Validity and Reliability of the VO2 Master Pro
Introduction
VO2 analyzers are worn by athletes to measure performance metrics such as VO2 max andmetabolic equivalents. These metrics are used by coaches to design individualized training programs. VO2measurements can be obtained either directly by measuring the heat a subject generates within a small
enclosed chamber (direct calorimetry), or indirectly through analysis of inspired and expired gases (indirect calorimetry). In-direct calorimetry is the preferred method for measuring athletic performance
because it is simpler to implement and allows for maximal testing (VO2 max) on a stationary bike ortreadmill.
The advent of technology begets VO2 analysis tools that go beyond the conventional lab test.
Newer developments in technology have taken VO2 analyzers off the lab bench and into the field.
However, most portable units require large battery packs, usually housed in awkward backpacks orwaistbands, that may impede the athlete during testing. A study by the University of IOWA found that
increasing body weight with a backpack caused a detrimental effect on VO2 [1]. At fixed treadmill speeds,subjects had an increase in VO2 when loaded with a pack. The VO2 Master Pro is a novel, patented VO2analyzer entirely self-contained to a small mask worn on the subject’s face, eliminating the constraints ofa backpack.
This study aimed to determine the validity and reliability of the VO2 Master Pro when compared
to a VacuMed metabolic simulator. The VacuMed simulator has been validated with the industry-standard
Douglas bag method [2] and has been used to validate popular VO2 analyzers such as the Cosmed K5 [3].
The simulator’s design is based on concepts discussed by Huszczuk and Wasserman [4].
Twenty-four different set points of ventilation and metabolism were applied to two VM Pros, toexamine accuracy and repeatability over a broad range. Bland-Altman plots, ordinary least products
regression (OLP), mean percentage differences and typical percentage error were analyzed. A two-way
random intraclass correlation (ICC) model was used to determine ICC coefficients to further determine
reliability.

MethodTwo VM Pros were used in three tests to determine intra and inter reliability. For each test, thedevice was connected to the flow conduit of a metabolic simulator (VacuMed Model 17056). Atmosphericpressure, temperature and humidity were recorded and used to determine the appropriate metabolic
simulator mass flow rate of gas, as per manufacturer instructions [5]. Data was recorded at each test
condition (table 1) after 30s of controlled input passed, to allow the metabolic simulator to reach stasis.
Reported outputs were collected for a minimum of 10 breaths and averaged into a single recorded value.
Validity was examined using Bland-Altman plots, OLP regression, mean percentage differences
and typical percent errors. Unit reliability was examined using intraclass correlation coefficients, minimum
detectable change and typical error.

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Table 1: Controlled Inputs of VacuMed Metabolic Simulator
StepTidal Volume (L)

12
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24

1.5
1.5
1.5
1.5
2.0
2.0
2.0
2.0
2.5
2.5
2.5
2.5
3.0
3.0
3.0
3.0
3.5
3.5
3.5
3.5
4.0
4.0
4.04.0Respiratory Frequency(Breaths Per Minute)2230405025354555
22303640203035402030364020253035

VO2 STPD (mL)
1000
1300
1600
2000
1500
1750
2100
3000
2000
2300
2600
3000
2500
3000
3600
4000
3000
3300
3600
4000
3500
3625
3750
4000

Results
Table 2: VO2 Master Pro Intra – Inter Device Reliability Results

Ventilation
1.000(0.995 - 1.000)

VO20.999(0.996 - 1.000)

ICC (Inter-Rater)

1.000(1.000 - 1.000)

0.999(0.999 To 1.000)

Standard Deviation (%)
Typical Error Percent (%)
Minimum Detectable Change
Intra-Rater (%)
Minimum Detectable ChangeInter-Rater (%)

0.66
0.62
1.72

2.21
0.52
2.34

1.43

3.45

ICC (Intra-Rater)

