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Monitoring of Ventilation During Exercise by a Portable Respiratory Inductive Plethysmograph^*

^* From the Pulmonary Division, Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland.

Correspondence: Konrad E. Bloch, MD, FCCP, Pulmonary Division, Department of Internal Medicine, University Hospital of Zurich, Rämistrasse 100, CH-8091 Zurich, Switzerland; e-mail: pneubloc{at}usz.unizh.ch

	Abstract

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Objectives: To evaluate the accuracy of a portable respiratory inductive plethysmograph that allows the monitoring of ventilation without airway instrumentation during exercise in unrestrained subjects.

Design: Validation of a novel technique by comparison to a reference standard.

Participants: Thirty-one subjects, including 20 healthy volunteers, 6 patients with COPD, and 5 patients with congestive heart failure.

Interventions: Participants performed progressive treadmill exercise to exhaustion. Ventilation was monitored by a novel battery-powered, miniaturized, and calibrated respiratory inductive plethysmograph. Inductance sensors encircling the rib cage and abdomen were built into an elastic body garment. A pneumotachograph attached to a mouthpiece served as the reference method.

Measurements and results: Breath-by-breath comparisons between the inductance plethysmograph and pneumotachograph over the course of progressive exercise to exhaustion revealed no significant bias of respiratory cycle time, tidal volume (VT), and minute ventilation. The corresponding limits of agreement (bias ± 2 SDs) were ± 6%, ±17%, and ± 17%, respectively, for 2,480 breaths. Comparisons of mean values averaged over 20 breaths revealed improved limits of agreement of ± 1% for cycle time, and ± 7% for tidal volume and minute ventilation, respectively, for 124 comparisons. Agreement between methods was similar for patients and healthy subjects. Among the patients, maximal minute ventilation was lower, and breathing was more rapid and shallow than in healthy subjects. Obstructive lung disease was associated with a shorter duty cycle than heart failure.

Conclusions: The portable respiratory inductive plethysmograph accurately estimates ventilation during treadmill exercise, and identifies differences in breathing patterns among patients with pulmonary or cardiac diseases and healthy subjects. This unobtrusive monitoring technique is promising for application in ambulatory patients.

Key Words: breathing pattern • exercise • inductive plethysmography • noninvasive physiologic monitoring • pulmonary ventilation

	Introduction

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Spirometric assessment of lung function and evaluation of the ventilatory response to exercise by standard techniques requires patient cooperation and airway instrumentation. Since these measurements alter the breathing pattern and ventilation,¹² and are usually performed in a laboratory, they may not reflect ventilation during usual daily physical activities of patients at their home or workplace. Portable equipment for unobtrusive and cooperation-independent monitoring of ventilation in ambulatory patients would therefore be desirable. Chest surface sensors of an inductive plethysmograph or magnetometer have been used for noninvasive ventilatory monitoring during sleep and for physiologic research, but the application of these techniques in an ambulatory setting has been hampered by the lack of portable equipment and by the tendency of conventional sensors to dislocate with body motion.³⁴⁵⁶

Recently, a portable respiratory inductive plethysmography (RIP) system has become commercially available. It comprises a novel patient interface consisting of a snugly fitting, elastic garment incorporating rib cage and abdominal inductance sensors, thereby minimizing the propensity for sensor dislocation. The corresponding battery-powered digital signal-processing unit has the weight and size of a palmtop computer. Since this equipment seems promising for application in outpatients under various conditions at rest, and during exercise, the purpose of this study was to evaluate its accuracy for measuring tidal volume (VT) and respiratory timing during exercise. We have previously demonstrated the accurate measurement of ventilation by RIP during maximal bicycle exercise in a small number of healthy subjects.¹ To extend the validation of RIP to the measurement of ventilation during a form of physical activity that is more representative of the daily activities of many subjects, the current protocol included treadmill exercise. Furthermore, we studied a larger number of healthy volunteers as well as patients with cardiac and pulmonary diseases to evaluate the effect of the disease and associated abnormalities of chest wall motion and breathing pattern⁶⁷⁸ on the accuracy of ventilatory monitoring by RIP. We hypothesized that the measurement of ventilation by RIP in healthy subjects and patients during exercise is valid within the published standards.

