iain wrote: ↑June 18th, 2025, 4:22 am
The Watts I think would be an issue as many serious users may be interested in comparative performance or meeting thresholds for boat selection. C2's results are the standard.
As far as I understood from various YouTube video's: most national teams use time trials for crew selection, and don't look at power.
iain wrote: ↑June 18th, 2025, 4:22 am
Clearly "pace" is arbitrary, I would hope that generally Watts are reasonably accurate given the meaning of ergometer!
I can't speak for the C2 implementation, but I know the underlying physics and measurement issues extremely well. In my opinion, you are wrong here. There is a bit of a paradox here: there is a direct relation between pace and power displayed, making them essentially interchangeable. However, how you get to them, especially in the presence of noise, is a different matter.
First off: there is only one thing the PM5 really knows, and it is flywheel position and the time it took to get there. The rest is just maths and physics based on that. This is where you get your paradox.
Second of all: power is measured on the flywheel and thus completely ignores the rowers own weight which needs to move up and down a slide. Here strokerate and aggressiveness of the the drive come into play. These is considerable work (50+ Watts) which tends to behave totally different on the water. That part is problematic for both power and pace, so I'll ignore that part in the rest of my text.
In essence, the only theoretical difference between power and pace is the magic number 2.8. One can indeed debate whether the 2.8 is an arbitrary number that relates power to pace. However, it was determined by 2 Olympic rowers. And even RP3 acknowledges it is a pretty decent approximation based on their own research (they actually use of different ratio's for simulating different boats).
Life becomes a lot more interesting when we get to the practical side. Research by the University of Ulm shows that C2 uses the simplified power formula (i.e. average power across the stroke = drag * average angular velocity across the stroke), which completely
ignores the netto acceleration/deceleration of the flywheel across the stroke (see
here for my detailed analysis). Ulm's research confirms this as inconsistent strokes thus can have huge effects on power measurement. So to say that C2 measures power accurately, is extremely debatable to begin with.
With OpenRowingMonitor I actually experimented with using the complete formula next to the simplified formula. Despite ORM having a far more accurate stroke detection and a much more robust approach to flywheel speed measurement than a PM5, results were quite different and the complex formula results in more unstable power measurements (as is my rowing probably), and thus it becomes challenging to compare the two. So power is a really volatile measurement, prone to noise, even when done right. So there is a lot to say for the simplified formula, but it isn't accurate to begin with.
An additional issue is that C2's stroke boundaries are incorrectly defined (as in: easy and reliable to detect, but inaccurate/shifted), the effect of the simple formula is actually enlarged: small measurement errors, especially at the start of the drive, can create significant metrics errors. Although on average the across a stroke this stabilizes it a bit, it is a noisy measurement to begin with.
A key issue is that flywheel speed is the first derivative of flywheel position, and that small measurement errors in position/time reporting tend to be enlarged. So small measurement errors in time/position lead to bigger errors in flywheel speed. As the power calculation depends on flywheel speed measurement, it tends to enlarge noise. When you look at the raw force curve data communicated via the BLE interface you see that happening: that data contains quite some noise and erratic behaviour. When you look at apps like EXR (which doesn't smooth force curves), it is quite noisy. It shows that the first and especially the second derivative are unstable, even for rowers with decades of OTW competition experience.
Looking at linear speed, life becomes a lot easier. The simplified formula provides a direct route to linear distance travelled: Linear Distance = (drag/2.8)^1/3 * Rotational Distance.
This formula is completely independent from stroke detection (although the drag is updated per stroke, it tends to be pretty stable). In essence, it uses a direct linear relation between rotational distance and linear distance. In my book, this is actually a pretty good approximation as the flywheel tends to have the same drag behaviour as a boat. As a PM5 updates distance in-stroke, I suspect they use the same approach.
For speed across the stroke you still need stroke detection. Small time errors tend to drown out in the length of the measurement. The only noise is stroke detection being unstable, and there the PM5's approach is sufficiently robust enough to handle that. In OpenRowingMonitor we use this approach as well, and our experience shows that you can completely mess up stroke detection and still get decent distance and pace estimates. So we calculate power based on pace measured, not the other way around.
So claiming that power is the most reliable measurement in the presence of noise. Can't agree with that.
The SmartRow actually approaches this from the other side: they really measure the force and acceleration of the handle. First integral gives you speed, second integral gives you position. As force x distance travelled is power, there this might hold more true that their power calculation is most robust against noise. Measurement noise tends to create displacement errors, having quite a significant impact of power/distance calculations, making this part extremely challenging. But it would be interesting to compare the output of their force curve with the PM5's.