Heart Rate Variability (HRV) Analysis and HRV4Training

18 January 2021
HEART RATE VARIABILITY ANALYSIS
AND HRV4Training
Marco Altini, PhD
@altini_marco

2
Marco Altini
• PhD cum laude in Machine Learning
• MSc cum laude in Computer Science
Engineering
• MSc cum laude in Human Movement
Sciences, High Performance
Coaching
• Founder of HRV4Training
• Data Science Advisor at Oura
• Guest Lecturer at VU Amsterdam
• 50+ publications at the intersection
between technology, health and
performance

318 January 2021
Circa 2009
First Android mobile phone,
linked to external ECG sensor

418 January 2021
2015-onwards
Validated, camera-based HRV
analysis

518 January 2021 518 January 2021
HRV4Training: a scientific tool
Ease of use & low cost: improves compliance and accessibility
Awareness: how are we responding and adapting to training and lifestyle stressors?
Actionability: how can we improve?
• Better training plans, personalized to an individual’s unique response to
stress
• Adjustments and optimizations on the go so that performance can be
further improved
• Simply better managing stress and lifestyle
Based on simple physiological relationships between stress and homeostasis, backed
by years of scientific research

6
IN THIS TALK
What’s Heart Rate Variability? (HRV)
• Physiology
How to collect data
• Available technologies
Guidelines
• Measurements, confounding factors
Data analysis and interpretation
• Normal values, training prescription
Getting practical
• HRV4Training app and Pro

WHAT’S HEART RATE VARIABILITY?

8
BEAT TO BEAT
VARIATION
RR intervals: time difference
between consecutive beats

10
STRESS
Homeostasis is about maintaining
balance
As we face a stressor, the
autonomic nervous system (ANS)
self-regulates many body functions
Heart rhythm is regulated by the
sympathetic and parasympathetic
branches of the ANS

11
HRV AS INTERNAL LOAD
Facing a stressor triggers a specific
response, typically consisting of
increased sympathetic activity
(flight or flight) and reduced
parasympathetic activity
Parasympathetic activity increases
HRV and can be measured in a
very short timeframe (e.g. 1
minute). A suppression, is typically
associated to high(her) stress

12
HRV AS INTERNAL LOAD
Higher HRV
Higher
parasympathetic
activity, less
stressed
Lower HRV
Inhibited
parasympathetic
activity, more
stressed

LET’S LOOK AT A FEW EXAMPLES

14
ACUTE STRESSORS
Acute stressors are typically
quite strong, transitory events
and can be detected even
when analyzed in isolation
However, we should remember
that all of these factors (and
many others) act simultaneously
on the ANS (-> collect
contextual data, training,
subjective metrics, etc.)

TRAINING LOAD

TRAINING LOAD
HRV is more sensitive than
HR, the change is about
5-8% after hard sessions,
while for HR just 0.5-1%

TRAINING LOAD

TRAVEL EXAMPLE

TRAVEL EXAMPLE
Much lower HRV
when traveling
daily, higher stress
on the body

ALCOHOL EXAMPLE

ALCOHOL EXAMPLE
Lower HRV
with higher
alcohol intake

GETTING SICK (COVID)

23
STRESS = TRAINING +
LIFESTYLE

24
STRESS = TRAINING +
LIFESTYLE

STRESS COMES FROM DIFFERENT
SOURCES AND OUR CAPACITY TO
HANDLE STRESS IS LIMITED

26
IN THIS TALK
• Physiology
How to collect data
Guidelines
Getting practical

DATA COLLECTION
At HRV4Training we have developed (and validated) the world’s first
system able to measure HRV using the phone camera
The technique is called photoplethysmography (PPG for short) and consists
in detecting changes in blood volume during a cardiac cycle, by
illuminating the skin and measuring changes in light absorption.
HRV4Training uses the phone camera to extract PPG and then determine
markers of the autonomous nervous system activity, in particular
parasympathetic activity (validated at High Performance Sports New
Zealand)

29
CAMERA-BASED
MEASUREMENT
Validated with respect to ECG and
chest straps

3018 January 2021
analysis
Camera
PPG
Instantaneous
heart rate
Timer

3118 January 2021
From Plews et al. “Comparison of
HRV recording with smart phone
PPG, Polar H7 chest strap and
electrocardiogram methods”

OTHER (VALID) WAYS TO MEASURE
The morning measurement can be taken using one of the following:
• Validated camera measurement
• Apple Watch and Breathe app to trigger a
• measurement, then read the data in HRV4Training
• Scosche Rhythm24 armband (not the rhythm+)
• Corsense finger sensor
• Polar H7 or H10 chest straps (Garmin straps and tickr straps can also
work depending on your phone)
The only reliable alternative to a morning measurement is a night
measurement, in this case we recommend the Oura ring, paired to
HRV4Training
• Not interchangeable, pick a method and stick to it

