DDFA – new dynamic heart rate zone training – a Suunto first

TLDR: DDFA is a method for continuously determining your heart rate zones using novel HRV (RR) correlations. Suunto has included this feature on its modern watches and as a post-workout analysis on its smartphone app for all workouts using a chest strap.

Athlete Benefit: Suunto’s DDFA should always give accurate heart rate zones so you will always know the correct intensity for endurance.

This article explains some of DDFA’s background and limitations before showing how Suunto has integrated it into its watches and ecosystem. It’s not wholly groundbreaking, but it is a notable step forward for two reasons: 1) it appears to be the best available method of intensity from HR, and 2) for the first time, truly dynamic HR zones are adopted by one of the major sports wearables companies.

Understanding Heart Rate Variability

Your heart doesn’t beat like a metronome with perfect regularity. Instead, it has a natural, complex rhythm that changes slightly from beat to beat. This variation in the time between heartbeats is called Heart Rate Variability (HRV).

Scientists measure HRV by examining the time between heartbeats and RR intervals (NN intervals). When resting, Sports and wellness insights use relatively straightforward rMSSD and SDNN calculations.

More recently, sports-grade endurance activity has seen an old mathematical method called detrended fluctuation analysis (DFA), used to study patterns in HRV intervals. For example, I use DFA a1  via alphaHRV (Garmin CIQ) and on the AI Endurance platform.

Traditional DFA Approach

The traditional approach looks at patterns in two ways:

1. Short-term (4-16 heartbeats)
2. Long-term (16-64 heartbeats)

They would assign a number (scaling exponent) to describe how the heart behaves in each range.

Alternate explanation: here

Limitations of Traditional DFA

This approach has some drawbacks:

1. The ranges (4-16 and 16-64) are somewhat arbitrary.
2. Two numbers often aren’t enough to fully describe the complex behaviour of the heart.
3. Heart behaviour can change over time, like during exercise or sleep.

Introducing Dynamic DFA (DDFA)

To address these limitations, researchers at Tampere University developed a new method called Dynamic DFA (DDFA). This approach:

1. Looks at heart patterns across all scales, not just short and long-term.
2. Tracks how these patterns change over time.

This method was tested on a small group of indoor cyclists and validated against lactate thresholds, ventilatory thresholds and somewhat arbitrary thresholds derived from HRmax. DDFA was reported to give better correlations to lactate thresholds than a traditional DFA calculation.

Bottom Line

You can use DDFA with a chest strap to determine lactate thresholds (LT1 or AeT, LT2 or LTHR). This gives a 3-zone model

1. Below LT1 – Aerobic
2. Between LT1 and LT2 – Anaerobic
3. Above LT2 – VO2max

Importantly, these thresholds match those that almost all of us use in 5- and 7-zone models.

More at DOI:  here (2023) and here (2020)

Using In Sport

You already know you are training to improve your thresholds, which change as the weeks pass. But they change every day, even within a day and throughout each workout. These threshold changes may often be gradual but can be more pronounced during a workout as you fatigue or as environmental conditions change.

Consider: If you are going for a 5-hour bike ride starting at 8 am and finishing in the Summer sun atop Mt Teide at 1 PM you could potentially use DDFA thresholds to more precisely regulate your efforts than either HR zones or power zones – time will affect the meaning of your heart rate, the temperature will affect the meaning of your heart rate and elevation will affect the impact of your body’s power output.

Problems & Other Points

While this is an exciting development for Suunto to include in a consumer-grade product, it’s still early.

• Current DFA methods can already include dynamic adjustments – for example, alphaHRV makes adjustments based on the ventilatory rate.
• A small sample size was used in the study.
• The study was conducted in controlled laboratory conditions, which may not translate well to real-world efforts, perhaps because of vibration.
• The method probably won’t work for strength training and intervals but should be good for most other endurance sports and activities.
• There are issues with the meaning of lactate levels and the sampling to estimate them.
• Real-time calculations require processing power and might impact the performance of wearables.
• There is a 10-minute warm-up period before DDFA data is produced.

Bring In Suunto

Suunto has partnered with Monicardio to bring these new zones to its watches. The Suunto app offers a DDFA analysis for those of you with older, less powerful watches.

If you want this to work, use a Bluetooth chest strap to make HRV-grade recordings. The Suunto Smart Belt can do that as can Polar H10/H9 and Garmins more recent HRMs like HRM PRO Plus. Optical armbands will not work and only the Suunto Smart Belt will cache data for swimming with Suunto watches.

Get The App

Get the Zone Sense app from the SuuntoPLUS store on your smartphone app.

Before you start your workout, ensure the app is enabled, that you have a chest strap paired and that you have disabled the optical HR.

Successive workouts more precisely define your baseline, and at least one ramp test will be needed to determine LT2/LTHR.

The intensity state of aerobic (green), an-aerobic (yellow) and vo2max (red) ranges are then evaluated based on the shift from this normal aerobic level, a.k.a. the workout baseline. The workouts that have very little aerobic effort will not contribute to this baseline definition. To have the best possible accuracy with ZoneSense, please ensure that you have easy aerobic sessions in your training regularly to analyze the effort of different types of training. [Suunto]

Here is the ramp test I did today, as shown on the Suunto app.

I’ll have to say that the colours (zones) differ from those that showed during the test, which only had me in the red VO2max zone for a few seconds here it says 10 minutes. I’m assuming that the charts include an element of ‘learning’

Another Test

If my leg holds up, I plan a run similar to the example below (not mine) tomorrow. I should be able to better test extended periods of low-anaerobic effort over 90 minutes or so. The test should also show that Suunto determines different zones for cycling/running.

Here is Suunto’s example of an undulating Half Marathon. It shows relatively constant anaerobic efforts in yellow (typical Z3, Z4) and VO2max efforts above the threshold in red (Z5). You can see that pace (black line) varied throughout the race and trended downwards, i.e., it got more difficult to hold the effort as the time increased.

OK, I managed to do a similar run, which is below. Again, the on-watch colour coding was MUCH higher than shown below in the app post-run chart. I assume it’s because the watch hadn’t been calibrated based on my first use for RUNNING (this run was my first). The chart shows the even exertion I aimed for based on feel, it was hot, and I did that ramp test yesterday, so you can see my power trailing off after an hour. I’d probably say it felt more challenging than the DDFA Index shows after the hour mark.

DDFA – Where will this lead?

I’ve been looking for a heart rate-based way to determine intensity and load for about 15 years. Whenever I’ve worked with some breakthrough method or tech, its limitations soon surface. DDFA looks extremely promising to me. The truth will be in the testing.

Monicardi has a patent on this particular flavour of the calculation, so I’m unsure if or how this would be adopted elsewhere.

This is currently a measure of near real-time intensity, I imagine it’s straightforward to blend this with a CTL/ATL/TSB model. I’d love to see how this impacts load calculations. it could be revolutionary…or not.