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O2 during
exercise
Department of Anesthesia and Division of Pulmonary and Critical Care Medicine, Mayo Clinic and Foundation, Rochester, Minnesota 55905
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
APPENDIX
ACKNOWLEDGEMENTS
FOOTNOTES
REFERENCES
ABSTRACT 
Proctor, David N., and Kenneth C. Beck. Delay time
adjustments to minimize errors in breath-by-breath measurement of 
O2 during exercise.
J. Appl. Physiol. 81(6):
2495-2499, 1996.
If the delay time between gas concentration and
flow signals is not adequately corrected during breath-by-breath
analysis of expired gas, an error in calculation of oxygen consumption
(O2) will result. To
examine the frequency and delay time dependences of errors in
O2 measurement, six healthy
men exercised at 100, 200, and 250 W on a cycle ergometer while
breath-by-breath assessment of
O2 was made simultaneously
with collection of expired air. Subjects breathed first at normal rates
(15-30 breaths/min) and then at 70 breaths/min. Each subject
performed each level of exercise twice by using erroneous values for
the delay time between gas concentration and flow signals. At normal
breathing frequencies, errors in
O2 measurement were
±10% over the full range of delay times used, and the errors were
not tightly correlated with variations in delay times from optimum.
However, at 70 breaths/min, errors approached ±30% as the
variations in delay times deviated ±0.1 s from the optimal, and the
errors were highly correlated with the variations in delay times. We
conclude that there is greater potential for errors in
O2 measurement with
incorrect delay time at higher breathing frequencies. These findings
suggest that the optimal delay time for breath-by-breath systems should
be adjusted by using high breathing frequencies.
human performance; indirect calorimetry; hyperpnea; gas exchange; equipment validation; oxygen consumption
INTRODUCTION OXYGEN CONSUMPTION
( To determine the frequency range of interest in the clinical setting,
we retrospectively reviewed the exercise responses of 113 adult
patients referred to our laboratory (Fig. 1). At rest, breathing rates ranged from ~5 to just over 30 breaths/min. At maximum exercise, the breathing rates were considerably higher, ranging
from 20 to >60 breaths/min. About 14% of the patients breathed at
frequencies >55 breaths/min near maximal exercise. Because of the
emphasis often placed on
In this paper, we examine the errors in breath-by-breath measurements
of METHODS
O2) and carbon dioxide
production (CO2) are commonly
used to characterize the response to exercise in both the research and
clinical settings (13). Originally, the measurements were made by using
timed collections of expired gas (8). Recently, rapid gas analyzers and
computer technology have made breath-by-breath analysis of gas exchange
practical and commonplace by using commercially available equipment
(5). Although these systems offer the advantage of being able to
present the data in real time, there are some technical errors that can make breath-by-breath measurements inaccurate (13). One of these errors
is the delay time between the expired gas and expiratory flow signals
(6, 9, 13). The gas concentration signal is delayed by
~0.15-0.65 s compared with the flow signal in most commercially
available systems. This is due to delays in transport of gas in the
sampling tubing and delays introduced by electronic signal processing
(2). This delay is handled in the computer by shifting the signals
representing gas concentrations by an appropriate number of sample
periods to properly align the gas concentration and flow signals before
performing the integrations necessary to determine
O2 and
CO2. The delay time is
usually determined during calibration by introducing a rapid change in gas concentration and measuring the response time of the gas analyzer. Errors can occur in this calibration procedure. For instance, a small
part of the total delay time consists of valve-actuation times that can
only be determined empirically and that can change due to component
failure. If the delay time of the gas concentration signal is
underestimated by the computer,
O2 and
CO2 will be underestimated,
whereas if the shift is too large,
O2 and CO2 will be overestimated (5,
9, 13). Because a constant time shift represents a larger fraction of
the total breathing cycle of shorter breaths, the error will be
magnified at higher breathing frequencies (4, 6, 13). Thus it is
important that breath-by-breath systems be validated over an acceptable frequency range.
O2 measurements made near
maximal exercise (8, 11), these data emphasize the need to ensure
proper equipment performance up to ~60 or even 70 breaths/min.
Fig. 1.