Lung volume changes are commonly estimated by body surface sensors of magnetometers or RIP sensors placed at the rib cage and abdomen based on the classic two-degrees-of-freedom model of chest wall excursions described by Konno and Mead.⁹ Smith and Mead,¹⁰ and McCool and coworkers¹¹ proposed a three-degrees-of-freedom model that included an additional term reflecting axial chest wall motion related to flexion and rotation of the vertebral spine and pelvis. To investigate the potential effect of such movements on the accuracy of RIP (with rib cage and abdominal sensors only), we compared measurements among volunteers carrying a custom-fitted and loaded backpack incorporating a metal frame that stabilized their back, and volunteers with unrestricted spinal motion. We hypothesized that restricting spinal motion by the backpack would not significantly improve the agreement between RIP and flowmeter-derived estimates of ventilation.

	Materials and Methods

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Subjects and Patients
A total of 31 individuals, among them 20 healthy volunteers, 5 patients with severe congestive heart failure (CHF), and 6 patients with COPD (Table 1 ) gave informed consent to participate in the study, which was approved by the hospital ethics committee. The healthy volunteers were recruited from among hospital staff. Any medical condition requiring treatment at the time of the study was an exclusion criterion. The patients were recruited from among successive patients who had been referred for cardiopulmonary exercise testing to evaluate physical performance and dyspnea during exercise. Of the five patients with heart failure, three were studied during regular follow-up and two were evaluated for possible cardiac transplantation. Three had severe coronary artery disease from dilated cardiomyopathy. Four of the six COPD patients were candidates for lung volume reduction surgery, and two were referred for evaluation of progressive symptoms.

View larger version (38K): [in this window] [in a new window] [Download PPT slide]   Figure 1.. Schematic drawing of the portable RIP system. The RIP transducers encircling the rib cage and abdomen consist of shielded electrical wires arranged in a sinusoidal array and sewn into a snugly fitting, elastic garment directly worn against the skin. The transducers are connected along with the ECG electrodes to a signal-processing and signal-recording unit that was the size of a palmtop computer. It was worn on a belt or in a pouch. The pulse oximeter sensor and the accelerometers incorporated in the garment, and connected to the same recorder, are not shown.

Protocol
Ventilation was simultaneously monitored by RIP and the flowmeter during progressive treadmill exercise to exhaustion. The initial speed was 1.5 miles per hour, and increased approximately every minute by 0.5 to 1 mile per hour. The treadmill was inclined at 12° in healthy subjects, and between 0° and 3.5° in patients to achieve an exercise duration of at least 5 min. Subjects and patients were encouraged to exercise to their exhaustion, but no other instructions were given. Tests were terminated according to standard criteria,¹³ and when the subject or patient could no longer keep up with the speed and wished to stop. Ten of the 20 healthy subjects were carrying a climber’s backpack loaded to a weight of 11 kg. It had a built-in metallic frame that stabilized their back, and was closely attached to the body by the shoulder harness and a belt around the abdomen, located approximately at the iliac crest.

Data and Statistical Analysis
At the end of tests, the data were downloaded from the RIP recorder to a computer and were analyzed by dedicated software (VivoLogic; VivoMetrics). It allowed the review of raw and processed data on a video screen, automatic calibration, and breath-by-breath calculation of breathing pattern variables and heart rate as previously described.¹⁶ Relative gains in rib cage and abdominal RIP signals were determined at the beginning of the tests during 5 min of regular breathing performed in a standing position by the qualitative diagnostic calibration method.¹⁴ The RIP sum signal was calibrated in absolute units (liters) by comparison to the integrated output of the flowmeter over the duration of 20 breaths.¹ Inspiratory VT, total duration of respiratory cycle (TT), and inspiratory minute ventilation (I), which is the product of VT and breath rate, were measured breath by breath as described previously. Rib cage abdominal motion was assessed by computing the rib cage contribution to VT, and the phase shift between rib cage and abdominal excursions, as described recently.¹⁵ The heart rate was determined by the ECG incorporated in the portable RIP recorder. The spiroergometry unit measured respiratory variables breath by breath, and these data were matched with corresponding values obtained with the RIP device by means of a common time stamp on the ECG signals of both systems that synchronized the recorders.

