Blog post by Marco Altini

​In the past few weeks I had the pleasure to get to know Francesco Cuzzolin thanks to our partnership with the EuroLeague Players Association

Francesco needs no introductions, but I’m gonna do it anyway: first European to become Head Strength and Conditioning Coach in NBA (@ Toronto Raptors), formerly at Benetton Treviso, Virtus Bologna, the Russian National Basketball Team and Italian National Basketball Team, lecturer in training / re-training and injury prevention at the University of Verona and of Padova, Research and Innovation Director for Technogym, currently personal trainer for Andrea Dovizioso

Francesco is also an expert in HRV monitoring, and has been using the available technologies for decades. Needless to say, we clicked

In the first episode of his new podcast, we tried to break down the science and application of HRV and stress monitoring with a lot of practical insights. I hope this will be a useful resource for anyone getting started with our technology and striving to get their athletes to peak performance

Link here

Blog post by Marco Altini

We are starting a new research project together with CUS Torino Women's Rugby, and the University of Turin. ​

In particular, this work aims at quantifying training load and resting physiology (HR, HRV) in the context of the menstrual cycle, looking at the relationships between these variables over several months in rugby athletes.

More updates will follow, special thanks to Luca Beratto for involving us!

In the hope that we will all get to race a little more in 2021, HRV4Training is looking for brand ambassadors worldwide

Are you passionate about sport and technology and have been using HRV4Training daily at least for 6 months to better balance stress? We are looking for you!

We are going to select up to 30 brand ambassadors, we accept applications in English, Italian and Spanish. Would you like to spread the word about HRV4Training in another language? Send us a message with your proposal for our consideration!

What do we offer to the ambassador and mentors?

• Ambassadors - free HRV4Training gear: choose between hats, singlet, or face mask and 1 year free access to HRV4Training Pro, our web platform;
• Mentors - free access to HRV4Training Pro for you and up to 5 clients for one year;
• Ambassadors and Mentors will be featured on our website and on social media (mainly IG);
• Repost of your posts on IG stories.

What do we expect from the ambassadors and mentors?

• Up to 4 posts per year (on your chosen platform such as IG, FB, Strava, or personal website/blog) to schedule together with our team, where you explain how you use the app; 
• Ambassadors and Mentors should include an HRV4Training handle in their bio on social media;
• Ambassadors should send us a photo of them wearing the singlet that we can share on our website and social media;

We believe in empowering individuals with the ability to measure and interpret physiological data so that training and lifestyle stressors can be better balanced, resulting in improved health and performance

Learning from athletes and coaches is an invaluable part of the journey, and we are looking forward to getting to know you and your experience

​​To participate in the selection process, fill in this google form. 

Deadline is November 30th, 2020

Parasympathetic saturation refers to a situation in which parasympathetic activity is particularly high, but this is not reflected accurately in HRV data. As Kiviniemi et al. explain in [1], "possible physiological mechanisms underlying saturation could be due to the dose response of the heart to the acetylcholine secreted by vagal nerve ending. The dose response to acetylcholine has been considered to be linear until its concentration reaches the level at which a further increase in acetylcholine concentration does not produce a change in the response", or in Daniel Plews' words [3]: "a heightened vagal tone may give rise to sustained parasympathetic control of the sinus node, which may eliminate respiratory heart modulation and reduce HRV".

It follows that as reported in another of Daniel's papers [2], "in some circumstances, such as vagal saturation, decreases in cardiac parasympathetic indices of HRV during this particular training phase can be related to positive performance outcomes and consequently reductions in HRV, so should not be viewed negatively". 

Looking at the relationship between HRV and RR interval length you can identify possible parasympathetic saturation. Parasympathetic saturation is a rare event which can happen in elite endurance athletes during high load training blocks.

In particular, parasympathetic saturation typically requires:

1. average low heart rate (in the 40s or lower)
2. high volume training
3. elite endurance athletes

​
Under these circumstances, you can look at the relationship between HRV and the average RR interval length (basically the inverse of heart rate), to determine the likelihood of saturation.

Normally, higher HRV is associated to lower HR (see data below for an example), and therefore we expect a linear relationship. However, if you are in a period of high training load and HRV is low, together with low HR, and therefore the correlation between HRV and the average RR interval length is small or negative (we lose the linear relationship that we were just discussing), parasympathetic saturation is plausible (below I'll show how you can look at this in our platform). 

Depending on how you measure your HRV, you could be pro-active and collect data that is less likely to be affected by the issue of parasympathetic saturation.