Histogram showing no. of patients with observed breathing frequencies
measured at rest and near maximal (Max) exercise during incremental
cycle ergometer-testing protocol in a clinical exercise- testing
laboratory. Note that 14% of patients breathed at >55 breaths/min at
peak exercise (vertical dotted line) and that there were a few patients
in this limited retrospective review who breathed >70 breaths/min.
These data emphasize need for adequate equipment validation over a wide
range of breathing frequencies.
[View Larger Version of this Image (21K GIF file)]
O2 during exercise by
systematically varying the gas-sampling delay times and breathing
frequency. Because of the frequency dependence of the error,
validations performed at relatively low breathing rates may be within
acceptable limits, whereas validations at higher but still
physiologically reasonable breathing rates may show significant errors.
O2,
CO2, and expired
minute ventilation (E) were made by
using a commercially available automated system (Medical Graphics,
model CPX/D, St. Paul, MN) modified to interface to a respiratory mass
spectrometer (Perkin Elmer 1100). Subjects breathed through a
disposable pneumotachograph that contained the mass spectrometer
gas-sampling port. The pneumotachograph registered flow by comparing
impact and stagnation pressures in a region of slight narrowing of the
flowing gas stream. Linearity of the flowmeter system was ensured by
the manufacturer, who applied multiple correction factors to adjust for
nonlinearity (12). The sampling rate of the mass spectrometer was 60 ml/min, and the sampling line was 200 cm long. The pneumotachograph was
connected to a Hans-Rudolph non-rebreathing valve (80 ml total dead
space volume) so that expired air could be periodically collected in meteorologic balloons (latex rubber) and subsequently analyzed for
expired O2 and
CO2 concentrations (mass
spectrometer) and volumes (Tissot gasometer). Calculations of
O2 and
CO2 were performed by using
the Haldane transformation (8). This permitted the comparison of
breath-by-breath and bag (Bag) determinations of
O2 and
E.
The breath-by-breath measurement system was calibrated by using the
system's standard computer programs and precision-grade gas mixtures.
The pneumotachograph was calibrated by using a 3-liter calibration
syringe, again following procedures dictated by standard calibration
routines. Multiple syringe strokes were performed over a range of flows
to check the linearity of the pneumotachograph response. Calibrations
were performed with the pneumotachograph attached to the
non-rebreathing valve, exactly as configured during data collection.
Protocol.
Subjects completed separate bouts of light (100 W,
n = 6), moderate (200 W,
n = 6), and heavy (250 W,
n = 4) exercise at self-selected pedaling rates (55-75 revolutions/min) while breath-by-breath gas-exchange measurements were continuously monitored. To examine the
effect of altering the delay time between gas concentration and flow
signals on breath-by-breath measurements, two bouts of exercise were
performed at each intensity, each with a randomly chosen delay time
varying between 0.11 and 0.25 s. Two bouts with different delay times
at each of three power outputs gave six bouts total for each subject.
The delay time of the computerized system was adjusted during a 10- to
15-min rest between bouts of exercise by manual change of the internal
correction factors and recalibration of the system, as outlined in the
Appendix.
Each bout of exercise lasted 6 min and was preceded by 2 min of warm-up
at 50 or 100 W. Subjects breathed normally during the first 4 min. A
1-min Bag collection was made during the fourth minute. To examine the
effect of high breathing rates on gas-exchange measurements, subjects
performed the final 2 min of each bout while breathing at 70 breaths/min. A 1-min Bag collection was made during the second minute
of the high breathing rate (i.e., sixth and final minute of the bout).
The subjects had all attained a near steady state in the minute of data
collection, as judged from the breath-by-breath display of
O2 and
CO2 over time. A metronome
was used to pace the subjects' breathing, and they were coached to
reduce their tidal volume to avoid lightheadedness associated with
hypocapnia. The two Bag collections (minutes
3-4 and
5-6) were compared to assess
the oxygen cost of the hyperpnea.
Data analysis.
The breath-by-breath O2 and
E were calculated over the exact period
of Bag collection. The mean
O2 for the
interval was computed by first summing the VO2
contributions from each breath and dividing by the sum of breath times
for the interval.
Percent errors in O2
measurement were calculated as (breath-by-breath 
Bag)/Bag × 100, where breath-by-breath and Bag data were obtained over the
same sampling period. The optimal delay time was determined from the
intercept of %errors in O2
measurement regressed against delay time. Analysis was performed on
data obtained at normal breathing rates and during hyperpnea (70 breaths/min).