To compare equal numbers of breaths from each individual despite the variation in exercise duration, four periods of 20 breaths from low, intermediate, submaximal, and maximal exercise intensity, respectively, were analyzed (ie, a total of 80 breaths per individual). Data collected after the initiation of walking when the breathing pattern had stabilized corresponded to low intensity. Intermediate intensity was defined as a period within the first half of the duration of exercise after low intensity. Submaximal data were collected within the second half of the duration of exercise, before maximal exercise. Maximal values of physiologic variables were defined as their mean over the final 20 breaths during maximal exercise. The predicted maximal heart rate was calculated as 220 – age, and the predicted maximal oxygen uptake (o₂max) was computed according to Wassermann et al.¹⁶

The data are summarized as the mean ± SD. Agreement between methods was evaluated by computing the mean difference (bias) and limits of agreement (± 2 SDs of the bias).¹⁷ The mean disagreement between methods was computed as the absolute difference in percent of the mean value by the two methods. Comparisons between groups were performed by analysis of variance followed by the Newman-Keuls test, where appropriate. A probability of p < 0.01 was considered to be significant.

With a sample size of 2,480 comparisons (for breath-by-breath data), and 124 comparisons (for mean data averaged over the duration of 20 breaths), the study was powered with > 0.95 to detect a 2% bias between methods in VT and VEi, and a bias of 1% in TT ( 0.05). To evaluate whether a nonsignificant result of a comparison between the two methods can be considered as a true absence of difference (ie, equivalence), we employed the confidence interval approach, as described by Jones et al.¹⁸ According to this method, equivalence is assumed if the confidence interval of an observed difference lies entirely within a specified equivalence range, which was defined as ± 2% for VT and I, and as ± 1% for TT.

	Results

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A satisfactory snug fit of the available standard sizes of RIP garments was achieved in all subjects and patients, and RIP recordings were successfully obtained in all of them. Figure 2 shows recordings in a healthy female subject, and a male patient with COPD. Table 2 summarizes o₂max, heart rate, and breathing pattern variables over the final 20 breaths during maximal exercise. The o₂max was above the predicted value in healthy subjects, and their maximal heart rate was close to the predicted value achieved at the end of the exercise tests. In contrast, o₂max was significantly reduced in patients, in particular in those with severe CHF, and they did not reach their predicted maximal heart rate. All patients with CHF were on ß-blocking drugs. The highest I and breath rate were observed in healthy subjects carrying a backpack. They achieved their higher I compared to healthy subjects not carrying a backpack through a higher breath rate, while VT was lower. Patients with COPD had a higher breath rate/VT ratio (ie, a more rapid shallow breathing pattern) and a shorter duty cycle (TI/TT) than healthy subjects and patients with CHF (Table 2). In addition, patients with COPD had a greater rib cage contribution to VT and a greater asynchrony of rib cage vs abdominal motion (quantified by the phase angle)⁶¹⁵¹⁹ than patients with CHF.

View larger version (59K): [in this window] [in a new window] [Download PPT slide]   Figure 2.. Representative recordings obtained in a healthy female patient (top, A), and a male patient with COPD (bottom, B). The left panels include recordings over the entire exercise duration. Walking can be identified in the signal of an accelerometer incorporated in the garment and arranged to provide a qualitative measure of acceleration in the spinal axis. In the patient with COPD (bottom, B, left), the increase in end-expiratory lung volume suggesting dynamic hyperinflation can be appreciated with progressive exercise in the sum signal of the inductive plethysmograph operated in DC mode. The end-expiratory lung volume level at the beginning of exercise is assigned a value of 0 L on the volume scales. The right panels show several breaths during maximal exercise. Minor deflections superimposed onto respiratory waveforms of the inductance signals are related to body movements. These artifacts do not affect accurate breath detection by the computer algorithm, as can be verified by the vertical lines reflecting the breath-by-breath values of I. Sum = inductive plethysmographic sum volume signal; RC = rib cage volume signal; AB = abdominal volume signal; HR = heart rate.