In particular:

• if you measure your HRV during the night, there isn't anything you can do. Hence you should use the procedure below to determine if parasympathetic saturation is likely in your own case. In this case it might be preferable to use a morning measurement.
• If you measure in the morning, you can measure while sitting (or standing), so that you add a little stress on your body and potentially prevent the issue of parasympathetic saturation, as recommended by Andrew Flatt [4]. Some practitioners mention lower compliance when asking athletes to take their measurement in a way other than while still lying down in bed, and as usual, no data won't help, hence first make sure that this is not affecting compliance. Make also sure to always measure in the same body position, so if you decide to sit or stand for your measurement, first always allow for 30-60" of rest to allow your body to re-adjust to the change in posture, then take your measurement always in the same body position every day.

As mentioned earlier, if you are in a period of high training load and HRV is low, together with low HR, and therefore the correlation between HRV and the average RR interval length is small or negative, parasympathetic saturation is plausible.

We have developed a new feature in HRV4Training Pro to help you analyze this relationship. In the plot below, you would see the darker dots in the lower right corner (low HRV, low HR or high RR interval length). In this case, the suppression in HRV should not be interpreted negatively, as reported by ​Plews et al.: "the lack of correlation between the R-R interval and Ln rMSSD indicate that athletes are more likely to undergo parasympathetic saturation".

​You can find the plot below under Insights / Resting Physiology in HRV4Training Pro, we also report the correlation between HRV and the RR interval length for the past 2 and 6 weeks, so that you can more easily spot any recent changes:

Finally, we have added Possible parasympathetic saturation as an automatically detected trend, hence the system will try to do the math for you:

Blog post by Marco Altini

Our work on HRV and altitude adaptation in elite triathletes is available on Sport Performance and Science Reports, at this link. This work is based on my thesis, and was carried out in collaboration with the Dutch Triathlon Federation and Vrije Universiteit Amsterdam

We hope you will find it interesting

Blog post by Marco Altini

We recorded our latest webinar that was put together for the Spanish Paralympic Committee. In this talk, we cover:

• What's HRV
• How to collect data
• Guidelines and best practices
• Data analysis and interpretation (with case studies) 

¡gracias!
​

The Overview page in HRV4Training pro shows your daily heart rate and HRV, together with normal values and baseline, to ease interpretation of your recent trends

In addition, you can also color-code the bars based on annotations such as alcohol intake or menstruation, as well as based on the daily advice, coefficient of variation and detected physiological response

In the latest update of Pro, available for any user when logging in at HRV4T.com, we also added a few tips and explanations that should help you better understand what could be behind a recent change in physiology, as well as how the different algorithms work

Here are a few examples. Recent literature as shown that during the luteal phase of the menstrual cycle, there can be a small drop in HRV. This is now reported in Pro when selecting Menstruation as annotation, as shown below:

When selecting the Daily Advice, we report more details on how the daily advice is built:

Here is an example for sick days:

And finally for the Coefficient of Variation, including an explanation of how to read the data:

We hope you'll find the new update helpful

We have made a small change to the next version of the HRV4Training app on iOS and Android to allow you to quickly hide your daily score and historical data on race or match day. Needless to say, there are days in which we might not be able to do much about our physiological stress level (for example race day), or when the value might be less representative of a poor response, and simply affected by things such as race excitement, an isolated poor night of sleep, etc. 

All of these circumstances can still have a psychological impact for some, especially on race day. In the app, you can always hide your score before the measurement from Menu / Settings and unchecking the "Show daily advice" box. However, it might just be too many steps to remember first thing in the morning

Thus, in the next version of the app, you will be able to quickly hide your daily scores when filling in your questionnaire. First make sure to have the "training phase" tag enabled, as shown below:

Then, on race or match day you simply need to select "Competing | Hide HRV" and the app will not show you your score. On the following day you can simply select a different training phase to see your data again.

Alternatively, you can always re-enable your daily score by going to Menu / Settings and checking the "Show daily advice" box.
​

We hope you'll find this improvement useful. Enjoy and take care!