RESULTS
The average E and
O2 responses obtained from
the 1-min Bag collections are shown in Table
1. At all three power outputs, E was 42-90% higher while subjects
were breathing at 70 breaths/min than during normal breathing rates.
Bag-derived O2 values did not
differ significantly between normal and high breathing rates while
subjects were cycling at any of the exercise levels, indicating low
work of breathing in these normal subjects. The increases in
O2 with increasing exercise
intensity were very close to values predicted for cycle ergometry,
according to equations published by the American College of Sports
Medicine (1). During the heavy work intensity (250 W),
O2 responses of all four
subjects studied were higher during hyperpnea (70 breaths/min) than
during normal breathing, though the difference failed to reach
significance.
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Figure 2 shows the induced errors in
breath-by-breath determinations of
O2 expressed as the %error
compared with the corresponding Bag values. When subjects breathed at
normal frequencies (A), induced
errors in breath-by-breath determinations of
O2 were ±10% across the
range of delay times used (i.e., 0.11-0.25 s). By contrast, during
high-frequency breathing (B; 70 breaths/min), breath-by-breath measurement errors induced by variations
in delay times ranged from 30 to 30%.
The corresponding mean errors in E (data
not shown) ranged from 0 to 2.7%. The
E errors were only statistically
significantly different from zero (P < 0.05) during the high-frequency breathing at the 200- and 250-W
work intensities. However, the errors in
E measurement were small in comparison
with the O2 measurement
errors and, as expected, were not correlated with the delay times
(P > 0.05).
As shown in Fig. 2 and Table
2, at high breathing
rates, errors in O2
measurement were much more tightly correlated with delay times compared
with low breathing rates. The correlation coefficients between delay
times and %error in O2
measurement were lower at normal breathing frequencies compared with
hyperpnea. The lower correlation coefficients resulted in wider
confidence intervals for the delay times intercept at 0% error. In
fact, at 100 and 200 W, the delay time intercept was virtually
indeterminate from our data. Average delay time intercept obtained from
data for high breathing rates was 0.18 s, which is shorter than the 0.20-0.22 s reported initially by the equipment calibration
routines. The use of 0.20-0.22 s gave small errors in
O2 measurement at normal
breathing rates and 10-15% errors at 70 breaths/min (Fig. 2). The
0.18 s is also shorter than the delay time for the mass spectrometer
alone (Fig. 3 as discussed in the
Appendix).
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DISCUSSION
The important findings of this study are that errors in
O2 measurement by using a
breath-by-breath gas exchange measurement system can be 30% at high,
but still physiological, breathing frequencies when errors are close to
an acceptable range at lower breathing frequencies. Although errors as
high as 30% are unlikely when equipment is calibrated properly, this
study emphasizes the magnification of error at high breathing rates. It
should be noted that the manufacturer of the CPX/D system we used
(Medical Graphics) routinely performs validation testing at high
respiratory rates when in development and on each unit before it is
shipped. Our system required revalidation because we used a mass
spectrometer in place of supplied gas analyzers. These errors were not
due to errors in measurement of E or
errors in the gain of the gas analyzers but were due to induced errors
in delay times used to align flow and gas concentration signals. These
results stress the importance of using high breathing frequencies
during initial validation of automated breath-by-breath systems used to
measure O2.
The effect of delay time on measurements of
O2 and
CO2 by using
breath-by-breath methods has been discussed by others (2, 4, 6, 7, 9).
Although Beaver et al. (4) made the point that the errors would be
magnified at a higher breathing frequency, no studies have
systematically examined the effects of breathing frequency on the error
in measurement of O2.
Huszczuk et al. (7) demonstrated lack of frequency dependence of
O2 in a well-tuned system by
using a gas-exchange simulator. We found, as predicted (4), that the
errors in O2 measurement were
magnified by subjects breathing at high frequencies and that these
errors were not due to mismeasurement of
E.
