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- All Subjects: Ambient Biometrics
- Creators: Forzani, Erica
- Creators: Pollat, Scott
Description
Flow measurement has always been one of the most critical processes in many industrial and clinical applications. The dynamic behavior of flow helps to define the state of a process. An industrial example would be that in an aircraft, where the rate of airflow passing the aircraft is used to determine the speed of the plane. A clinical example would be that the flow of a patient's breath which could help determine the state of the patient's lungs. This project is focused on the flow-meter that are used for airflow measurement in human lungs. In order to do these measurements, resistive-type flow-meters are commonly used in respiratory measurement systems. This method consists of passing the respiratory flow through a fluid resistive component, while measuring the resulting pressure drop, which is linearly related to volumetric flow rate. These types of flow-meters typically have a low frequency response but are adequate for most applications, including spirometry and respiration monitoring. In the case of lung parameter estimation methods, such as the Quick Obstruction Method, it becomes important to have a higher frequency response in the flow-meter so that the high frequency components in the flow are measurable. The following three types of flow-meters were: a. Capillary type b. Screen Pneumotach type c. Square Edge orifice type To measure the frequency response, a sinusoidal flow is generated with a small speaker and passed through the flow-meter that is connected to a large, rigid container. True flow is proportional to the derivative of the pressure inside the container. True flow is then compared with the measured flow, which is proportional to the pressure drop across the flow-meter. In order to do the characterization, two LabVIEW data acquisition programs have been developed, one for transducer calibration, and another one that records flow and pressure data for frequency response testing of the flow-meter. In addition, a model that explains the behavior exhibited by the flow-meter has been proposed and simulated. This model contains a fluid resistor and inductor in series. The final step in this project was to approximate the frequency response data to the developed model expressed as a transfer function.
ContributorsHu, Jianchen (Author) / Macia, Narciso (Thesis advisor) / Pollat, Scott (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2013
Description
Energy Expenditure (EE), a key diagnostic measurement for treatment of obesity, is measured via indirect calorimetry method through breath biomarkers of CO2 production and/or O2 consumption rates (VCO2 and/or VO2, respectively). Current technologies are limited due to prevailing designs requiring wearable facial accessories that present accuracy, precision, and usability concerns with regards to free living measurement. A novel medical device and smart home system, named Smart Pad, has been developed, with the capability of energy expenditure assessment via VCO2 measured from a room’s CO2 concentration. The system has 3 distinct capabilities: contactless EE measurement, air quality optimization via actuation of room ventilation, and efficiency optimization via ventilation actuation of only human-occupied environments. The Smart Pad shows accuracy of 90% for 14-19 minutes of resting measurement and accuracy of 90% for 4.8-7.0 minutes of exercise measurement after calibrating for air exchange rate (λ [hour-1]) using a reference method. Without reference instrument calibration, the Smart Pad system shows average accuracy of nearly 100% with correlations of Y=1.02X, R=0.761 for high resolution measurements and Y=1.06X, R=0.937 for averaged measurements over 50-60 minutes. In addition, the Smart Pad validation for contactless EE measurement has been performed in different environments, including a vehicle, medical office, a private office, and an ambulatory enclosure with rooms, ranging in volume from 3.1 m3 to 18.8m3. It was concluded that contactless EE measurements can be accurately performed in all tested scenarios with both low and high air exchange environments with λ ranging from 1.5 Hours-1 to 10.0 Hours -1. The system represents a new way to assess EE of individuals under free-living conditions in an unobstructive, passive, and accurate manner, and it is comparable or better in single breath gas measurement accuracy (with comparisons sourced from FDA data) than other medical devices (e.g. Vyntus CPXTM, MasterScreen CPXTM, Oxycon ProTM, and MedGemTM) which were 510(k) cleared by the FDA for prescription use in metabolic/cardiopulmonary diagnostics.
ContributorsSprowls, Mark (Author) / Forzani, Erica (Thesis advisor) / Destaillats, Hugo (Committee member) / Kulick, Doina (Committee member) / Nikkhah, Mehdi (Committee member) / Raupp, Gregory (Committee member) / Arizona State University (Publisher)
Created2021
Description
Energy Expenditure (EE) (kcal/day) is a key parameter used to guide obesity treatment, and it is often measured from CO2 production, VCO2 (mL/min), and/or O2 consumption, VO2 (mL/min) through the principles of indirect calorimetry. Current EE measurement technologies are limited due to the requirement of wearable facial accessories, which can introduce errors as measurements are not taken under free-living conditions. A novel contactless system, the SmartPad, which measures EE via VCO2 from a room’s ambient CO2 concentration transients was evaluated. First, SmartPad accuracy was validated by comparing the SmartPad’s EE and VCO2 measurements with the measurements of a reference instrument, the MGC Ultima CPXTM, in a cross-sectional study consisting of 20 subjects. A high correlation between the SmartPad’s EE and VCO2 measurements and the MGC Ultima CPX’s EE and VCO2 measurements was found, and the Bland-Altman plots contained a low mean bias for EE and VCO2 measurements. Thus, the SmartPad was validated as being accurate for VCO2 and EE measurements. Next, resting EE (REE) and exercise VCO2 measurements were recorded using the SmartPad and the MGC Ultima CPXTM at different operating CO2 threshold ranges to investigate the influence of measurement duration on system accuracy in an effort to optimize the SmartPad system. The SmartPad displayed 90% accuracy (±1 SD) for 14–19 min of REE measurement and for 4.8–7.0 min of exercise, using a known room’s air exchange rate. Additionally, the SmartPad was validated by accurately measuring subjects’ REE across a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m^2) with REEs ranging from ~1200 to ~3000 kcal/day. Lastly, the SmartPad has been used to assess the physical fitness of subjects via the “Contactless Thermodynamic Efficiency Test” (CTET).
ContributorsVictor, Shaun (Author) / Forzani, Erica (Thesis director) / Wang, Shaopeng (Committee member) / Barrett, The Honors College (Contributor) / Watts College of Public Service & Community Solut (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
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 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