We are excited to share the news that we are partnering with ELPA, the EuroLeague Players Association

One of ELPA’s objectives is to provide its members services that help them maximise and prolong their careers

Therefore, ELPA and HRV4Training are announcing a multi-year deal that will allow ELPA members to benefit from a tool which measures their heart rate variability (HRV), and provides a detailed analysis of how their bodies react to their stress levels during the season. HRV4Training app will be used to monitor physiological responses to a busy schedule made of frequent games, traveling and all that elite sport such as professional basketball encompasses

Boki Nachbar (Managing Director, ELPA): “We continuously seek for ways to help our members take advantage of newly accessible technologies for professional athletes, such as HRV4Training. Especially in current climate players need to understand how their bodies react to various intense moments that happen during the season. Mastering that understanding will help them to better control the stress and it can therefore prolong and enhance their careers."

Thank you and all the best for the upcoming season

Blog post by Marco Altini

​We are collaborating with the College of Health and Human Sciences at Kansas State University for a (remote) research study on HRV  and cycling performance

In particular, the purpose of this study is to determine if cycling endurance performance is altered when an individual has a change in their 7-day average heart rate variability. This study will provide insights to individual exercise prescription regarding when to appropriately decrease exercise intensity or duration in response to changes in the cardiovascular system

If you are interested in participating, please read below and apply here

Who can join the study?

• Own a bicycle and indoor bike trainer
• Own a heart rate monitor (watch or chest strap)
• Own a cycling computer or cycling performance application
• Between the ages of 25-64 years
• English speaking
• Own a smartphone 

What is required during the study?

• Complete health, demographic and cycling equipment questionnaires.
• Record your morning HRV throughout your study duration.
• Maintain your current cycling/exercise routine.
• Perform six (6) 40-minute time trials.
• Record and submit all time trial data
• Complete a 24-hour nutrition recall after completing your time trial

Blog post by Marco Altini

If you have any questions or doubts before getting started with your team, feel free to send me a quick message on Twitter - we're here to help!

​
We have modified the Coach Panel in HRV4Training Pro to allow you to display the Overview page directly in the panel, without the need to navigate to each athlete's individual pages. You can choose between heart rate and heart rate variability, as well as add color-coding based on annotations.

The Overview page (more info here) is probably the most important single page in the platform, as it shows daily scores, normal values and baseline, making it really easy to quickly understand how things are trending, and how an athlete is responding to training and lifestyle stressors.

As you  can see from the images below, tapping "Show Overview" you will be able to see the plots directly in the Coach Panel, and save a little time during your daily check-ins. You can now also pick the type of physiological parameter (HR or HRV) and annotation (context, visualized in terms of color coding).

​We hope you'll enjoy the new feature, which you can try at HRV4T.com

Below you can see a few screenshots of this new functionality.

Blog post by Marco Altini

In this video with Rebecca Caroe at the Rowing Chat, we discuss:

• Physiological stress
• What is heart rate variability (HRV)
• Controlling HRV
• Application in elite sport

​Thank you for having us!

Blog post by Marco Altini

One of my favorite guest posts on our blog was written a few years back by Andrew Flatt. Andrew is a brilliant scientist and coach and has dedicated much of his time to investigating the relationships between HRV, training load and other stressors, in a variety of sports and athletes.

The full article focuses mostly on strength and power athletes, and can be found here. However, I believe some aspects are really applicable to any sport, and I'd like to report them here and show a little example using my own data collected with HRV4Training and the Pro platform.

Quoting Andrew:

"Highly trained individuals are more likely to see a pronounced decrease in HRV the following morning in response to a training session if: 

1. The training stimulus is considerably greater than the individual typically experiences (an abrupt increase in load

2. The training stimulus is novel or different from what the individual is accustomed

3. Training is otherwise normal, but non-training related stressors are affecting recovery" 

Point 3 is the one I'd really like to focus on in this post. Non-training related stressors are key. There's a whole body of research looking for example and how injury risk can increase due to high stress regardless of any changes in training, see psychophysiological models of injury for example. Needless to say, our capacity to handle stress is limited, and this exactly why HRV measurements are useful: they provide an overall marker of stress

In my view, non-training related stressors are an often overlooked great reason to use HRV monitoring, despite the fact we all understand well that if something is bothering us (issues at work, at home, financial concerns, etc) we can hardly focus and perform optimally.

As a recreational runner, I love to try to make a bit of progress, pushing myself to higher loads from time to time. When I manage to do so gradually and consistently, over longer periods of time ( > than a year for example), I do not expect my HRV to drop during an acute high-load block, as my body is well conditioned, and should assimilate the stimulus properly.

When we add other stressors though, the situation can easily change, and this is exactly why it is important to objectively monitor physiological stress and individual responses to stress (in a generic way), so that we can get the full picture. It would be really naive to think that the only thing that matters is training, and all we do in the remaining 22-23 hours of our day is irrelevant.

