50: Heart rate variability, training & performance

2012 - 2015

User generated data

Page 51: Heart rate variability, training & performance

User generated data Dataset

Page 52: Heart rate variability, training & performance

User generated data Acute HRV changes

Page 53: Heart rate variability, training & performance

User generated data Acute HRV changes

Page 54: Heart rate variability, training & performance

User generated data Acute HRV changes & consistency

Page 55: Heart rate variability, training & performance

User generated data Acute HRV changes & consistency

Page 56: Heart rate variability, training & performance

User generated data Acute HRV changes & consistency

Page 57: Heart rate variability, training & performance

User generated data

•  What’s next – Better understand relation between

physiological parameters and physical condition in the long term

– Build better individual models

– Stratify on more parameters / include different samples of the population

Page 58: Heart rate variability, training & performance

Questions?

HRV4Training.com/faq

@marco_alt


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