View larger version (32K): [in this window] [in a new window] [Download PPT slide]   Figure 3.. Identity plots of I (top left, A), VT (middle left, C), and TT (bottom left, E) recorded by RIP vs corresponding values by the flowmeter in 10 healthy subjects without backpack (), 10 subjects with backpack (•), 6 patients with COPD (), and 5 patients with CHF (). Each of the 31 individuals is represented by four data points representing mean values averaged over periods of 20 breaths, respectively, over the course of progressive stages of exercise intensity up to exhaustion. All paired values of TT fall within ± 5% of identity, and values of I and VT fall within ± 10% of identity. Right top, B, middle right, D, and bottom right, F: plots of differences in I, VT, and TT, respectively, measured by the two methods (expressed in percent) vs their mean value. The full and dashed lines represent the mean difference (bias) and the limits of agreement (± 2 SDs of the bias), respectively.

	Discussion

TOP Abstract Introduction Materials and Methods Results Discussion References

The o₂max and heart rate over the last 20 breaths during maximal exercise indicated a high intensity of exercise performed by the healthy subjects (Table 2). In patients with severe CHF, heart rate might not have reached the predicted maximal value because of the treatment with ß-blocking agents or because of premature exercise termination due to leg weakness or insufficient effort. In patients with COPD, exercise was most likely limited by their inability to increase ventilation. Consistent with the exhausting ventilatory effort they performed, their breathing pattern was more rapid and shallow than that of patients with CHF or healthy subjects, as quantified by a high breath rate/VT ratio (Table 2). Further characteristics that differentiated patients with COPD from those with CHF were a short TI/TT, a high rib cage contribution to VT, and asynchronous rib cage-abdominal motion (ie, a greater phase angle) [Table 2]. These breathing patterns were consistent with our previous observations in patients with COPD at rest.⁶

With no significant bias for breath-by-breath estimates of TT, VT, and I, and limits of agreement of 8% for TT and 18% for both VT and I (Table 3), the accuracy of portable RIP in the current investigation compares favorably to results achieved in previous studies using stationary equipment in resting patients with chronic obstructive lung disease undergoing lung volume reduction surgery,⁶¹⁵ in sleep apnea patients during sleep studies,⁴⁵ and in healthy volunteers during bicycle exercise¹ and treadmill exercise.²⁰ In an earlier study,¹ we had to tape the RIP sensors encircling the rib cage and abdomen to the skin to avoid displacement during exercise. Major excursions in the abdominal RIP signal related to leg motion with pedaling were noted (Fig 2 in our previous publication).¹ This required adjustments of the criterion for automatic, computer-assisted breath detection with progressive exercise. In the current study, no special fixation of RIP sensors contained within the garment was necessary. Walking at a brisk pace on the treadmill was also associated with artifacts in RIP raw waveforms (Fig 2). However, this did not require adjustment of the minimal volume change accepted as a breath by the computer algorithm from the default value of 25% of VT during the initial qualitative diagnostic calibration.¹¹⁴ This default value was preset in the software (VivoLogic), which employed similar concepts for automatic breath detection as we have previously described.¹ The robust computer-assisted breath detection achieved in the current study during treadmill exercise may have been related to a more favorable signal/noise ratio compared to bicycle exercise, and to the fact that the software (VivoLogic) applies digital filtering to RIP signals before performing breath detection and computation of breathing pattern variables (see the VivoLogic software user manual). It is also conceivable that the leg and body movements between bicycle and treadmill exercise might have been associated with different amounts of movement artifacts on respiratory waveforms.