The optimal delay time is the time shift that produces zero error in
measurement of O2. At normal
breathing rates, the width of the statistical 95% confidence limits
for delay time at zero error was wide, being essentially indeterminate
at rest and ~60 ms at 250 W. Hughson et al. (6) showed a similar
confidence limit in one subject exercising at 200 W. However, their
technique of recalculating the same data by using varying delay times
should have produced somewhat less scatter in the data than our
technique of making multiple measurements in different subjects. The
slope of the regression of %error against delay time ranged from
39 %/s at 100 W to 124 %/s at 250 W. Our slope at 200 W,
expressed in
ml · min
1 · ms1
[0.68 s1 × (2,578 ml/min)/(1,000 ms/s) = 1.75 ml · min1 · ms1],
compares favorably with a slope that can be derived from data presented
by Noguchi et al. (9) of 1.4 ml · min1 · ms1
on the basis of measurements in three subjects. In our study, the slope
of %error against delay time increased and the confidence limits
narrowed considerably at higher breathing rates. The delay time
intercepts were similar over a wide range of exercise intensities. Because optimal delay times that minimized the errors were similar across exercise intensities, adjustment of delay times at low-intensity exercise may be safely extrapolated to higher intensities.
These results emphasize the importance of initial validation of gas-exchange measurement systems by using high breathing frequencies. An alternative to Bag collection of human expired air is use of a mechanical gas-exchange simulator (7). High breathing frequencies are important during validation because errors observed during normal breathing frequencies were not as strongly correlated with delay time and were close to acceptable limits over a range of delay times. It should be stressed that these errors will be produced by any breath-by-breath measurement system when delay times used are in error and are not a deficiency in the design of commercial products. Both initial validation and periodic monitoring of measurement errors are recommended because there are a number of factors that can cause delay times to change, such as buildup of debris or moisture in gas-sampling lines, variations in the gas-sampling rates through the analyzer, or changes in length of the sampling tubing. It should be noted that stable daily calibrations (including a procedure to determine delay time) should be sufficient to ensure accuracy once equipment is initially validated. However, when equipment is serviced, repeat validation is useful to ensure adequate system performance.
In summary, we found that errors in
O2 measurement due to varying
the delay time factor by using a breath-by-breath gas-exchange system
reached 30% at high, but still physiological, breathing frequencies
when the induced errors were close to acceptable range at lower
breathing frequencies. These findings emphasize the need for adequate
initial and periodic validations of breath-by-breath gas-exchange
measurement systems covering the full range of breathing frequencies
likely to be encountered in practice.
ACKNOWLEDGEMENTS
This work was supported by the Mayo Foundation, National Institute of General Medical Sciences Grant GM-08288, and a General Clinical Research Center grant (Division of Research Resources Grant M01-RR00585).
FOOTNOTES
Address for reprint requests: K. C. Beck, Pulmonary Function Lab, S-3 Plummer Bldg, Mayo Clinic, Rochester, MN 55905.
Received 7 July 1995; accepted in final form 22 July 1996.
APPENDIX
To perform these studies, we used CPX-D system from Medical Graphics (St. Paul, MN) by using calibration software version 3.8 and breath-by-breath data-acquisition software version 3.3. On consultation with engineers from Medical Graphics, we edited the CAL.CFG file, changing the numbers at the end of lines 202 and 203 to vary the delay times reported. It should be noted that Medical Graphics performs validation studies at high respiratory rates both in development and before each unit is shipped. We repeated validation because we used their system with a mass spectrometer in place of standard gas analyzers.
The delay time reported by the calibration routine of the commercial software represents a sum of many components. To see how the reported delay time corresponded with the delay time of the mass spectrometer by itself, we performed the following "pop" test. We arranged an electrical circuit to produce a voltage when the sampling line of the mass spectrometer was sampling calibration gas. A thin wire that was part of the circuit was arranged so that it would break at the precise moment the tip of the sampling line from the mass spectrometer exited flowing calibration gas. In this way, we could rapidly pop the sampling line out of the flowing gas to sample room air, obtaining an electrical event signal when the sampling line began sampling room air. Results from this test are shown in Fig. 3. The delay in the gas concentration signal measured from the point the sampling line exited the calibration gas to the point where the O2 signal had increased by 10% was 240 ms. This time is ~50-60 ms longer than the delay time reported by the commercial software. This difference in delay time represents the time needed to process the flow signal and actuation times for small switching valves that are used in the determination of delay time. The manufacturer ordinarily includes a correction for these signal-processing delays.
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