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Description
This work describes the development of a device for measuring CO2 in breath, which has applications in monitoring a variety of health issues, such as Chronic Obstructive Pulmonary Disease (COPD), asthma, and cardiovascular disease. The device takes advantage of colorimetric sensing technology in order to maintain a low cost and

This work describes the development of a device for measuring CO2 in breath, which has applications in monitoring a variety of health issues, such as Chronic Obstructive Pulmonary Disease (COPD), asthma, and cardiovascular disease. The device takes advantage of colorimetric sensing technology in order to maintain a low cost and high user-friendliness. The sensor consists of a pH dye, reactive element, and base coated on a highly porous Teflon membrane. The transmittance of the sensor is measured in the device via a simple LED/photodiode system, along with the flow rate, ambient relative humidity, and barometric pressure. The flow is measured by a newly developed flow meter described in this work, the Confined Pitot Tube (CPT) flow meter, which provides a high accuracy with reduced flow-resistance with a standard differential pressure transducer. I demonstrate in this work that the system has a high sensitivity, high specificity, fast time-response, high reproducibility, and good stability. The sensor has a simple calibration method which requires no action by the user, and utilizes a sophisticated, yet lightweight, model in order to predict temperature changes on the sensor during breathing and track changes in water content. It is shown to be effective for measuring CO2 waveform parameters on a breath-by-breath basis, such as End-Tidal CO2, Alveolar Plateau Slope, and Beginning Exhalation Slope.
ContributorsBridgeman, Devon (Author) / Forzani, Erica S (Thesis advisor) / Nikkhah, Mehdi (Committee member) / Holloway, Julianne (Committee member) / Raupp, Gregory (Committee member) / Emady, Heather (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Spirometry is a type of pulmonary function test that measures the amount of air volume and the speed of air flow from a patient's breath in order to assess lung function. The goal of this project is to develop and validate a mobile spirometer technology based on a differential pressure

Spirometry is a type of pulmonary function test that measures the amount of air volume and the speed of air flow from a patient's breath in order to assess lung function. The goal of this project is to develop and validate a mobile spirometer technology based on a differential pressure sensor. The findings in this paper are used in a larger project that combines the features of a capnography device and a spirometer into a single mobile health unit known as the capno-spirometer. The following paper discusses the methods, experiments, and prototypes that were developed and tested in order to create a robust and accurate technology for all of the spirometry functions within the capno-spirometer. The differential pressure sensor is set up with one inlet measuring the pressure inside the spirometer tubing and the other inlet measuring the ambient pressure of the environment. The inlet measuring the inside of the tubing is very sensitive to its orientation and position with respect to the path of the air flow. It is found that taking a measurement from the center of the flow is 50% better than from the side wall. The sensor inlet is optimized at 37 mm from the mouthpiece inlet. The unit is calibrated by relating the maximum pressure sensor voltage signal to the peak expiratory flow rate (PEF) taken during a series of spirometry tests. In conclusion, this relationship is best represented as a quadratic function and a calibration equation is computed to provide a flow rate given a voltage change. The flow rates are used to calculate the four main spirometry parameters: PEF, FVC, FEV1, and FER. These methods are then referenced with the results from a commercial spirometer for validation. After validation, the pressure-based spirometry technology is proven to be both robust and accurate.
ContributorsMiller, Dylan (Author) / Forzani, Erica (Thesis advisor) / Trimble, Steve (Committee member) / Xian, Xiaojun (Committee member) / Arizona State University (Publisher)
Created2013