Determination of lung volume by hydrogen dilution at the time of underwater weighing

A method for measuring the volume of air in the lungs at the time of underwater weighing is described. A low concentration of hydrogen is used as a tracer gas in a closed-circuit rebreathing system. At the end of a normal exhalation the subject is connected to a respiratory bladder containing 2 L of air with a small admixture of hydrogen. After an equilibration period of five breaths the subject submerges completely, together with the bladder, and underwater weight is measured. Lung volume, at the time of weighing, is determined by hydrogen dilution. Using this method, the coefficient of variation for body density in the same individual was 0.23%.

Investigating and understanding CO2 levels in school classrooms

 It is a reported fact that a high CO2 concentration is a problem in school classrooms. However, the mere reporting of such results stops short of investigating causes; understanding is often missing. Steady-state results are often used in situations where changes occur frequently, such as varying student numbers, opening and closing classroom doors and windows and changing weather conditions. We revisit the mass balance model commonly used to predict or track CO2 concentrations in enclosed spaces as these factors change over time under varying conditions. This has prompted the study in several classrooms of actual air exchange rates, student exhalation rates, room volumes and ventilation design. In these cases, student numbers, room ventilation conditions (open and closed doors), room volume and the CO2 concentration have been recorded throughout the day. By fitting the model equation to the data, unknown parameters such as actual air change rates and CO2 exhalation rates per student can be determined. Having verified that the data can be modelled, we can predict behaviour in other cases such as a realistic rate of CO2 increase. This allows designers to size classrooms and ventilation systems to achieve a desired CO2 characteristic for known usages while saving energy.

Monitoring and analysis of respiratory patterns using microwave doppler radar

 Noncontact detection characteristic of Doppler radar provides an unobtrusive means of respiration detection and monitoring. This avoids additional preparations, such as physical sensor attachment or special clothing, which can be useful for certain healthcare applications. Furthermore, robustness of Doppler radar against environmental factors, such as light, ambient temperature, interference from other signals occupying the same bandwidth, fading effects, reduce environmental constraints and strengthens the possibility of employing Doppler radar in long-term respiration detection, and monitoring applications such as sleep studies. This paper presents an evaluation in the of use of microwave Doppler radar for capturing different dynamics of breathing patterns in addition to the respiration rate. Although finding the respiration rate is essential, identifying abnormal breathing patterns in real-time could be used to gain further insights into respiratory disorders and refine diagnostic procedures. Several known breathing disorders were professionally role played and captured in a real-time laboratory environment using a noncontact Doppler radar to evaluate the feasibility of this noncontact form of measurement in capturing breathing patterns under different conditions associated with certain breathing disorders. In addition to that, inhalation and exhalation flow patterns under different breathing scenarios were investigated to further support the feasibility of Doppler radar to accurately estimate the tidal volume. The results obtained for both experiments were compared with the gold standard measurement schemes, such as respiration belt and spirometry readings, yielding significant correlations with the Doppler radar-based information. In summary, Doppler radar is highlighted as an alternative approach not only for determining respiration rates, but also for identifying breathing patterns and tidal volumes as a preferred nonwearable alternative to the conventional - ontact sensing methods.

Non-contact measurement of respiratory function and deduction of tidal volume

 This paper further the investigation of Doppler radar feasibility in measuring the flow in and out due to inhalation and exhalation under different conditions of breathing activities. Three different experiment conditions were designed to investigate the feasibility and consistency of Doppler radar which includes the combination of the states of normal breathing, deep breathing and apnoea state were demonstrated. The obtained Doppler radar signals were correlated and compared with the gold standard medical device, spirometer, yielding a good correlations between both devices. We also demonstrated the calibration of the Doppler radar signal can be performed in a simple manner in order to have a good agreements with the spirometer readings. The measurement of the flow in and out during the breathing activities can be measured accurately under different dynamics of breathing as long as the calibration is performed correctly.

Noncontact detection and analysis of respiratory function using microwave Doppler Radar

Real-time respiratory measurement with Doppler Radar has an important advantage in the monitoring of certain conditions such as sleep apnoea, sudden infant death syndrome (SIDS), and many other general clinical uses requiring fast nonwearable and non-contact measurement of the respiratory function. In this paper, we demonstrate the feasibility of using Doppler Radar in measuring the basic respiratory frequencies (via fast Fourier transform) for four different types of breathing scenarios: normal breathing, rapid breathing, slow inhalation-fast exhalation, and fast inhalation-slow exhalation conducted in a laboratory environment. A high correlation factor was achieved between the Doppler Radar-based measurements and the conventional measurement device, a respiration strap. We also extended this work from basic signal acquisition to extracting detailed features of breathing function (I: E ratio). This facilitated additional insights into breathing activity and is likely to trigger a number of new applications in respiratory medicine.