Thanks @Inigo_Tolosa for you work on this (and your Colleagues).
In the AI Enduance link, it mentions:
Perform a Linear Regression
We perform a linear regression in the space defined by effective mean power/pace
versus effective mean . By ‘effective’ we mean excluding any data points where the power is zero, so it’s the average of all data points with power greater than zero. The mean is taken over the first 10 minutes for running (20 min for cycling) and it is calculated for each of the last 21 workouts. That is, the linear model considers only past sessions. We do not consider the data point given by the new workout yet.
As the linear model is reliant on the last 21 workouts, is it safe to assume if we have <21 workouts that the proceeding steps won’t have a base (or a reliable one) to compare to? Is the readiness then less accurate or not accurate until we have 21 or more?
Also, there was mention of the native Garmin <> H10 connection:
For background, we recommend pairing alphaHRV via ANT+ because it does not care about ANT+ or BLE for data quality (both equally good) whereas ‘native’ Garmin <> H10 connections provide bad HRV data in ANT+ mode if your heart rate is above 120 bpm. This is due to a questionable Garmin setting where they don’t allow more than 2 data points per second in ANT+.
What is different about Ant+ and native connection?
Have you already read the AI linked blog post?
Most answers to your questions are there, and in the 5krunner post linked from that blog.
It´s workouts from the last 21 days BTW.
In the first paragraph there´s something about HRV being dependent on training load. I would rather say the response to training load. Subtle difference, but important IMHO.
No results on that search here by the way, is that field still public? Or will it not show up if (as I am suspecting) the field isn’t populated yet by my Edge?
And heh, glad I just found this topic, I’ve been wondering for weeks already what that error/warning-like beep at the 10-minute mark was for. (During rides BTW, where I think I read that the data should only arrive twenty minutes in?)
All the fields with a result in the top summary are after that menu. These can also be used directly for Fitness charts. FIT file fields that contain a summary metric, but are not automatically fetched by Intervals can be configured here.
The Interval fields are calculated from one or more of your data streams and display in the selection/interval header and as a table column on the Interval data page. These can be the result of calculation of one or more standard/custom data streams and are like ‘cadence’ for example. They display point data or interval/selection average.
On Edge devices, you may have to switch to a profile without the IQ app, or shutdown the unit and restart.
´Queued´ means that it has been transfered to the device, but not yet ´installed´.
Yes, automatic updates are not what we could expect.
The edge devices receive the new file of the app, but they don’t install anything till next restart.
I always restart the edge after installing any new update.
Not sure how it works for watches, but I think that restarting is not required, at least for newest ones
I have been using the Readiness assessment since last week Thursday.
I see in the What’s New notes, it shows 0.9.988 (03/09/2024) as the addition of support for Readiness assessment.
I can assume then, that the Download queue can be ignored, as I have Readiness showing.
Readiness has been there before that version for testing. During summer I have done several updates improving this feature (basically how it is shown) and fixing some bugs.
0.9.988 is the version that provides the final implementation and corresponds to the official announcement.
On edge, the app informs about the version you are running at the bottom of the screen. Check there that it’s updated, but force a restart before if you haven’t done it yet
A new version of alphaHRV is available (0.100.00)
Now the a1 and respiration rate live plots can display from 2 min up to last 2 hours of the activity
It is only available for some of the newest devices: edgexx40/50, Fénix7, FRx65 and above.
After checking possible issues that could compromise performance in older devices, I will probably extend this feature to some few more