THE NUANCES OF NIGHT HRV DATA
Different tools can provide data collected at different times. There are
some important considerations to make when deciding which tool to use,
mostly because of:
• The circadian rhythm
• Sleep stages
The circadian component of night HRV typically shows an increase during
the night. Minute by minute data can on the other hand differ based on the
sleep stage in which it was measured
For these reasons, we recommend using the whole night of data and
averaging the HRV data across the night, to remove the issues above

CIRCADIAN RHYTHM
Here are almost 600 nights of sleep from the same person:

CIRCADIAN RHYTHM
Here are almost 600 nights of sleep from the same person:
A device like an Apple Watch
that provides sporadic
measurements during the
night might have validity
issues due to the time at
which the data is collected.
Better to use it for a morning
measurement (conscious, no
effect of sleep stage, + similar
time each day)

SLEEP STAGES
HRV differs between sleep stages:
1. A device that tries to use
HRV data collected only
during deep sleep or during
the last segment of deep
sleep (or any other sleep
stage) makes the strong
assumption that such stage
can be accurately detected.
Unfortunately that is not the
case

SLEEP STAGES: MORE ISSUES
HRV differs between sleep stages:
2. Even in an ideal world
where sleep stage
classification is 100%
accurate, deep sleep can
happen at very different
times each day, therefore re-
introducing errors due to the
circadian rhythm. Better to
use the whole night of data

38
IN THIS TALK
• Physiology
How to collect data
Guidelines
Getting practical

CONFOUNDING FACTORS
Due to the very nature of what we are measuring (parasympathetic
activity, or the ANS response to stress while trying to maintain homeostasis),
there are many confounding factors that can influence the data.
Physical exercise, nicotine, caffeine, meds, circadian rhythm, alcohol
intake, age, digestion, sickness, etc.

HOW DO WE COLLECT MEANINGFUL DATA?
It is key to measure in a way that limits as much as possible the effect of
confounding stressors and other factors
The simplest way to do so is to create a reproducible context in which to
measure, which basically means to measure as soon as you wake up,
before exercise, breakfast, coffee or reading annoying emails

42
BEST PRACTICES
How/when to take the
measurement
• Morning, still in bed, etc.
What type of measurement
• Lying down, sitting
How many times per week?
• Measurement frequency
Other issues / recommendations

43
WHEN AND HOW TO
MEASURE
First thing after waking up:
• Relaxed physiological state
• Limit all external stressors
• Closest to what we do in
research / clinical studies
(well, actually even better)
• Highly correlated with night
measurements
• Don’t read your social media
before the measurement

44
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 (<32-35 bpm, in this case
sitting or standing might be
preferable)
• Going to another room also
fine, take time to relax

45
MEASUREMENT
FREQUENCY
• 4-5 times/week will get you a
reliable baseline
• The more the better, easier to
make it a routine and do it daily
• Wait at least 4 weeks before
implementing any changes
(determine an athlete’s normal
values)

46
IN THIS TALK
• Physiology
How to collect data
Guidelines
Getting practical

DATA ANALYSIS AND
INTERPRETATION

DATA ANALYSIS: NORMAL VALUES
HRV analysis requires a mindset shift
First of all, we need to understand the nature of the data and the constant
re-adjusting of the autonomous nervous system, and therefore take all the
necessary steps to acquire a reliable measurement
Secondly, we need to shift from a “higher is better” to a “normal is better”
mentality, as physiologically speaking, being in a stable condition is
typically a good sign

PLANNING AND ADJUSTMENTS
A software that interprets any HRV increase as a good sign, or any HRV
decrease as a bad sign, is failing to correctly represent the fact that there
are normal variations in physiology
Only variations outside of this normal range, should trigger concern or
more attention or simply be interpreted as actual changes

NORMAL IS GOOD
HRV IS ABOUT CONTINUOUS
FEEDBACK. WHAT YOU OPTIMIZE IS
PERFORMANCE, NOT HRV ITSELF

PLANNING AND ADJUSTMENTS
In HRV4Training we deal with day to day variations and the fact that
physiology is often changing by learning what variations are normal in your
specific case, and building a model relying on the past 60 days of
measurements so that only significant changes will be interpreted as such,
when providing daily advice for your workouts.

