Authors
Yuan Mao, Wei Zheng, Qian Chen
Published in
PloS one. Volume 21. Issue 9. Pages e0357672. Epub Sep 03, 2026.
Abstract
To address the safety risk of mistaking tap water or purified water for acidic electrolyzed oxidizing water (AEOW) during manual cleaning in central sterile supply departments (CSSDs), this study aimed to develop a low-cost, rapid identification device based on electrical conductivity differences to ensure the accuracy and safety of the disinfection process.
A lighthouse-shaped rapid identification device (LRID) was fabricated based on the significantly higher electrical conductivity of AEOW compared with tap water and purified water. Centered on an Arduino Nano microcontroller, the device integrates a conductivity sensor, a wireless charging module, and an LED indication system. It achieves automatic discrimination by detecting liquid electrical conductivity: the green LED remains illuminated for AEOW, while the red LED lights up for tap water or purified water. Identification accuracy, battery life, and waterproof performance were evaluated, and the satisfaction of CSSD technicians with the conventional pH test strip method and the LRID was compared.
The LRID achieved 100% identification accuracy (90/90) for AEOW, tap water, and purified water collected from the CSSDs of 10 hospitals. The average battery life was 83.75 ± 1.27 h, supporting a weekly charging schedule. All devices functioned normally after continuous immersion in AEOW for 30 days, confirming reliable waterproof performance. Scores from 28 CSSD technicians showed that the LRID was significantly superior to the pH test strip method in identification accuracy, ease of operation, and promotability (P < 0.001).
This study successfully developed and validated a low-cost (approximately 20 USD), highly reliable, and easy-to-operate AEOW rapid identification device. The LRID effectively prevents disinfection failures caused by liquid misuse in CSSDs and holds significant potential for its application and promotion.
PMID:
42691025
Bibliographic data and abstract were imported from PubMed on 04 Sep 2026.
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