OHR vs HRM-Run in everyday life: completely useless (for me)

After posting images, videos, and a dry run of a comparison activity between OHR and HRM-Run values on this thread, I've finally worn my HRM-Run for an entire day, starting and ending at home, and including the entire day at the office (10.5hrs). Using a connectIQ app (Auxiliary HeartRate, see discussion here) and a Fit2Txt converter (thanks Former Member) I plotted these two on a graph that show just how completely useless (and partially random) OHR exactly is (for me).

Now some have suggested in that previous thread that OHR sometimes works poorly for specific people based on many factors such as skin complexion, body hair, etc., but I have used the FR645M in the past and actually found the OHR on it (again, for me) impressively plausible, which is why I never put it through such a test. On the 945 in contrast, I noticed that OHR was so off from the very first day (for example, 90-105bpm while laying on the couch) but until now I was frustrated by not being able to show just how bad, except for verbally explaining it or posting  15-second video clips.

Now I know others are suffering from this as well because the thread above has quite some complains, and seeing how acute the problem is (again, at least for me) - I'm wondering if Garmin will pick up the glove or not, even if not 100% of users seem to be affected. This is not a case of a 5-10% variance, this metric is utterly and completely useless to the point that I will just turn OHR off completely because it's just not worth the battery.  I'm asking, once again, that you find the time to look at these stats and supply some kind of response.

If anyone else is interested in running such a test, just let me know, it's really simple.

Edit: I also ran this test during a running activity and the results were completely different: "OHR vs HRM-RUN during running: amazing (for me)"

Top Replies

  • Former Member
    Former Member over 1 year ago +1

    let the wordplay begin Smile

    nice comparison...but

    did you just prove you can not compare these two how you did because one of them is outside it's usecase ?

    1) OHR best for "activity tracking"…

All Replies

  • This is a 15 minute zoom-in to the part on the very center where the HRM-Run shoots high. The explanation to this is a 4-5 minute run from one office building to another, and it actually seems that perhaps during an activity (for higher actual HR) - the OHR does a better job. It does, however, deal quite badly with the recovery (and anything else)

  • Former Member
    0 Former Member over 1 year ago

    let the wordplay begin Smile

    nice comparison...but

    did you just prove you can not compare these two how you did because one of them is outside it's usecase ?

    1) OHR best for "activity tracking"

    2) HR strap best for logging sport activities

    3) you could be right about the HR strap and the lesser lower heart rate accuracy

    4) OHR is slow in picking up rapid HR changes while HR strap does this much better (ohr-vs-hrm-run)

    5) you used the HR strap out of it's usecase, being most of the time too dry to work properly

    6) case closed Wink

    7) new case : compare OHR+ox vs OHR-ox

    happy & safe sporting

  • It's quite hard for me to understand how easily you dismissed this test and I'm not sure I understand what you meant with your 7 points.

    I did not use the HRM-Run outside of its use case because as long as its moist enough (which believe me, it was) it works just the same whether you're running or sitting in a non A/C room at 31c and 85-90% humidity. Therefore I believe this test is super relevant, and IMO it compares all-day OHR to what I consider to be at least in very close proximity to the actual heart rate (given by the HRM-Run).

    A little number analysis about the % of gap between OHR and HRM-Run HR:

    • Super accurate (less than 3% gap): 10.5% of the time
    • Acceptable (between 3% and 10% gap): 18.6% of the time
    • Not accurate (between 10% and 30% gap): 23.2% of the time
    • Very inaccurate (between 30% and 50% gap): 21.2% of the time
    • Ridiculously inaccurate (more than 50% gap): 31.9% of the time  
  • Former Member
    0 Former Member over 1 year ago

    Edit: I also ran this test during a running activity and the results were completely different: "OHR vs HRM-RUN during running: amazing (for me)"

    this is it....much better use case test Wink

    happy & safe sporting

  • Former Member

    I think the confusion for which you think the test I mentioned in my edit note is a much better use case is because of the mistake I made in naming this post. It should have been "OHR vs. HRM-RUN in day to day: completely useless (for me)" but I couldn't find a way yesterday to edit it. That's why the 2nd one I created reads "OHR vs. HRM-RUN during running: amazing (for me)".

    One is meant to show that during everyday activities the OHR is horrible (again, for me), and the other is that during running it has amazing results.

  • I would like to perform a simliar test. So far I have the CIQ field installed and working. Also used the Fit2TCX converter on the FIT file downloaded from GC. This resulted in a .txt file. Could you please post instructions on how to graph it?

  • Former Member
    0 Former Member over 1 year ago in reply to talsela

    I think the confusion for which you think the test I mentioned in my edit note

    thank you for clarifying Wink

    happy & safe sporting

  • Hi . Do you have a UNIX based OS by chance? That's how I did this. If you do - I can send you some command-line commands to single out the values you need before you can paste them in Excel. Otherwise feel free to send me the txt file and I can do that for you.

  • Yes, I have access to a linux machine so I can give it a go. 

  • This is assuming you recorded a 'running' activity, in that case do the following (I used a 'treadmill' activity to record the day at the office but you can also do it with 'running' and turn off GPS if not needed):

    1. grep -A20 "TYPE=0 NAME=record" original.txt > data.txt
    2. grep -A20 "TYPE=6 NAME=record" original.txt >> data.txt
    3. grep timestamp data.txt | cut -d= -f3 | cut -dT -f2 | cut -dZ -f1 > timestamp.txt
    4. grep heart_rate data.txt | cut -d= -f3 | cut -d" " -f1 > ohr.txt
    5. grep currHeartRate data.txt | cut -d= -f3 > hrm_run.txt

    Now you have three files (timestamp.txt, ohr.txt, hrm_run.txt). Paste their contents in three columns in Excel and plot a simple line graph.

    Notice the time is GMT, and that the 20 in steps 1+2 could differ for you, the idea is that you get enough of the section following the 'TYPE=0' and 'TYPE=6' that includes all three attributes we need, without overflowing to the next section, and that depends on your setup (Stryd for example adds more attributes)

    Let me know if it worked for you.