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- All Subjects: Electrical Engineering
- All Subjects: Spirometry
- Genre: Academic theses
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
Wearable technology has brought in a rapid shift in the areas of healthcare and lifestyle management. The recent development and usage of wearable devices like smart watches has created significant impact in areas like fitness management, exercise tracking, sleep quality assessment and early diagnosis of diseases like asthma, sleep apnea etc. This thesis is dedicated to the development of wearable systems and algorithms to fulfill unmet needs in the area of cardiorespiratory monitoring.
First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.
Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.
Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.
The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.
First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.
Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.
Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.
The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.
ContributorsTipparaju, Vishal Varun (Author) / Xian, Xiaojun (Thesis advisor) / Forzani, Erica (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Angadi, Siddhartha (Committee member) / Arizona State University (Publisher)
Created2020
Description
Contaminated aerosols and micro droplets are easily generated by infected hosts through sneezing, coughing, speaking and breathing1-3 and harm humans’ health and the global economy. While most of the efforts are usually targeted towards protecting individuals from getting infected,4 eliminating transmissions from infection sources is also important to prevent disease transmission. Supportive therapies for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2) pneumonia such as oxygen supplementation, nebulizers and non-invasive mechanical ventilation all carry an increased risk for viral transmission via aerosol to healthcare workers.5-9 In this work, I study the efficacy of five methods for self-containing aerosols emitted from infected subjects undergoing nebulization therapies with a diverse spectrum on Non-Invasive Positive Pressure Ventilator (NIPPV) with oxygen delivery therapies. The work includes five study cases: Case I: Use of a Full-Face Mask with biofilter in bilevel positive airway pressure device (BiPAP) therapy, Case II: Use of surgical mask in High Flow Nasal Cannula (HFNC) therapy, Case III: Use of a modified silicone disposable mask in a HFNC therapy, Case IV: Use of a modified silicone disposable mask with a regular nebulizer and normal breathing, Case V: Use of a mitigation box with biofilter in a BiPAP. We demonstrate that while cases I, III and IV showed efficacies of 98-100%; cases II and V, which are the most commonly used, resulted with significantly lower efficacies of 10-24% to mitigate the dispersion of nebulization aerosols. Therefore, implementing cases I, III and IV in health care facilities may help battle the contaminations and infections via aerosol transmission during a pandemic.
ContributorsShyamala Pandian, Adithya (Author) / Forzani, Erica (Thesis advisor) / Patel, Bhavesh (Committee member) / Xian, Xiaojun (Committee member) / Arizona State University (Publisher)
Created2021
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