Intra and inter repeatability coefficients were greater than 0.999, demonstrating high reliability.
Both ventilation and VO2 had an excellent correlation between the metabolic simulator and the VO2Master Pro, with R2 values of 0.9998 (p < 0.01) and 0.9972 (p < 0.01) respectively (figures 1 and 2). The
confidence intervals of ventilation and VO2 indicated no statistically significant bias, with their slopes
passing through 1 and intercepts through 0. Mean percent differences were less than 1%.
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Table 3: Validation Results

R2Slope (95% CI)

Intercept (95 % CI)

Mean % diff (Min Max)

TypicalPercent Error

Ventilation

0.99980.9977(0.9916 To1.0039)-0.2981(-0.8668 To0.2707)-0.62(-2.85 To 0.25)

0.466

VO20.9972

0.9951(0.9719 To1.0183)

15.461(-51.729 To82.704)

0.22(-5.05 To 3.91)

1.56

Bland-Altman plots demonstrated excellent agreeability and low deviation across the entire
range, with a mean error of 0.5L/min [-1.31,0.332] for ventilation (figure 3) and 2mL/min [-94.0,98.15] forVO2 (figure 4), given a 95% confidence interval.

Figure 1: Ventilation Reported by Simulator Vs VO2 Master Pro (R2 = 0.9998, p < 0.01).

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Figure 2: VO2 Reported By Simulator versus VO2 Master Pro (R2 = 0.9972, p < 0.01).

Figure 3: Bland-Altman Plot of Ventilation with mean of 0.5L/min [-1.31, 0.332].

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Figure 4: Bland–Altman Plot of VO2 with a mean of 2mL/min [-94.0,98.15].

Discussion
This research is subject to several limitations. The VacuMed metabolic simulator is only capableof producing VO2 inputs of up to four liters per minute. This study tested VO2 inputs from one liter up tothe maximum. The Vacumed 17056 has a series of fixed tidal volume selections from one to four liters, inhalf-liter increments. As such, this study was unable to test any tidal volume measurements between thehalf-liter steps, above four liters, or below one liter. In future studies, validation at greater tidal volumes,
ventilations and metabolic rates should be evaluated. In addition, validation at resting metabolic rates
and ventilations should be examined.

Conclusion
The VO2 Master Pro demonstrated excellent agreement with the simulator throughout the entire
tested metabolic range. The mean differences of 2mL/min for VO2 and 0.5l/min for ventilation
demonstrated no proportional or fixed bias, with confidence intervals crossing through zero and one
respectively. Typical percent error was less than 2% for all metrics, easily achieving the 3%
recommendation by the Australian sports institute [6]. Intra and inter reliability of the VO2 Master Pro
were excellent with ICC coefficients greater than 0.99, and minimum detectable changes less than 3.5%
for VO2 and 1.5% for ventilation. These results are comparable to popular VO2 analyzers such as theCosmed K5 [3].

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References[1] M. L. Puthoff, B. J. Darter, D. H. Nielsen and H. J. Yack, "The Effect of Weighted Vest Walking on
Metabolic Responses and Ground Reaction Forces," Medicine & Science in Sports & Exercise, pp.
746-752, 2006.
[2] J. Bunn, J. L. Pittsley, S. V. Baker and J. Yates, "Assessment of accuracy of the Vacu-Med 17053
calibrator for ventilation, oxygen uptake, and carbon dioxide production," Respiratory Care, vol. 56,no. 4, pp. 472-476, 2011.
[3] L. Guidetti, M. Meucci, F. Bolletta, G. P. Emerenziani, M. C. Gallotta and C. Baldari, "Validity,reliability and minimum detectable change of COSMED K5 portable gas exchange system in breathby-breath mode," PLOS ONE, 2018.
[4] A. Huszczuk, B. Whipp and K. Wasserman, "A respiratory gas exchange simulator for routinecalibration in metabolic studies," European Respiratory Journal, pp. 465-468, April 1990.
[5] VacuMed, Operating & Service Manual: Metabolic Calibrator / Simulator No. 17056, Ventura, CA:Author, 2017.
[6] R. T. C. G. Australian Institute of Sport, Physiological Tests for Elite Athletes, 2nd ed., Champaign,
United States: Human Kinetics Publishers, 2013.

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