Masks effectively block larger respiratory droplets, but poor sealing or misuse can lead to particle leakage. Smaller exhaled particles, if virus-carrying, can linger in the air and increase infection risk. To address this issue, this research endeavours to develop the PEBAR by integrating a breath-responsive system. The objective is to optimize energy efficiency and user comfort while concurrently promoting environmental protection. The core components of the BR-PEBAR include a mask, a microcontroller board, a cartridge, and a DC blower. Initially, we create a program using Arduino to generate code that responds to breathing patterns. This code adjusts to variations in human breathing during system operation using a microcontroller and a pressure sensor inside the mask. Next, we examine how different factors affect the BR-PEBAR’s performance. This includes the location of the pressure sensor, tubing dimensions, and mask fit. The goal is to understand how each variable impacts the mask’s internal pressure and identify the most efficient configuration. Once operational parameters are established, we conduct tests to assess particle capture efficiency (CE) in real-world scenarios. During Arduino code development, choosing to average five simultaneous readings was selected to maintain balance, ensuring system precision and quick adjustments, as single readings can lead to extreme values and instability. Choosing a pressure sensing point below the mouth preserved mask transparency. Larger tubing diameter and shorter length minimized voltage requirements. After validation, the modified BR-PEBAR effectively managed up to 25 liters/minute with CE consistently above 99.5%. This suits routine respiratory activity and light exertion, reducing environmental pollution and Infection risk.
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Lin et al. (2024) studied this question.
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