According to recommended standards, the assessment of exercise performance is not based on breath-by breath values but on data averaged over > 30 to 60 s.¹³ Therefore, the comparison of mean RIP and flowmeter-derived values averaged over periods of 20 breaths (corresponding to approximately 30 s at maximal exercise) were also performed. This analysis revealed limits of agreement of ± 1% for TT, and ± 8% for VT and I (Fig 3). Thus, 95% of differences were expected to fall within these ranges. This indicates, for example, that a reduction in the ventilatory reserve measured by a flowmeter during maximal exercise by > 8% below the expected value will be detected by RIP in 97.5% of cases. Taking into account a tolerated inaccuracy of flowmeters within ± 5% (according to American Thoracic Society standards),²¹ and repeatability coefficients of 25 to 28% for maximal minute ventilation measured by a flowmeter during repeated bicycle exercise tests in the same individuals, 1 week apart,¹² the accuracy and precision of RIP achieved in the current study is excellent. Whether similar results can be obtained in other, less controlled settings, over longer time periods, and in more obese patients remains to be confirmed.

Based on measurements in healthy volunteers performing specific respiratory maneuvers and activities that induced rotation or flexion/extension of the vertebral spine and pelvis, Smith and Mead,¹⁰ and McCool and coworkers¹¹²² suggested that the estimation of lung volume changes based on data from body surface sensors could be improved by monitoring axial displacements by a magnetometer attached to the skin at the sternal and umbilical level as a third degree of freedom of chest wall motion, in addition to anteroposterior dimensions (measured by magnetometers) or cross-sections of the rib cage and abdomen (measured by RIP). Employing a portable ventilation monitor incorporating two pairs of magnetometers arranged in an elegant array so that their signals reflected anteroposterior rib cage and abdominal dimensions as well as the sternal-umbilical distance, McCool and coworkers²² achieved a satisfactory agreement of VT estimates compared to flowmeter measurements during submaximal bicycle exercise in nine healthy volunteers. At a mean VT of 1.74 L, the bias and the limits of agreement were 0.18 and ± 0.69 L, respectively, corresponding to a mean relative disagreement of 14%.²² In the current study involving maximal exercise, the bias and limits of agreement computed for all participants, including healthy subjects and patients, compare favorably with the cited results (the bias and the limits of agreement of VT were –0.01 ± 0.32 L, the mean disagreement was 7% at a mean VT of 1.93 L) [Table 3]. The accuracy of RIP did not differ among patients and healthy subjects without a backpack, and healthy subjects carrying a backpack that restricted the range of spinal motion by the metal frame and weight (Table 3). Therefore, the degrees of freedom of chest wall motion in addition to those monitored by the two RIP sensors, presumably induced by rigorous muscle contractions during maximal exercise, an elevated respiratory impedance in patients, or spinal flexion/extension or rotation, did not significantly affect lung volume estimates by RIP during maximal treadmill exercise.

In conclusion, we have demonstrated accurate, cooperation-independent measurement of ventilation by a novel, portable monitoring device during progressive treadmill exercise to exhaustion in healthy subjects and patients with cardiac and pulmonary diseases. The RIP monitor was able to identify differences in breathing patterns between healthy subjects and patients with cardiac or pulmonary disease. Therefore, portable RIP is a promising tool for unobtrusive respiratory monitoring in unrestrained subjects and patients for investigation of ventilatory adaptation to exercise and disease.

	Footnotes

 
Abbreviations: CHF = congestive heart failure; RIP = respiratory inductive plethysmography; TI/TT = duty cycle; TT = total duration of respiratory cycle; I = inspired minute ventilation; O₂max = maximal oxygen uptake; VT = tidal volume

Supported by grants from the Zurich Lung League and the Hartmann-Muller Stiftung Zurich. The RIP monitor (LifeShirt) was provided by VivoMetrics, Ventura, CA.

Received for publication October 16, 2004. Accepted for publication February 8, 2005.

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