{'fraction_non_alphanumeric': 0.012717852096090438, 'fraction_numerical': 0.0051813471502590676, 'mean_word_length': 4.883656509695291, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Automated Calibration Machine for Spirometers

Spirometer testing is the most adopted test by pulmonologists. It is used to evaluate the performance of the lungs of the patients suffering from COPD, Asthma and other conditions that affect breathing. The spirometer device needs periodic calibration since the results obtained are essential for the diagnosis of the patient. Currently the calibration of spirometers is done manually using a syringe. However, these syringes are not accurate and this is leading to incorrect calibration, thus leading to unneeded substitution of expensive spirometer devices and/or incorrect test results. The purpose of this work is the design and prototyping of an automated calibration machine that simulates the exhalation of a patient and reproduces graphs such as the peak expiratory flow curve. The prototyped system in this work will be used to control and/or calibrate any spirometer device. In order to simulate the human's exhalation based on predefined equations and graphs, a centrifugal fan with forward curved blades connected to an AC single phase motor were used. The flow in the pipe connecting the fan to the spirometer was simulated on Abaqus CFD model based on maximum Flow rate 10 L/s. And the pipe was designed according to the maximum pressure 405 Pa using Abaqus standard explicit model. The rotational speed of the motor was varied using a Variable Frequency Drive controlled using Arduino as microcontroller. In order to find a relationship between flow rate and frequency, a digital pitot tube anemometer and manometer was used. Then the flow rate was measured in the frequency range of 0 Hz to 100 Hz by taking the average value of 40 frequency samples per step. The machine is controlled from an Android mobile application using two modes: Manual and Automatic. The Manual mode allows the user to control the flow rate manually by selecting the suitable maximum peak expiratory flow values to run the test. The automatic mode was enabled by using an air flow sensor which allows the results to be obtained automatically as a feedback on the application's screen.