In the first part of “The Beginners Guide to HRV“, we looked at a general overview of Heart Rate Variability and how tracking our own HRV has the potential to guide our workouts, specifically high intensity of effort resistance training (HIT) workouts. In the second part, I want to expand on that premise and look at the practicalities of tracking and using HRV data in this context. This is where the rubber meets the road.
A quick look at Wikipedia reveals that the HRV app market has expanded pretty quickly over the last few years, with a total of 8 HRV tracking apps listed. There are actually even more available than the ones that Wikipedia list and I’m sure the market will continue to grow over the coming months and years, with the cream rising to the top.
List of free HRV apps
- Elite HRV
List of paid HRV apps
- Bioforce HRV
- Elite HRV
- Inner Balance
- Vitness Rx
I have experience of two of the listed apps. The first one I used was the ithlete app. I then transitioned over to Elite HRV in May 2014, thanks to Skyler Tanner’s recommendation.
The personal data mentioned in this article is the output of using the Elite HRV app. The general principles regarding HRV, which are elaborated on, should apply broadly speaking across most of the apps, if not all of them. This post is certainly not meant as a review of the available apps, but rather how they (the good ones anyway) can benefit us, as exercise enthusiasts. I am not an affiliate of Elite HRV, however that is the only app I can currently recommend to those looking to use an HRV app, primarily for the purpose of optimizing resistance exercise scheduling frequency, based on my personal experience so far.
What is measured by a good HRV app?
Warning: a hint of mathematics in the next few paragraphs!
As mentioned in part 1, there is a variation in the length of time between heartbeats and HRV apps measure this variation to ultimately give us an HRV “score”. A good app will only measure the time between “NN” beats; this means “normal to normal” beats, those that originate from the sinoatrial node impulse. It is important to remove data from arrhythmia, ectopic beats (those which originate from fibers outside of the sinoatrial node), and artifacts (noise from elsewhere in the body outside the heart, and poor monitor contact or malfunction). HRV readings would be inaccurate and misleading, if data from non-normal beats and artifacts were allowed to skew the data.
Once these NN inter-beat measurements have been recorded, the app has to present this information in an understandable and usable format. There are several different categories of analysis method that exist, including:
- time-domain methods
- frequency-domain methods
- geometric methods
- non-linear methods
RMSSD, the metric that determines your HRV score
The most widely used are the time-domain methods (ones that look at the variability in seconds), including:
- SDNN (standard deviation of Normal to Normal intervals)
- RMSSD (root mean square of successive (adjacent) differences)
- NN50 (the number of pairs of successive NNs that differ by more than 50 ms)
- pNN50 (proportion of NN50 divided by total number of NNs)
We will focus on RMSSD, as that is the metric that the most popular apps will use to work out your HRV score. To give a user-friendly HRV score, the app has to do a couple of things. Firstly, many research articles (even prior to HRV apps) show that RMSSD must be scaled logarithmically to be useful. Don’t worry; the apps do all this work instantaneously for us, so we don’t need the mind of a mathematician to choose what day to exercise on. This finally provides a user-friendly number or score, which you and I can easily interpret.
We get a number on a scale than runs approximately to 100. The higher your baseline HRV score is, the better. Scores slightly over 100 are possible, due to the formula used, you may however be Superman or Wonderwoman, if you get over 100 as your normal baseline.
What does the HRV score mean?
Effectively, the HRV score is a measurement of your current preparedness to cope with all varieties of stress: physical, mental and emotional. Your HRV baseline is not set in stone; it can change chronically, all being well gradually increasing over weeks and months toward your genetic maximum. Conversely, it can also decrease gradually over time, for instance if you were to quit exercise for a year.
As well as chronic, gradual and slow changes to your HRV baseline, fairly dramatic acute changes can also occur literally overnight – we’ll look into these in a moment.
Intense exercise is a stressor that has an impact on both chronic and acute changes to HRV.
- Acutely, intense exercise will cause HRV to decline, both during the workout and immediately afterward. The more intense the exercise, the greater the acute effect on HRV.
- Chronically, well-applied exercise allowing for adequate rest as well as adequate stimulus will increase baseline HRV gradually.
Of course as we discovered in the first post, other stressors have an effect on HRV too. Those include things like sleep-wake cycle, nutrition, mental stress, emotional stress and so on.
We must remember that our workouts and the scheduling of them do not exist in a vacuum and it is the sum total of all of the stressors that we endure at any one time that contribute to our current HRV score. Working out on a day when your HRV baseline is well below usual could be the straw that breaks the camel’s back, allowing an infection to take hold, making us feel overly fatigued and irritable the next day, or requiring a longer recovery period than usual or ideal.
Monitoring your daily HRV score will help you to figure out when you can push to your limits with minimal or no downside, and when not to.
How to use the HRV technology
Let’s now look at the practical process of using HRV technology in some more detail.
