HRV Webinar for K3Fitness

Heart Rate Variability & Training Webinar – K3Fitness

Marco Altini, PhD @marco_alt

Lead Data Scientist @ Bloomlife Creator of HRV4Training

Cardiorespiratory Fitness Estimation Energy Expenditure Estimation

Activity Recognition

PhD Applied Machine Learning

BSc, MSc Computer Science Engineering

Making it smaller

Maternal and fetal monitoring during

pregnancy Prediction of pregnancy complications

Labour detection

Load Data Scientist Bloomlife

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

•  What is heart rate variability (HRV)?

•  How to collect data (technology)

•  Best practices

•  What to do with the data

•  HRV4Training & Coach overview

Quick outline

2012 - 2015

What is HRV?

Beat to Beat Variation

Not a single number: time and frequency domain features. Most meaningful and standardized feature for short measurements: rMSSD (apps typically convert it to something more human-friendly, e.g. 0-10 or 0-100)

Heart Rate Variability (HRV) •  Regulated by sympathetic /

parasympathetic branches of the ANS

•  HRV (rMSSD) is a clear proxy of parasympathetic activity / recovery / body functions at rest – Understand how we react to stressors

Autonomic Nervous System

Higher HRV

Less physiologically stressed

Ready to perform

Lower HRV

More physiologically stressed

Tiredness

This slide is an oversimplification






Quick outline

2012 - 2015

How to collect HRV data

Full ECG: gold standard (see prev image)

Chest strap + app: typically very accurate, recommend Polar H7 (HRV4Training, ithlete, Elite HRV) Validated PPG devices: HRV4Training, ithlete, same as an ECG/Polar. Higher compliancy Wristbands: not there yet, will be soon

Hardware for HRV analysis

All technologies are affected by artifacts (or noise), either in the technology itself or simply actual artifacts in the data due to e.g. ectopic beats. Even an ECG needs to be correctly cleaned up for artifacts, same for Polar data. The app needs to do some extra work, check what you are using.

A note on artifacts






Quick outline

2012 - 2015

Best practices: how to get the most out of HRV measurements?

60 Seconds 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)

•  Anything affects the ANS > best practices

Best Practices

•  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?

•  Other issues / recommendations

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!

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 unless your heart rate is very low (<40 bpm, in this case sitting or standing might be preferable)

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) – do not breathe at unnatural rate (e.g. too deep).


12/minute

6/minute

Consistency is key

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

routine

Stick to those

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)

Are 60 seconds really enough?

•  Yes. Just follow the best practices

Other issues

•  Do not swallow while measuring, try to relax and avoid swallowing or repeat the measurement (swallowing causes tachicardia and therefore can affect the measurement)

•  Empty the bladder •  Measure every day: while 4-5 times/

week will get you a good baseline, valuable information is lost (e.g. weekly variability in measurements)






Quick outline

2012 - 2015

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

performance?

What to do with HRV data

•  Acute HRV changes: day to day variations to acute stressors –  intense workout –  getting sick –  travel –  etc.

•  Multi parameter trends: long term/chronic changes in baseline values –  Maladaptation to training –  Tapering –  etc.

Acute HRV changes HRV change following training

Acute HRV changes The day after rest or easy trainings

Higher HRV

Acute HRV changes The day after average or intense trainings

Lower HRV

Acute HRV changes

Acute HRV changes: research


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Acute HRV changes: training

Acute HRV changes: alcohol

Acute HRV changes: getting sick

Acute HRV changes: travel

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


•  HRV baseline and variation

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


•  Look for: – Steady or increasing HRV baseline – Steady or decreasing HR baseline – Low CV, unless HRV baseline also

decreasing

Always in the context of your current training/load


Vesterinen et al. Start an intense training block only when HRV not trending negatively

Other recommendations

Step 1 is always collecting data. Collect for months before you implement any changes.

Understand what affects your physiology. Every person is different, by monitoring physiological responses to your training you can get unique insights on how your body is responding Step 2 is how to optimize training using HRV. Do we always aim for higher values?

HRV will go through cycles of higher and lower values over months, depending on your physiological stress level. By making day to day changes we can try to optimize performance and training in the long term, not necessarily resulting in increased HRV at the end, but in better performance as we trained our body harder at the right moment (see Vesterinen et al). Very different from HR (typically reducing with increased fitness).






Quick outline

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

•  Accessibility & high quality –  camera-based data acquisition (validated

with respect to ECG)

•  Insights –  combine annotations and physiological

data to better understand acute changes, trends, fitness, etc. -> interpretation, more than just data

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

about the relations between training, lifestyle, physiology and performance

HRV4Training

AdaptedfromTamuraetal.WearablePhotoplethysmographicSensors—PastandPresent

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Camera-based measurement: accuracy (rMSSD)

Camera-based measurement: accuracy (PPG vs ECG)

HRV4Training: measurement

Camera view

PPG view

60 seconds timer Breathing bar for paced breathing

Instantaneous heart rate

HRV4Training: tags & history

HRV4Training: main screen

Daily score and advice (color coded)

Baseline

Advice message

Your normal values and where you stand today

HRV4Training: insights

•  Acute HRV changes: day to day variability in response to training

•  HRV trends: multi-parameter analysis to look at the big picture

•  VO2max estimation: based on submaximal HR (requires Strava link)

•  Training load analysis: standard ATL/CTL models

•  Custom correlations: explore relations between tags and physiological data

HRV4Training: acute HRV changes

•  day to day variability in response to training

•  Analysis by sport and training intensity.

•  How does your physiology respond?

HRV4Training: HRV Trends

•  multi-parameter analysis to look at the big picture

•  Is it the right time to start intense training blocks?

•  Are we adapting well to the current training plan?

•  More experimental

HRV4Training: VO2max

•  Based on submaximal HR (lower submaximal HR -> higher fitness level)

•  Link to Strava to automatically acquire workouts data

HRV4Training: training load analysis

•  Pick training load metric (intensity, distance, RPE, TSS, suffer score, etc.)

•  Acute training load •  Chronic training load •  Injury risk (too much

acute training with respect to our chronic?)

HRV4Training: custom correlations

•  explore relations between tags and physiological data

•  What other factors influence your physiology?

HRV4Training Coach

•  Automatically retrieve your athlete’s data right after the measurements

•  Analyze insights + explore custom parameters

•  Quickly assess physiological stress level based on your athlete historical data (overview of daily advice, HRV and subjective scores)

•  Configure remotely your athletes tags & filter them locally

•  Export all data as csv files

HRV4Training Coach

Questions?

HRV4Training.com/faq

HRV4Training.com/Blog

@marco_alt

HRV Webinar for K3Fitness

Science

Transcript of HRV Webinar for K3Fitness