Design and Implementation of Digital Asthma Diagnosis System

Design and Implementation of Digital Asthma Diagnosis System

Qinghua Yao, Xiantao Yang
DOI: 10.4018/IJHISI.2019070101
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In this article, the MSP430F149 is the microcontroller (MCU), and a pressure sensor, MPX5100AP, is used to measure body measurement of maximal forced expiratory volume (FEV) and peak expiratory flow rate (PEFR). The two analog signals are processed by the signal conditioning circuit, and then the corresponding digital signals are acquired by the MCU. With the related operations of multiple respiratory parameters, a built-up time of respiration signal mutation rate values and the determination of the mutation rate, a mathematical model is built among FEV, PEFR and the rate of variation. The mathematical model of the system is analyzed, and the relationship between the detection results and the degree of airway obstruction is established. Finally, the patient's condition analysis results are given directly on the LCD, which provided the objective indicators for the medical treatment of the disease.
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3. Principle Of Flow Velocity Measurement

At present, a widely accepted theory of gas flow measurement is to calculate the gas flow rate by comparing the delay difference between the two separated sensors and the distance between the two sensors (Wang, 2014). Through the character of gas flow sensor to capture the signal about the nature of the obtained material, the gas velocity signal is received. After acquiring sensors' signals, the signal of the corresponding back-end processing is to realize the measurement of gas flow rate. The related detection signal method of correlation coefficient is selected, which is shown in Figure 1. The basic idea of related measurement technique is to convert the flow velocity measurement to the time interval measurement by the analysis of the flow noise signal, and the gas flow rate is measured by the distance between the two sensors (Gretchen, 2002).

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