Then, you will need ideally to hold off from performing intense exercise for 7-10 days, so that you can establish your initial HRV baseline.
Intense exercise as mentioned is going to affect your HRV score, so whilst you are establishing a baseline it is best to avoid intense exercise. Perhaps you can take comfort from James Fisher’s advice that taking up to a three week “break from training appears to have no negative effect on muscular size, and in fact improves your rate of growth when you return to training.” This is therefore a two for one deal; you’ll establish an accurate HRV baseline and potentially respond better to intense exercise when you start up again.
Also, you can’t just take a reading on day one and say “that reading is my baseline”, because you could be having an off day that day. To get to an accurate baseline, you’re going to need multiple consecutive daily readings.
You don’t of course have to be completely inactive during that week. The effect of exercise on HRV relates to the intensity of exercise performed. Moderate and mild physical activity will have a fairly minimal impact on morning after HRV readings.
When and how to take baseline readings
Baseline HRV readings are best taken first thing in the morning, within moments of waking up, before the stressors of the waking day begin to accumulate.
My personal routine goes like this:
- wake up
- pee (important to do this before taking a reading)
- put heart rate monitor on, assume reading position
- focus on breathing for a full minute
- then, start recording HRV data through the app – different apps record the data for slightly different lengths (Elite HRV takes around 2:30 minutes)
Once the app has finished recording the data, you will have an HRV score and a resting heart rate reading. Over the next week, simply repeat that pattern, every morning, making sure to use the same reading position each time. By the end of this week you will have enough data to estimate your initial HRV baseline, so long as you weren’t ill that week or under an inordinate amount of stress. For example, don’t choose a week when you are moving home to do this.
Let’s look at body position options during the reading, as this is also important.
There are three main options:
Standing adds orthostatic stress, which means that your recorded heart rate will be higher and your HRV score will be lower than if you were lying down. It is also possible that orthostatic stress will help relay HRV changes acquired from intense exercise, more clearly and obviously than supine measurements can. Due to this some experts recommend that athletes with a resting heart rate below ~50bpm always measure in a standing position rather than supine. Variability may prove too subtle to measure effectively in the supine position for an individual with a very low resting heart rate.
The most relaxed position and the one that will give you, your true resting heart rate. However, there is the possibility of parasympathetic saturation, occurring in this position, which in certain circumstances may mean that your HRV score shows a false high.
Of course, you could split the difference and take the reading seated. There will be some increased stress over being supine, but you’ll be in a more comfortable and relaxed position to take the reading than if you were standing. This should help make the variation slightly more significant and easy to read than supine position results. This is my current personal favourite position.
Whichever position you pick stick with it, so that the morning readings you take are comparable to each other. Taking a supine reading one morning and a standing reading the next will be misleading, as position alone can dramatically alter HRV data output. We are looking to compare like with like.
Other lifestyle data
Elite HRV (and other HRV apps) allow you to input other lifestyle data manually; data such as your mood, sleep length, sleep quality, workout data and additional notes. All of which are useful when looking back over HRV patterns and analysing to find possible reasons why those patterns occurred in such a way at a particular time. It will only take a minute extra to do this.
Baseline HRV scores in some context and traffic light color-codes
My morning baseline HRV score is currently ~85, let’s give that score some context.
Joel Jamieson of Bioforce HRV has put together a neat table categorizing different levels of baseline HRV, I have adapted his table below and added some pertinent information for us, i.e. people engaging in high intensity resistance exercise:
Typical HRV scores
Please note that genetic factors likely play a role in ultimate HRV expression and potential, so bear in mind that I recommend you only compare yourself against yourself (and not against anyone else).
Traffic light color-code
The Elite HRV, ithlete and Bioforce HRV apps all give a color-code with each morning HRV reading that you take (other HRV apps may do too). This color-coding works by comparing your current reading with your baseline trend over the last week.
If the app’s algorithm considers your current reading to be comparatively good, it’ll give you a green color. If you have comparatively lowered or increased HRV a bit too much it will give you a yellow or amber color, and if you have lowered or increased quite dramatically it’ll give you a red color.
According to the app manufacturers, the colors typically mean:
- green – you are good to train full bore
- yellow/amber – you might want to dial the intensity back somewhat or have an easy day
- red – you’d probably do well to take a day off
This is where I think that we need to be careful as High Intensity Resistance Exercise enthusiasts. Firstly, as far as I can tell none of the app manufacturers specifically had this type of exercise at the forefront of their minds, whilst developing their respective apps. I believe that they likely had physical activity, sports skill training, endurance exercise, movement and general resistance training all in mind. This is the right thing for them to do, as it makes the apps useful to the widest possible audience and broadest set of circumstances.
How can HRV assist in scheduling High Intensity Resistance Exercise workouts
The answer to this question is a little involved to explain in a paragraph, so I made a new post (part 3), where I share my experience, observations and learnings from using HRV data.