Analysis of the Accuracy of Differential Pressure Sensor in a Portable Spirometry with FVC, FEV1 and PEF Parameters
Abstract
Accurate measurement of lung function is essential for diagnosing and monitoring respiratory diseases such as chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis. Traditional spirometry methods often face challenges related to accuracy and sensitivity, which can lead to misdiagnosis and inappropriate treatment. This study aims to evaluate the performance of the DF-Robot differential pressure sensor as a portable spirometry tool, focusing on key parameters including Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV1), and Peak Expiratory Flow (PEF). The research was conducted at the Surabaya Electromedical Engineering Department, utilizing a pre-experimental design with a single group. The DF-Robot sensor's output was compared against a Hans Rudolph 5530 Syringe Calibrator to determine its accuracy. Data collection involved three different tube sizes, with ten repetitions for each size using the calibrator, and five repetitions with human subjects to assess real-world applicability. Results indicated that the DF-Robot sensor demonstrated high accuracy, with the smallest tube size yielding a minimal error of 0.9%. In contrast, larger tube sizes resulted in significantly higher error rates, with the largest tube showing an error of 33%. The study concluded that the DF-Robot differential pressure sensor is a promising alternative for portable spirometry applications, providing reliable measurements of lung function parameters. The findings underscore the importance of sensor selection in spirometry, as the accuracy of measurements directly impacts patient diagnosis and treatment. This research contributes valuable insights into the development of portable spirometry devices, potentially enhancing the diagnostic capabilities for respiratory diseases and improving patient outcomes in clinical practice. Future studies should explore further refinements in sensor technology and methodologies to optimize spirometry accuracy and reliability
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