5218 January 2021
analysis
Camera
PPG
Instantaneous
heart rate
Timer

5318 January 2021
Interpretation: daily scores are compared to normal
values to determine when HRV is significantly
suppressed
Score:
parasympathetic
activity
Lower score means
more stress

5418 January 2021
HRV4Training Pro
Web dashboard
Baseline and
normal values

5518 January 2021
HRV4Training Pro
Web dashboard
Clearly identifies periods
of higher chronic stress,
when it can be helpful to
hold back and reduce
training intensity

HRV AND TRAINING LOAD
The view that training should cause a dip in HRV is somewhat simplistic
HRV is a measure of physiological stress, and periods of higher cumulative
stress are typically highlighted by a reduction in HRV, but acute (day to
day) changes are hardly simply linked to training intensity, let alone the
fact that in a situation of positive adaptation to training, your HRV should
increase (or at least be stable) when consistently increasing training load
What we measure is the response

57
TYPICAL REASONS
BEHIND POOR
RESPONSES
See Flatt et al.
• The training stimulus is
significantly greater than what
the athlete normally experiences
• The training stimulus is novel or
different from what the athlete is
accustomed to
• Training is otherwise normal, but
non-training related stressors are
present

CONTEXT: POSITIVE ADAPTATION TO INCREASED
LOAD
Increased load is shown by a higher acute
(orange) load with respect to the chronic (blue)
one. A positive HRV response to increase load
consists in stable or increasing HRV

CONTEXT: POOR (LONG TERM) RESPONSE TO BAD
SLEEP
Here we can see how 1-2 nights of poor sleep with
increased acute load had a very poor response for
this person, with HRV remaining below normal
values for weeks

TRIATHLON TRAINING AND LIFE EVENTS
One year of daily
measurements in response to
various events, courtesy of
triathlete Ricardo Mazzini

TRAVEL AND RACING

START A CONVERSATION
A drop without a specific change in training
planning or load might help a coach start a
conversation with an athlete about potential non-
training related stressors to take into account

LIFESTYLE STRESS
Increased training load here is accompanied by a
positive HRV response. However, as soon as work
related stress increases, we have a poor
physiological response and reduced HRV

LIFESTYLE STRESS
This is the same data as in the previous slide, but
we can this time analyze the correlation between
HRV and self-reported work stress

MENSTRUAL CYCLE
HRV4Training was used in the first longitudinal study
investigating the relationship between the menstrual cycle
and HRV. A reduction in HRV during the second phase of
the cycle was found

MENSTRUAL CYCLE
For this individual, there is a strong link between
menstruation days and reductions in HRV, plus also
a tendency to decreased HRV during the second
phase of the cycle

FROM AWARENESS TO
ACTIONABILITY: TRAINING
PRESCRIPTION

TRAINING PRESCRIPTION
The goal is always to use the data in the best way possible, so that you can
understand how your body is responding to your training plan, and make
adjustments
HRV allows to provide the most appropriate training stimuli in a timely
manner, when your body is ready to take it, so that positive adaptation will
occur and you will be able to improve performance

Comparing your daily scores with respect to your historical data is a simple
statistical way to determine when a daily score or baseline is significantly
different from what is normal for you (e.g. lower, highlighting more stress),
and therefore this seems an optimal moment to adjust training so that we
can truly individualize it
This approach has shown performance improvements in multiple studies
Capacity for stress is limited

In this study, HRV4Training and Pro were used for
data collection. The approach used to build
normal values is similar to the one covered in this
presentation

A recent review and meta-analysis (2020) showed
the benefit of HRV-guided training. The field is
finally maturing

TRAINING PRESCRIPTION: EXAMPLE
Here is an example of how training prescription
could be implemented, scaling down training
intensity when HRV is below normal values

74
A COMBINED
APPROACH
• Physiological responses
(HRV at rest, heart rate
during exercise, etc.)
• Subjective scores (morning
questionnaires, RPE, etc.) ->
context
• Training data (duration, TSS,
etc.) -> context
HRV does not replace other
variables

75
IN THIS TALK
• Physiology
How to collect data
Guidelines
Getting practical

HRV4Training: GETTING PRACTICAL

77
SETUP
Athlete: HRV4Training app
• Morning measurement
• Questionnaire
• Optionally data can be hidden
Coach: web platform
• Compliance
• Normal values
• Long term trends
• Data export
• Additional features (training load,
correlations, etc.)

78
COACH PANEL
Overview of daily scores, baseline,
normal values, and subjective scores
all in one screen

79
QUESTIONNAIRE
Several parameters can be
configured for your athletes

80
DASHBOARD
Quick overview of recent trends in
various physiological, training and
subjective parameters (current week
vs previous month)

HRV4Training: a scientific tool
Ease of use & low cost: improves compliance and accessibility
Awareness: how are we responding and adapting to training and lifestyle stressors?
Actionability: how can we improve?
– Better training plans, personalized to an individual’s unique response to
stress
– Adjustments and optimizations on the go so that performance can be
further improved
– Simply better managing stress and lifestyle
Based on simple physiological relationships between stress and homeostasis, backed
by years of scientific research

Heart Rate Variability (HRV) Analysis and HRV4Training

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