Design and development of an automated MDI delivery system with breath detection for use with oxygen therapy

Eyasim, Muhammad Arshad

Design and development of an automated MDI delivery system with breath detection for use with oxygen therapy

Thesis / Dissertation

2024

Abstract

Introduction: Metered Dose Inhalers (MDI) are pressurised canisters that contain a bronchodilator medication used to treat obstructive lung disease symptoms. The medication is delivered to the lungs' airways by simultaneously actuating the MDI and inhaling, and the medication's effectiveness depends on optimal actuation-inhalation coordination. With the emergence of Covid-19, the use of MDI has increased among ventilated patients with Chronic Obstructive Pulmonary Disease or Asthma. This emphasised the difficulty with actuation-inhalation coordination, in which a nurse must remain by the bedside to monitor inhalation, time the actuations, and synchronise the actuations with inhalation, which is inaccurate because it more often falls outside the desired range of 0.2 s, resulting in lower drug effectiveness. To address the inaccurate actuation inhalation coordination and the limited number of Intensive Care Unit (ICU) resources, a need was identified for a device that can be used outside of ICU settings and can automatically deliver bronchodilator medications using MDIs. Methods: An automated MDI delivery system with breath detection was designed and developed. The device comprises of an actuation mechanism, a breath detection system, and a user interface. A cam and servo mechanism actuates the canister, the breath detection system detects inhalation with a pressure and flow rate sensor, and the user interface (UI) consists of a display and a rotary encoder. The device was tested using a continuous positive airway pressure device and a breathing simulator to validate the accuracy of the breath detection system, the accuracy of the actuation mechanism, and the device's operation. The device was then validated against the existing manual solution by comparing the delay between the actuation and the inhalation signal to determine the effectiveness of the developed device. Results: The developed device includes all the required functionalities and an intuitive UI. The device, however, is quite large and not impact-resistant; the noise during actuation can be disturbing, and it can only be used with canisters that do not require shaking before actuation. The device detects inhalation 0.11 s before the inhalation signal, and the servo actuates the canister in 0.25 s. This time difference of 0.14 s allows the medication to be delivered within the desired time after the onset of inhalation. Based on the user input settings, the device also operates as intended and the interval between actuations is the required 15 s. The automated test also shows a constant delay time of 0.14 s between the actuation and onset of inhalation, compared to the delays in the manual test, which vary and are mostly outside of the acceptable range. Conclusion: The results show that the device works as intended and is more effective than the existing manual solution by providing an automated and improved solution for bronchodilator therapy, thus increasing the medication delivery's effectiveness. Future recommendations are made to improve the device's design, and future work includes further validating the device's effectiveness.

Keywords

human biology

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