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Noninvasive Methods for Measuring Ventilation in Mobile Subjects
Measurements of Ventilation in Freely Ranging Subjects F Dennis McCool and Domyung Paek
Assessment of Heart Rate As a Predictor of Ventilation Jonathan M Samet, William E Lambert, David S James, Christine M Mermier, and Thomas W Chick
Ventilation, a measure of the frequency and depth of breathing, is an important determinant of the amounts of indoor and outdoor air pollutants that enter the respiratory tract. The Health Effects Institute funded two studies to develop and test methods for measuring ventilation in freely mobile subjects at home or at work. Drs. Dennis McCool and Domyung Paek at the Memorial Hospital in Rhode Island measured ventilation with a body surface displacement (BSD) model. Each subject wore wide elastic bands containing coated wire coils around the chest and abdomen and had special magnets affixed to the breastbone and navel. Changes in electrical signals from these devices indicated dimensional changes in the subject's body that were associated with breathing. After the BSD signals were calibrated with data from a spirometer (standard equipment for measuring breathing parameters), subsequent BSD measurements yielded data about a subject's breathing patterns, breath frequency, and ventilation.
In the second study, Dr. Jonathan Samet and colleagues at Johns Hopkins University wanted to develop methods for estimating ventilation from heart rate for future epidemiologic studies. Their 58 subjects included healthy adults and children, and adults with heart disease, lung disease, or asthma. First, the investigators collected spirometric and heart monitor data in the laboratory to plot ventilation–heart rate curves for each subject during cycling, vacuuming, and lifting. They then used heart monitor data to validate the accuracy of the Heartwatch, a portable, commercial device combining a small transmitter worn on the subject's chest with a wristwatch-style receiver that records heart rate. Finally, the investigators conducted a field study to estimate ventilation from Heartwatch data using a heart rate–ventilation calibration curve from a progressive exertion cycling test; they then categorized these ventilation data by activity using records maintained by the subjects.
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