In

**part 4**of this series, I made baby steps with a commercially available footpod called**Stryd**and ran with it in in what is billed the 'fastest half marathon in the world'. I measured only power and made some indirect assessments of what would be a safe threshold power level to run that distance with current fitness level. I also looked at running effectiveness.
Today, I kept the Stryd aside and turned to a neat powermeter treadmill at the home gym called the

**Cybex 770T**with Intelligent Suspension. In**Part 2**, I explained how this treadmill uses an AC motor with a variable frequency inverter drive. Treadmill belt speed is based on output frequency to the motor and according to the OEM, it would need no calibration. Infact, I measured the belt speed and even measured the time it would take for 10 revolutions. Comparing this to the treadmill speed readout gave a 1:1 match.
The objective of today's short test was to study how the treadmill maps power output to speed, mass and grade.

**Objective :**Curiosity, mostly. How does machine power vary with pace and mass? Perhaps mapping this would help in comparisons when doing the same with Stryd powermeter (to be tried later).

**Test Protocol :**Enter my correct weight of 64.5kg into the machine. Keep speed constant at 8kph (7:30 min/km) pace and get power readouts at 0%, 1%, 2%, 3%, 4%, 5% and 10% incline settings. Repeat this sequence with 10 kmph (6:00 min/km) and 12 kmph (4:36 min/km) speeds. I repeated the same experiment by entering weights of 70kg (+5 kg mass increase) and 80 kg (+10 kg). The total number of readings taken were 63.

**Results :**

Power output readings to corresponding mass and grouped by pace are shown below.

Fig.1 : Power table for 3 speeds and 3 weights for 7 different grades as measured on Cybex 770T.

For a given running pace, the power reading was linearly related to grade. Below, I show example of linear power lines for my weight 64.5kg and 70kg and 80kg for running pace 13kph (4:36 min/km). Also, both the y intercept (power at 0 grade) and slope of the line increase with mass.

Fig.2 : Power vs Treadmill incline for weight input of 64.5kg (yellow line), 70kg (orange line) and 80kg (green line).

To understand how power is mapped to speed, pace and mass, I performed a linear regression on the response Power with predictors speed, pace and weight input to the machine.

The regression equation I obtained was :

*TREADMILL POWER (W) = - 225 + (7.46 x GRADE) + (3.00 x MASS)*

**+ (18.8 x Speed)**[tested for running speeds only > 8kph]
where grade is expressed in % , Mass in kg, and Speed in kph.

*An equation is derived to map treadmill belt power to running speed, grade setting and pace for the Cybex 770T treadmill.*

*The key takeaway is that maintaining the same power on an incline as on level ground running is impossible unless running pace is slowed down. For perspective, if a 64kg person ran on this treadmill at 8kph with a 10% incline setting, he'd have to slow speed by 1 min/km or more to match the same power reading obtained with a 0% incline.*

*My finding is that for a given weight, the power reading increases by 1.4 times between 0% and 10% grade. My finding is also that for a given grade, power increases by 1.24 times between 64.5 kg and 80 kg.*

*The equation tends to slightly overpredict at lower speeds and underpredict at higher speeds for a given weight. It also tends to slightly overpredict at lower weights and underpredict at higher weights for a given speed. The sweetspot of the prediction seems to be at a pace of around 10 kph where errors are less than 2%.*

In the next post, I'll compare running uphill and power numbers using the Stryd to see if these same general takeaways are maintained. Ciao!

## 2 comments:

Hello Ron, do you have this table where I can do the calculations? My numbers are differents from your table and I would like to know why.

Best Regards

Ronaldo

You have to do some number crunching in a statistics package to get a general regression formula.

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