​Lets look at some data:

Above we can see three plots, with daily measurements collected over 3 months, first thing in the morning using the HRV4Training app:

• Physiological data (heart rate variability). Here is how we show historical data or normal values (light blue band), baseline (blue thick line) and daily scores (light gray bars) to make it easier to look at the big picture in HRV4Training Pro. You can find more information about how to use this visualization, here. 
• Training load: in this case I am using running distance, and showing a period of high load (in orange we have the acute load, and in blue the chronic load, when the acute load is higher than the chronic, it means that on a given week we are loading more than we are normally used to). We can also see how HRV data looks really good during this period of load, with the baseline increasing over time (anything that is an increase or a stable baseline during a high load period is typically a good sign, positive adaptation)
• Subjective data: in the last plot I annotate my "lifestyle stress" subjectively, based on how stressful my days have been. Note that we always advocate integrating these three aspects (physiological data, training load and subjective data) so that you have the full picture for yourself or your athletes, and can improve the decision making process. Here we can see how work stress increases quite a bit in the last period, while it was very low earlier. As stress increases, my HRV drops (the same situation can actually be seen at the beginning of the three months). We have recently added normal values to the subjective data as well, to make it easier to spot significant trends, and not only normal day to day variations.

We can also look at the correlation between physiological data and subjective metrics, in the Explore Correlations page that you can find under Insights in HRV4Training Pro:

In the plot above we can see again the strong baseline correlation between heart rate variability measured first thing in the morning, and lifestyle stress. As you can see "work stress" for me is typically the largest factor behind drops in HRV, especially when looking at the big picture (baseline more than day to day correlations).

Alright, hopefully this post gives you a more practical view of what to expect and how to interpret the data, always remember that multiple stressors play a role at the same time, and it is therefore beneficial to look at the data over longer periods of time, including normal values and baseline changes, and contextualizing physiological data (HRV or HR) with respect to your subjective annotations and training load. This is all computed for you in HRV4Training Pro.

take care!

We are starting our first partnership at HRV4Training in the Bundesliga today, with Hannover 96

Wishing the best for the upcoming season to the club. Thank you Tobi for your support!

🔬📲 ⚽️ 🇩🇪

Blog post by Marco Altini

​We put together a deck with practical information for players of organizations relying on our platform or simply getting started with measurements of resting physiology. Learn more below.

Blog post by Marco Altini

​We have just released an improvement to the correlations analysis in HRV4Training Pro, which now adds color coding to make it easier to spot stronger relationships between your annotated tags and your physiological data.

​You can try the new feature on HRV4Training Pro for free at this link, or use code SCIENCE for 15% off any package.

The correlation analysis in HRV4Training Pro lets you pick any timeframe between 30 days and 2 years. However, in general, we think that using a time frame between 60 and 90 days is ideal. 

Why  is that? Most likely the stressors you face will change over time, and similarly your response to certain stressors will change, therefore we believe it can be more helpful to look at these relationships in the relatively short time frame (e.g. 60-90 days), to get a better idea of what factors are influencing your physiology the most. Shorter windows (e.g. 30 days) might not have enough data, unless some really large stressor was present (for example if you go from sea level to 2000m / 6000ft of altitude, then you will certainly see a strong correlation between resting heart rate and altitude), otherwise it might be better to extend the window. On the other hand, longer windows (e.g. a whole year) might fail to capture more complex, multidimensional relationships between various training and lifestyle aspects, and your physiology.  

Finally, we would recommend to look at baseline correlations, more than day-to-day correlations. Baseline correlations are computed on the 7 days moving average of each variable, and therefore provide a more stable trend of the data. Typically, this is more insightful than to look at the individual data points, especially in the longer term.

Below you can seen an example:

• Negative correlations are shown in yellow. Remember that negative means that for example your HRV goes up while the other parameter goes down. It does not mean that this is a bad thing! If you have a negative relationship between life stress and HRV it simply means that your HRV goes up when  your life stress goes down, as show here for my own data.
• Positive correlations are shown in blue, in this case a higher HRV is associated with a higher value for a given parameter, for example mental energy in my case

and here is the actual data for the strongest correlation in my data, which is 'lifestyle stress', a tag I use to represent work-related stress:

The important part after you start looking at these correlations, is not to jump to conclusions. For example, it could be that the relation you are seeing is actually caused by another variable excluded by the analysis. However, this can be a useful starting point to explore your data, and we hope the new color-coding will make it a bit easier.

Enjoy