HRV – The big boys are starting to move in

Camera-HRV2016 should be an interesting year for the adoption of HRV.

Many of you are probably already familiar with some of the advanced HR analyses that can be performed with HRV. Hopefully, some of you have benefitted from these and related features.

I have mentioned and discussed HRV for well over two years (others for much longer) and the chatter & understanding on the forums has increased too at the same time.

But what surprised me is the relative lack of adoption by the sports-data analysis platforms. Currently, you only get the in-depth analysis from ithlete/BIOFORCE HRV, Elite HRV, EMFIT QS and some others – ie from the relatively small app-based players.

Sure you can see some of the more important measures (like RMSSD, pnn50, LF/HF ratio, SD1 or SD2**) in sporttracks desktop, or EPOC on Movescount and the recovery time HRV data is displayed on Garmin Connect and Polar Flow. But typically the bigger players just show a few bits of data and NOT analysis. There’s a number..but so what? Where’s the insight and actionability?

elite hrv
elite hrv – actionable stuff, as shown

Finally things seem to be moving.

Elite HRV seem to have based their business model on a great, free app BUT a paid-for team/coaching product. Nice to have your team/squad’s data summarized on a dashboard. So there’s clearly a benefit and opportunity in similar areas for others.


BioForce HRV Review the5krunner
BioForce HRV

Ithlete are probably better known than Elite HRV and have been around for longer. So it was no surprise to see Training Peaks recently partner with ithlete. Great move for ithlete and their credibility (ithlete and BIOFORCEHRV both come under the HRV Fit Ltd organisation). Great move for TP users.

Of course ithlete also have a similar team dashboard (for Liverpool FC, no less) as well as an impending coach app.

KUBIOS – advanced stuff. A bit over my head.

EMFIT QS also seem to have some sort of partnership with Under Armour (I couldn’t get the app-link to work myself). Under Armour are obviously pretty big in the USA especially with some recent app-acquisitions. EMFIT have a great sleeping/waking HRV concept -worth a look if you don’t know them especially for the more serious athletes amongst you.

Sporttracks have long had plans to integrate HRV on the online (MOBI) version – that will likely happen this year. I have hopes for it on the desktop version of sporttracks – sure there are the fields there for the HRV data already…but no analysis…I think we will have to wait for a plugin for that.

golden CheetahThere is/was chatter on the Golden Cheetah forum but I’m not so sure things are moving forwards there…yet.

Anyway just to be clear about what’s needed across a few different segments:

  1. Actionability – simple, high level insights such as traffic lights that are easily actionable/ignorable by the athlete such as train vs. no train.
  2. Team View – Ability of coaches to see all players’ status.
  3. Integration/openness between existing apps and analysis platforms
  4. A one-stop shop – not multiple applications on diverse platforms
  5. ANT+ and BTLE/Bluetooth SMART



** Footnote – Source wikipedia:

Time-domain methods

These are based on the beat-to-beat or NN intervals, which are analysed to give variables such as:

  • SDNN, the standard deviation of NN intervals. Often calculated over a 24-hour period. SDANN, the standard deviation of the average NN intervals calculated over short periods, usually 5 minutes. SDANN is therefore a measure of changes in heart rate due to cycles longer than 5 minutes. SDNN reflects all the cyclic components responsible for variability in the period of recording, therefore it represents total variability.
  • RMSSD (“root mean square of successive differences”), the square root of the mean of the squares of the successive differences between adjacent NNs.
  • SDSD (“standard deviation of successive differences”), the standard deviation of the successive differences between adjacent NNs.
  • NN50, the number of pairs of successive NNs that differ by more than 50 ms.
  • pNN50, the proportion of NN50 divided by total number of NNs.
  • NN20, the number of pairs of successive NNs that differ by more than 20 ms
  • pNN20, the proportion of NN20 divided by total number of NNs.
  • EBC (“estimated breath cycle”), the range (max-min) within a moving window of a given time duration within the study period. The windows can move in a self-overlapping way or be strictly distinct (sequential) windows. EBC is often provided in data acquisition scenarios where HRV feedback in real time is a primary goal. EBC derived from PPG over 10-second and 16-second sequential and overlapping windows has been shown to correlate highly with SDNN




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2 thoughts on “HRV – The big boys are starting to move in

  1. So I’m new to this whole HRV stuff. And I’m having trouble interpreting results. I’ve only been tracking for less than a week but the values seem almost random. My HRV actually increased after a long run and have decreased after rest days. Is that kind of day to day randomness normal? Are you looking for day to day changes or long term trends?

    I’ve been using a connectiq app on my 920xt. Does HRV calculation have a single definition or do different apps have different algorithms? If so, which are considered the “best?”

    When testing I’ve been breathing in and out deeply based on timed instructions from the app. Should I be breathing more normally? Because some apps can track HRV while sleeping and you can’t exactly breathe on a timer while asleep…

    1. start off by comparing like with like. waking reading for 2 minutes before you get out of bed. about 7 breaths/minute. you need to look at deviations from a baseline that emerges in your RMSSD value. higher generally better. however your 920 (like mine) isn’t really going to help to much beyond that. instead get one of the apps; elite hrv is free and a Bluetooth hrm and off you go. that’s the best place to start. after a while read a bit more about it and you can start measuring other hrv things

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