Exposure assessment by physiologic sampling pump - Prediction of minute ventilation using a portable respiratory inductive plethysmograph system

Ming Yi Lin, William A. Groves, Andris Freivalds, Gyung Lee Eun, Martin Harper, James E. Slaven, Larry Lee

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

A study was conducted to evaluate a portable respiratory inductive plethysmograph (RIP) as a means to estimate minute ventilation (V̇E) for use in controlling the flow rate of a physiologic sampling pump (PSP). Specific aims were to: (1) evaluate the ability of the portable RIP system to measure V̇E using a direct (individual) fixed-volume calibration method (Direct RIP model), (2) develop and evaluate the performance of indirect (group) regression models for V̇E prediction using output data from the portable RIP and subject demographic characteristics (Indirect RIP model), and (3) compare V̇E estimates from indirect and direct portable RIP calibration with indirect estimation models published previously. Nine subjects (19-44 years) were divided into calibration (n = 6) and test (n = 3) datasets and performed step-tests on three different days while wearing the portable RIP and breathing through a pneumotachometer (reference). Minute ventilation and portable RIP output including heart rate, breathing rate, and a motion index were recorded simultaneously during the 80 minute sessions. Calibration data were used to develop a regression model for V̇E prediction that was subsequently applied to the test dataset. Direct calibration of the portable RIP system produced highly variable estimates of V̇E (R2 = 0.62, average % error = 15 ± 50) while Indirect RIP model results were highly correlated with the reference (R2 = 0.80-0.88) and estimates of total volume were within 10% of reference values on average. Although developed from a limited dataset, the Indirect RIP model provided an alternative approach to estimation of V̇E and total volume with accuracy comparable to previously published models.

Original languageEnglish
Pages (from-to)1179-1186
Number of pages8
JournalJournal of Environmental Monitoring
Volume10
Issue number10
DOIs
Publication statusPublished - 2008 Oct 16

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health
  • Management, Monitoring, Policy and Law

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